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  <h1>Source code for torch.overrides</h1><div class="highlight"><pre>
<span></span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">Python implementation of ``__torch_function__``</span>

<span class="sd">While most of the torch API and handling for ``__torch_function__`` happens</span>
<span class="sd">at the C++ level, some of the torch API is written in Python so we need</span>
<span class="sd">python-level handling for ``__torch_function__`` overrides as well. The main</span>
<span class="sd">developer-facing functionality in this file are handle_torch_function and</span>
<span class="sd">has_torch_function. See torch/functional.py and test/test_overrides.py</span>
<span class="sd">for usage examples.</span>

<span class="sd">Note</span>
<span class="sd">----</span>
<span class="sd">heavily inspired by NumPy&#39;s ``__array_function__`` (see:</span>
<span class="sd">https://github.com/pytorch/pytorch/issues/24015 and</span>
<span class="sd">https://www.numpy.org/neps/nep-0018-array-function-protocol.html</span>
<span class="sd">)</span>

<span class="sd">If changing this file in a way that can affect ``__torch_function__`` overhead,</span>
<span class="sd">please report the benchmarks in ``benchmarks/overrides_benchmark``. See the</span>
<span class="sd">instructions in the ``README.md`` in that directory.</span>
<span class="sd">&quot;&quot;&quot;</span>

<span class="kn">import</span> <span class="nn">__future__</span>  <span class="c1"># noqa: F404</span>

<span class="kn">import</span> <span class="nn">collections</span>
<span class="kn">import</span> <span class="nn">contextlib</span>
<span class="kn">import</span> <span class="nn">functools</span>
<span class="kn">import</span> <span class="nn">types</span>
<span class="kn">import</span> <span class="nn">warnings</span>
<span class="kn">from</span> <span class="nn">functools</span> <span class="kn">import</span> <span class="n">wraps</span>
<span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Any</span><span class="p">,</span> <span class="n">Callable</span><span class="p">,</span> <span class="n">Dict</span><span class="p">,</span> <span class="n">Iterable</span><span class="p">,</span> <span class="n">List</span><span class="p">,</span> <span class="n">Optional</span><span class="p">,</span> <span class="n">Set</span><span class="p">,</span> <span class="n">Tuple</span><span class="p">,</span> <span class="n">Type</span>

<span class="kn">import</span> <span class="nn">torch</span>
<span class="kn">from</span> <span class="nn">torch._C</span> <span class="kn">import</span> <span class="p">(</span>
    <span class="n">_add_docstr</span><span class="p">,</span>
    <span class="n">_get_function_stack_at</span><span class="p">,</span>
    <span class="n">_has_torch_function</span><span class="p">,</span>
    <span class="n">_has_torch_function_unary</span><span class="p">,</span>
    <span class="n">_has_torch_function_variadic</span><span class="p">,</span>
    <span class="n">_is_torch_function_mode_enabled</span><span class="p">,</span>
    <span class="n">_len_torch_function_stack</span><span class="p">,</span>
    <span class="n">_pop_torch_function_stack</span><span class="p">,</span>
    <span class="n">_push_on_torch_function_stack</span><span class="p">,</span>
<span class="p">)</span>


<span class="n">__all__</span> <span class="o">=</span> <span class="p">[</span>
    <span class="s2">&quot;get_ignored_functions&quot;</span><span class="p">,</span>
    <span class="s2">&quot;get_overridable_functions&quot;</span><span class="p">,</span>
    <span class="s2">&quot;get_testing_overrides&quot;</span><span class="p">,</span>
    <span class="s2">&quot;handle_torch_function&quot;</span><span class="p">,</span>
    <span class="s2">&quot;has_torch_function&quot;</span><span class="p">,</span>
    <span class="s2">&quot;resolve_name&quot;</span><span class="p">,</span>
    <span class="s2">&quot;is_tensor_like&quot;</span><span class="p">,</span>
    <span class="s2">&quot;is_tensor_method_or_property&quot;</span><span class="p">,</span>
    <span class="s2">&quot;wrap_torch_function&quot;</span><span class="p">,</span>
    <span class="s2">&quot;enable_reentrant_dispatch&quot;</span><span class="p">,</span>
<span class="p">]</span>


<span class="k">def</span> <span class="nf">_disable_user_warnings</span><span class="p">(</span>
    <span class="n">func</span><span class="p">:</span> <span class="n">Callable</span><span class="p">,</span>
    <span class="n">regex</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">&quot;.*is deprecated, please use.*&quot;</span><span class="p">,</span>
    <span class="n">module</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">&quot;torch&quot;</span><span class="p">,</span>
<span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Callable</span><span class="p">:</span>
<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Decorator that temporarily disables ``UserWarning``s for the given ``module`` if the warning message matches the</span>
<span class="sd">    given ``regex`` pattern.</span>

<span class="sd">    Arguments</span>
<span class="sd">    ---------</span>
<span class="sd">    func : function</span>
<span class="sd">        Function to disable the warnings for.</span>
<span class="sd">    regex : str</span>
<span class="sd">        A regex pattern compilable by ``re.compile``. This is used to match the ``UserWarning`` message.</span>
<span class="sd">    module : str</span>
<span class="sd">        The python module to which the filtering should be restricted.</span>

<span class="sd">    Returns</span>
<span class="sd">    -------</span>
<span class="sd">    function</span>
<span class="sd">        The wrapped function.</span>
<span class="sd">    &quot;&quot;&quot;</span>

    <span class="nd">@wraps</span><span class="p">(</span><span class="n">func</span><span class="p">)</span>
    <span class="k">def</span> <span class="nf">wrapper</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
        <span class="k">with</span> <span class="n">warnings</span><span class="o">.</span><span class="n">catch_warnings</span><span class="p">():</span>
            <span class="n">warnings</span><span class="o">.</span><span class="n">filterwarnings</span><span class="p">(</span>
                <span class="s2">&quot;ignore&quot;</span><span class="p">,</span> <span class="n">category</span><span class="o">=</span><span class="ne">UserWarning</span><span class="p">,</span> <span class="n">message</span><span class="o">=</span><span class="n">regex</span><span class="p">,</span> <span class="n">module</span><span class="o">=</span><span class="n">module</span>
            <span class="p">)</span>
            <span class="k">return</span> <span class="n">func</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>

    <span class="k">return</span> <span class="n">wrapper</span>


<div class="viewcode-block" id="get_ignored_functions"><a class="viewcode-back" href="../../torch.overrides.html#torch.overrides.get_ignored_functions">[docs]</a><span class="nd">@functools</span><span class="o">.</span><span class="n">lru_cache</span><span class="p">(</span><span class="kc">None</span><span class="p">)</span>
<span class="nd">@_disable_user_warnings</span>
<span class="k">def</span> <span class="nf">get_ignored_functions</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="n">Set</span><span class="p">[</span><span class="n">Callable</span><span class="p">]:</span>
<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Return public functions that cannot be overridden by ``__torch_function__``.</span>

<span class="sd">    Returns</span>
<span class="sd">    -------</span>
<span class="sd">    Set[Callable]</span>
<span class="sd">        A tuple of functions that are publicly available in the torch API but cannot</span>
<span class="sd">        be overridden with ``__torch_function__``. Mostly this is because none of the</span>
<span class="sd">        arguments of these functions are tensors or tensor-likes.</span>

<span class="sd">    Examples</span>
<span class="sd">    --------</span>
<span class="sd">    &gt;&gt;&gt; torch.Tensor.as_subclass in torch.overrides.get_ignored_functions()</span>
<span class="sd">    True</span>
<span class="sd">    &gt;&gt;&gt; torch.add in torch.overrides.get_ignored_functions()</span>
<span class="sd">    False</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">Tensor</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span>
    <span class="k">return</span> <span class="p">{</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">typename</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">is_tensor</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">is_storage</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">set_default_tensor_type</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">set_default_device</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">get_default_device</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">set_rng_state</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">get_rng_state</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">manual_seed</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">initial_seed</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">seed</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">save</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">load</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">set_printoptions</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fork</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">get_default_dtype</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">get_num_interop_threads</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">get_num_threads</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">init_num_threads</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">import_ir_module</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">import_ir_module_from_buffer</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">is_anomaly_enabled</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">is_anomaly_check_nan_enabled</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">is_grad_enabled</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">merge_type_from_type_comment</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">parse_ir</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">parse_schema</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">parse_type_comment</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">set_anomaly_enabled</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">set_flush_denormal</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">set_num_interop_threads</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">set_num_threads</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">wait</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">as_tensor</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">from_numpy</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">default_generator</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">has_cuda</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">has_cudnn</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">has_lapack</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">device</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">finfo</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">has_mkl</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">has_mps</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">has_mkldnn</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">has_openmp</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">iinfo</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">memory_format</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">qscheme</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">set_grad_enabled</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">no_grad</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">enable_grad</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">inference_mode</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">is_inference_mode_enabled</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">layout</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">align_tensors</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">arange</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">as_strided</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">bartlett_window</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">blackman_window</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">broadcast_shapes</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">can_cast</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">compile</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">cudnn_affine_grid_generator</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">cudnn_batch_norm</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">cudnn_convolution</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">cudnn_convolution_transpose</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">cudnn_convolution_relu</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">cudnn_convolution_add_relu</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">cudnn_grid_sampler</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">cudnn_is_acceptable</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">empty</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">empty_permuted</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">empty_strided</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">empty_quantized</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">export</span><span class="o">.</span><span class="n">export</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">export</span><span class="o">.</span><span class="n">load</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">export</span><span class="o">.</span><span class="n">register_dataclass</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">export</span><span class="o">.</span><span class="n">save</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">eye</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">fftfreq</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">rfftfreq</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">from_file</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">full</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fill</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">hamming_window</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">hann_window</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">kaiser_window</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linspace</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">logspace</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">mkldnn_adaptive_avg_pool2d</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">mkldnn_convolution</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">mkldnn_max_pool2d</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">mkldnn_max_pool3d</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">mkldnn_linear_backward_weights</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">mkldnn_rnn_layer</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">normal</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">ones</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">promote_types</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">rand</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">randn</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">randint</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">randperm</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">range</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">result_type</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">scalar_tensor</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">sparse_coo_tensor</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">sparse_compressed_tensor</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">sparse_csr_tensor</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">sparse_csc_tensor</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">sparse_bsr_tensor</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">sparse_bsc_tensor</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">sym_constrain_range</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">sym_constrain_range_for_size</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">sym_fresh_size</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">tril_indices</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">triu_indices</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">vander</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">zeros</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">_jit_internal</span><span class="o">.</span><span class="n">boolean_dispatch</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">assert_int_or_pair</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">upsample</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">upsample_bilinear</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">upsample_nearest</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">has_torch_function</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">has_torch_function_unary</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">has_torch_function_variadic</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">handle_torch_function</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">sigmoid</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">hardsigmoid</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">tanh</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">_canonical_mask</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">_none_or_dtype</span><span class="p">,</span>
        <span class="c1"># Doesn&#39;t actually take or return tensor arguments</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">init</span><span class="o">.</span><span class="n">calculate_gain</span><span class="p">,</span>
        <span class="c1"># These are deprecated; don&#39;t test them</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">init</span><span class="o">.</span><span class="n">uniform</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">init</span><span class="o">.</span><span class="n">normal</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">init</span><span class="o">.</span><span class="n">constant</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">init</span><span class="o">.</span><span class="n">eye</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">init</span><span class="o">.</span><span class="n">dirac</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">init</span><span class="o">.</span><span class="n">xavier_uniform</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">init</span><span class="o">.</span><span class="n">xavier_normal</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">init</span><span class="o">.</span><span class="n">kaiming_uniform</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">init</span><span class="o">.</span><span class="n">kaiming_normal</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">init</span><span class="o">.</span><span class="n">orthogonal</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">init</span><span class="o">.</span><span class="n">sparse</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nested</span><span class="o">.</span><span class="n">to_padded_tensor</span><span class="p">,</span>
        <span class="n">has_torch_function</span><span class="p">,</span>
        <span class="n">handle_torch_function</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">set_autocast_enabled</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">is_autocast_enabled</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">set_autocast_dtype</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">get_autocast_dtype</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">clear_autocast_cache</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">set_autocast_cpu_enabled</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">is_autocast_cpu_enabled</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">set_autocast_xla_enabled</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">is_autocast_xla_enabled</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">set_autocast_ipu_enabled</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">is_autocast_ipu_enabled</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">set_autocast_cpu_dtype</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">get_autocast_cpu_dtype</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">set_autocast_ipu_dtype</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">get_autocast_ipu_dtype</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">get_autocast_gpu_dtype</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">set_autocast_gpu_dtype</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">get_autocast_xla_dtype</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">set_autocast_xla_dtype</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">autocast_increment_nesting</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">autocast_decrement_nesting</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">is_autocast_cache_enabled</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">set_autocast_cache_enabled</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">hardswish</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">is_vulkan_available</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">are_deterministic_algorithms_enabled</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">use_deterministic_algorithms</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">is_deterministic_algorithms_warn_only_enabled</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">set_deterministic_debug_mode</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">get_device_module</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">get_deterministic_debug_mode</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">set_float32_matmul_precision</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">get_float32_matmul_precision</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">unify_type_list</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">is_warn_always_enabled</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">set_warn_always</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">vitals_enabled</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">set_vital</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">read_vitals</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">vmap</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">cond</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">frombuffer</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">asarray</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">_functional_sym_constrain_range</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">_make_dep_token</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__delitem__</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__dir__</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__getattribute__</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__init__</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__iter__</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">__init_subclass__</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__delattr__</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__setattr__</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">__torch_function__</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">__torch_dispatch__</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__new__</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="vm">__class__</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">__subclasshook__</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__hash__</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">as_subclass</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">eig</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">lstsq</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">reinforce</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">new</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">new_tensor</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">new_empty</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">new_empty_strided</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">new_zeros</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">new_ones</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">new_full</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_make_subclass</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">solve</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">symeig</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">stride</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">unflatten</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">to_sparse_coo</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">to_sparse_csr</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">to_sparse_csc</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">to_sparse_bsr</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">to_sparse_bsc</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_to_sparse</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_to_sparse_csr</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_to_sparse_csc</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_to_sparse_bsr</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_to_sparse_bsc</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_typed_storage</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_reduce_ex_internal</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_fix_weakref</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_view_func</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_view_func_unsafe</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_rev_view_func_unsafe</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_make_wrapper_subclass</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_python_dispatch</span><span class="o">.</span><span class="fm">__get__</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_has_symbolic_sizes_strides</span><span class="o">.</span><span class="fm">__get__</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_conj</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_conj_physical</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_lazy_clone</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_neg_view</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_is_zerotensor</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_is_all_true</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_is_any_true</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_addmm_activation</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">to_padded_tensor</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_use_count</span><span class="p">,</span>
    <span class="p">}</span></div>


<span class="nd">@functools</span><span class="o">.</span><span class="n">lru_cache</span><span class="p">(</span><span class="kc">None</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">get_default_nowrap_functions</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="n">Set</span><span class="p">[</span><span class="n">Callable</span><span class="p">]:</span>
<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Return public functions that do not wrap in a subclass when invoked by</span>
<span class="sd">    the default ``Tensor.__torch_function__`` that preserves subclasses.  Typically,</span>
<span class="sd">    these functions represent field accesses (i.e., retrieving a Tensor that</span>
<span class="sd">    is stored somewhere on the Tensor) as opposed to computation.  Users of</span>
<span class="sd">    these functions expect object identity to be preserved over multiple accesses</span>
<span class="sd">    (e.g., ``a.grad is a.grad``) which cannot be upheld if we&#39;re wrapping on</span>
<span class="sd">    the fly every time (furthermore, the tensor stored here might already be</span>
<span class="sd">    the subclass, in which case wrapping really ought not to happen).</span>

<span class="sd">    Not ALL property accessors have this property; for example ``Tensor.T`` actually</span>
<span class="sd">    just creates a new transposed tensor on the fly, and so we SHOULD interpose on</span>
<span class="sd">    these calls (you need to check the implementation of the function to see if</span>
<span class="sd">    this is the case or not).  Additionally, if a property accessor doesn&#39;t return a Tensor,</span>
<span class="sd">    it doesn&#39;t have to be on this list (though it is harmless if it is).</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">Tensor</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span>
    <span class="k">return</span> <span class="p">{</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_base</span><span class="o">.</span><span class="fm">__get__</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">grad</span><span class="o">.</span><span class="fm">__get__</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_grad</span><span class="o">.</span><span class="fm">__get__</span><span class="p">,</span>
    <span class="p">}</span>


<div class="viewcode-block" id="get_testing_overrides"><a class="viewcode-back" href="../../torch.overrides.html#torch.overrides.get_testing_overrides">[docs]</a><span class="nd">@functools</span><span class="o">.</span><span class="n">lru_cache</span><span class="p">(</span><span class="kc">None</span><span class="p">)</span>
<span class="nd">@_disable_user_warnings</span>
<span class="k">def</span> <span class="nf">get_testing_overrides</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="n">Dict</span><span class="p">[</span><span class="n">Callable</span><span class="p">,</span> <span class="n">Callable</span><span class="p">]:</span>
<span class="w">    </span><span class="sd">&quot;&quot;&quot;Return a dict containing dummy overrides for all overridable functions</span>

<span class="sd">    Returns</span>
<span class="sd">    -------</span>
<span class="sd">    Dict[Callable, Callable]</span>
<span class="sd">        A dictionary that maps overridable functions in the PyTorch API to</span>
<span class="sd">        lambda functions that have the same signature as the real function</span>
<span class="sd">        and unconditionally return -1. These lambda functions are useful</span>
<span class="sd">        for testing API coverage for a type that defines ``__torch_function__``.</span>

<span class="sd">    Examples</span>
<span class="sd">    --------</span>
<span class="sd">    &gt;&gt;&gt; import inspect</span>
<span class="sd">    &gt;&gt;&gt; my_add = torch.overrides.get_testing_overrides()[torch.add]</span>
<span class="sd">    &gt;&gt;&gt; inspect.signature(my_add)</span>
<span class="sd">    &lt;Signature (input, other, out=None)&gt;</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="c1"># Every function in the PyTorchAPI that can be overriden needs an entry</span>
    <span class="c1"># in this dict.</span>
    <span class="c1">#</span>
    <span class="c1"># Optimally we would use inspect to get the function signature and define</span>
    <span class="c1"># the lambda function procedurally but that is blocked by generating</span>
    <span class="c1"># function signatures for native kernels that can be consumed by inspect.</span>
    <span class="c1"># See Issue #28233.</span>
    <span class="n">Tensor</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span>
    <span class="n">ret</span><span class="p">:</span> <span class="n">Dict</span><span class="p">[</span><span class="n">Callable</span><span class="p">,</span> <span class="n">Callable</span><span class="p">]</span> <span class="o">=</span> <span class="p">{</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">abs</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">absolute</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">adaptive_avg_pool1d</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">output_size</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">adaptive_max_pool1d</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">inputs</span><span class="p">,</span> <span class="n">output_size</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">acos</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">adjoint</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">arccos</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">acosh</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">arccosh</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">add</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">addbmm</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">batch1</span><span class="p">,</span> <span class="n">batch2</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">beta</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">addcdiv</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">tensor1</span><span class="p">,</span> <span class="n">tensor2</span><span class="p">,</span> <span class="n">value</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">addcmul</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">tensor1</span><span class="p">,</span> <span class="n">tensor2</span><span class="p">,</span> <span class="n">value</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">addmm</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">mat1</span><span class="p">,</span> <span class="n">mat2</span><span class="p">,</span> <span class="n">beta</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">addmv</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">mat</span><span class="p">,</span> <span class="n">vec</span><span class="p">,</span> <span class="n">beta</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">addr</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">vec1</span><span class="p">,</span> <span class="n">vec2</span><span class="p">,</span> <span class="n">beta</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">affine_grid_generator</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">theta</span><span class="p">,</span> <span class="n">size</span><span class="p">,</span> <span class="n">align_corners</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">all</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">allclose</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">trol</span><span class="o">=</span><span class="mf">1e-05</span><span class="p">,</span> <span class="n">atol</span><span class="o">=</span><span class="mf">1e-08</span><span class="p">,</span> <span class="n">equal_nan</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">alpha_dropout</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">p</span><span class="p">,</span> <span class="n">train</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">amax</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">amin</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">aminmax</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">keepdim</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">angle</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">any</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">keepdim</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">argmax</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">argmin</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">argsort</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">asin</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">_assert_async</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">msg</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">arcsin</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">asinh</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">arcsinh</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">atan</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">arctan</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">atan2</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">arctan2</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">atanh</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">arctanh</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">atleast_1d</span><span class="p">:</span> <span class="k">lambda</span> <span class="o">*</span><span class="n">tensors</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">atleast_2d</span><span class="p">:</span> <span class="k">lambda</span> <span class="o">*</span><span class="n">tensors</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">atleast_3d</span><span class="p">:</span> <span class="k">lambda</span> <span class="o">*</span><span class="n">tensors</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">avg_pool1d</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">padding</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">ceil_mode</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">count_include_pad</span><span class="o">=</span><span class="kc">True</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">baddbmm</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">batch1</span><span class="p">,</span> <span class="n">batch2</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">beta</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">batch_norm</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">bias</span><span class="p">,</span> <span class="n">running_mean</span><span class="p">,</span> <span class="n">running_var</span><span class="p">,</span> <span class="n">training</span><span class="p">,</span> <span class="n">momentum</span><span class="p">,</span> <span class="n">eps</span><span class="p">,</span> <span class="n">cudnn_enabled</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">batch_norm_backward_elemt</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">grad_out</span><span class="p">,</span> <span class="nb">input</span><span class="p">,</span> <span class="n">mean</span><span class="p">,</span> <span class="n">invstd</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">sum_dy</span><span class="p">,</span> <span class="n">sum_dy_xmu</span><span class="p">,</span> <span class="n">count_tensor</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">batch_norm_backward_reduce</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">grad_out</span><span class="p">,</span> <span class="nb">input</span><span class="p">,</span> <span class="n">mean</span><span class="p">,</span> <span class="n">invstd</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">input_g</span><span class="p">,</span> <span class="n">weight_g</span><span class="p">,</span> <span class="n">bias_g</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">batch_norm_elemt</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">bias</span><span class="p">,</span> <span class="n">mean</span><span class="p">,</span> <span class="n">invstd</span><span class="p">,</span> <span class="n">eps</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">batch_norm_gather_stats</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">mean</span><span class="p">,</span> <span class="n">invstd</span><span class="p">,</span> <span class="n">running_mean</span><span class="p">,</span> <span class="n">running_var</span><span class="p">,</span> <span class="n">momentum</span><span class="p">,</span> <span class="n">eps</span><span class="p">,</span> <span class="n">count</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">batch_norm_gather_stats_with_counts</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">mean</span><span class="p">,</span> <span class="n">invstd</span><span class="p">,</span> <span class="n">running_mean</span><span class="p">,</span> <span class="n">running_var</span><span class="p">,</span> <span class="n">momentum</span><span class="p">,</span> <span class="n">eps</span><span class="p">,</span> <span class="n">count</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">batch_norm_stats</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">eps</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">batch_norm_update_stats</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">running_mean</span><span class="p">,</span> <span class="n">running_var</span><span class="p">,</span> <span class="n">momentum</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">bernoulli</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">generator</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">bilinear</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">input1</span><span class="p">,</span> <span class="n">input2</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">bias</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">binary_cross_entropy_with_logits</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">size_average</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduce</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduction</span><span class="o">=</span><span class="s2">&quot;mean&quot;</span><span class="p">,</span> <span class="n">pos_weight</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">bincount</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">weights</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">minlength</span><span class="o">=</span><span class="mi">0</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">binomial</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">count</span><span class="p">,</span> <span class="n">prob</span><span class="p">,</span> <span class="n">generator</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">bitwise_and</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">bitwise_not</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">bitwise_or</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">bitwise_xor</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">bitwise_left_shift</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">bitwise_right_shift</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">block_diag</span><span class="p">:</span> <span class="k">lambda</span> <span class="o">*</span><span class="n">tensors</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">bmm</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">mat2</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">broadcast_tensors</span><span class="p">:</span> <span class="k">lambda</span> <span class="o">*</span><span class="n">tensors</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">broadcast_to</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">size</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">bucketize</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">boundaries</span><span class="p">,</span> <span class="n">out_int32</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">right</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">cartesian_prod</span><span class="p">:</span> <span class="k">lambda</span> <span class="o">*</span><span class="n">tensors</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">cat</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">tensors</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">concat</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">tensors</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>  <span class="c1"># alias for torch.cat</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">concatenate</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">tensors</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>  <span class="c1"># alias for torch.concatenate</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">cdist</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">x1</span><span class="p">,</span> <span class="n">x2</span><span class="p">,</span> <span class="n">p</span><span class="o">=</span><span class="mf">2.0</span><span class="p">,</span> <span class="n">compute_mode</span><span class="o">=</span><span class="s2">&quot;use_mm_for_euclid_dist_if_necessary&quot;</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">ceil</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">celu</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">chain_matmul</span><span class="p">:</span> <span class="k">lambda</span> <span class="o">*</span><span class="n">matrices</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">channel_shuffle</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">groups</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">cholesky</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">upper</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">cholesky</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">cholesky_ex</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">check_errors</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">cholesky_inverse</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">upper</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">cholesky_solve</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">input1</span><span class="p">,</span> <span class="n">input2</span><span class="p">,</span> <span class="n">upper</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">choose_qparams_optimized</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">numel</span><span class="p">,</span> <span class="n">n_bins</span><span class="p">,</span> <span class="n">ratio</span><span class="p">,</span> <span class="n">bit_width</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">chunk</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">chunks</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">clamp</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="nb">min</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="nb">max</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">clip</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="nb">min</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="nb">max</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">clamp_min</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="nb">min</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">clamp_max</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="nb">max</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">column_stack</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">tensors</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">cov</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">correction</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">fweights</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">aweights</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">clone</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">combinations</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">r</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">with_replacement</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">complex</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">real</span><span class="p">,</span> <span class="n">imag</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">copysign</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">polar</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">abs</span><span class="p">,</span> <span class="n">ang</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">cond</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="nb">ord</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">conj</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">conj_physical</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">resolve_conj</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">resolve_neg</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">constant_pad_nd</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">pad</span><span class="p">,</span> <span class="n">value</span><span class="o">=</span><span class="mi">0</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">conv1d</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">bias</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">padding</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">dilation</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">groups</span><span class="o">=</span><span class="mi">1</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">conv2d</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">bias</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">padding</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">dilation</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">groups</span><span class="o">=</span><span class="mi">1</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">conv3d</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">bias</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">padding</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">dilation</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">groups</span><span class="o">=</span><span class="mi">1</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">convolution</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">bias</span><span class="p">,</span> <span class="n">stride</span><span class="p">,</span> <span class="n">padding</span><span class="p">,</span> <span class="n">dilation</span><span class="p">,</span> <span class="n">transposed</span><span class="p">,</span> <span class="n">output_adding</span><span class="p">,</span> <span class="n">groups</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">conv_tbc</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">bias</span><span class="p">,</span> <span class="n">pad</span><span class="o">=</span><span class="mi">0</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">conv_transpose1d</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">bias</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">padding</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">output_padding</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">groups</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">dilation</span><span class="o">=</span><span class="mi">1</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">conv_transpose2d</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">bias</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">padding</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">output_padding</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">groups</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">dilation</span><span class="o">=</span><span class="mi">1</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">conv_transpose3d</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">bias</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">padding</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">output_padding</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">groups</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">dilation</span><span class="o">=</span><span class="mi">1</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">corrcoef</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">cos</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">cosine_embedding_loss</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">input1</span><span class="p">,</span> <span class="n">input2</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">margin</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">size_average</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduce</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduction</span><span class="o">=</span><span class="s2">&quot;mean&quot;</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">cosh</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">cosine_similarity</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">x1</span><span class="p">,</span> <span class="n">x2</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="mf">1e-8</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">count_nonzero</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">cross</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">cross</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">dim</span><span class="o">=-</span><span class="mi">1</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">ctc_loss</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="n">log_probs</span><span class="p">,</span> <span class="n">targets</span><span class="p">,</span> <span class="n">input_lengths</span><span class="p">,</span> <span class="n">target_lengths</span><span class="p">,</span> <span class="n">blank</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">reduction</span><span class="o">=</span><span class="s2">&quot;mean&quot;</span><span class="p">,</span> <span class="n">zero_infinity</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">cummax</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">cummin</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">cumprod</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">cumsum</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">cumulative_trapezoid</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">y</span><span class="p">,</span> <span class="n">x</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dim</span><span class="o">=-</span><span class="mi">1</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">logcumsumexp</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">deg2rad</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">dequantize</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">det</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">det</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>  <span class="c1"># alias for torch.det  # type: ignore[attr-defined]</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">detach</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">diag</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">diagonal</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">diag_embed</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">diagonal</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">diagflat</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">offset</span><span class="o">=</span><span class="mi">0</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">diff</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">n</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">dim</span><span class="o">=-</span><span class="mi">1</span><span class="p">,</span> <span class="n">prepend</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">append</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">diagonal</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">offset</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">dim1</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">dim2</span><span class="o">=</span><span class="mi">1</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">diagonal</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">offset</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">dim1</span><span class="o">=-</span><span class="mi">2</span><span class="p">,</span> <span class="n">dim2</span><span class="o">=-</span><span class="mi">1</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">diagonal_scatter</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">src</span><span class="p">,</span> <span class="n">offset</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">dim1</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">dim2</span><span class="o">=</span><span class="mi">1</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">as_strided_scatter</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">src</span><span class="p">,</span> <span class="n">size</span><span class="p">,</span> <span class="n">stride</span><span class="p">,</span> <span class="n">storage_offset</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">digamma</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">dist</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">p</span><span class="o">=</span><span class="mi">2</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">div</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">rounding_mode</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">divide</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">rounding_mode</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">dot</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">dropout</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">p</span><span class="p">,</span> <span class="n">train</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">dsmm</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">mat2</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">hsmm</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">mat1</span><span class="p">,</span> <span class="n">mat2</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">dsplit</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">indices_or_sections</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">dstack</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">tensors</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">eig</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">eigvals</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">eigh</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">UPLO</span><span class="o">=</span><span class="s2">&quot;L&quot;</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">eigvalsh</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">UPLO</span><span class="o">=</span><span class="s2">&quot;L&quot;</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">einsum</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">equation</span><span class="p">,</span> <span class="o">*</span><span class="n">operands</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">embedding</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">padding_idx</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">max_norm</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">norm_type</span><span class="o">=</span><span class="mf">2.0</span><span class="p">,</span> <span class="n">scale_grad_by_freq</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">sparse</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>  <span class="c1"># noqa: B950</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">embedding_bag</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">offsets</span><span class="p">,</span> <span class="n">max_norm</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">norm_type</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">scale_grad_by_freq</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">&quot;mean&quot;</span><span class="p">,</span> <span class="n">sparse</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">per_sample_weights</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">padding_idx</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>  <span class="c1"># noqa: B950</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">empty_like</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">layout</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">device</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">requires_grad</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">eq</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">equal</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">erf</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">erfc</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">erfinv</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">exp</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">exp2</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">expm1</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fake_quantize_per_channel_affine</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">scale</span><span class="p">,</span> <span class="n">zero_point</span><span class="p">,</span> <span class="n">axis</span><span class="p">,</span> <span class="n">quant_min</span><span class="p">,</span> <span class="n">quant_max</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fake_quantize_per_tensor_affine</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">scale</span><span class="p">,</span> <span class="n">zero_point</span><span class="p">,</span> <span class="n">quant_min</span><span class="p">,</span> <span class="n">quant_max</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fused_moving_avg_obs_fake_quant</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="n">observer_on</span><span class="p">,</span> <span class="n">fake_quant_on</span><span class="p">,</span> <span class="n">averaging_const</span><span class="p">,</span> <span class="n">running_min</span><span class="p">,</span> <span class="n">running_max</span><span class="p">,</span> <span class="n">scale</span><span class="p">,</span> <span class="n">zero_point</span><span class="p">,</span> <span class="n">quant_min</span><span class="p">,</span> <span class="n">quant_max</span><span class="p">,</span> <span class="n">ch_axis</span><span class="p">,</span> <span class="n">per_row_fake_quant</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">symmetric_quant</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>  <span class="c1"># noqa: B950</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fbgemm_linear_fp16_weight</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">packed_weight</span><span class="p">,</span> <span class="n">bias</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fbgemm_linear_fp16_weight_fp32_activation</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">packed_weight</span><span class="p">,</span> <span class="n">bias</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fbgemm_linear_int8_weight</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">packed</span><span class="p">,</span> <span class="n">col_offsets</span><span class="p">,</span> <span class="n">weight_scale</span><span class="p">,</span> <span class="n">weight_zero_point</span><span class="p">,</span> <span class="n">bias</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>  <span class="c1"># noqa: B950</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fbgemm_linear_int8_weight_fp32_activation</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">packed</span><span class="p">,</span> <span class="n">col_offsets</span><span class="p">,</span> <span class="n">weight_scale</span><span class="p">,</span> <span class="n">weight_zero_point</span><span class="p">,</span> <span class="n">bias</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fbgemm_linear_quantize_weight</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fbgemm_pack_gemm_matrix_fp16</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fbgemm_pack_quantized_matrix</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">feature_alpha_dropout</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">p</span><span class="p">,</span> <span class="n">train</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">feature_dropout</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">p</span><span class="p">,</span> <span class="n">train</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">ifft</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">n</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dim</span><span class="o">=-</span><span class="mi">1</span><span class="p">,</span> <span class="n">norm</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">rfft</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">n</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dim</span><span class="o">=-</span><span class="mi">1</span><span class="p">,</span> <span class="n">norm</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">irfft</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">n</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dim</span><span class="o">=-</span><span class="mi">1</span><span class="p">,</span> <span class="n">norm</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">hfft</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">n</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dim</span><span class="o">=-</span><span class="mi">1</span><span class="p">,</span> <span class="n">norm</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">ihfft</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">n</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dim</span><span class="o">=-</span><span class="mi">1</span><span class="p">,</span> <span class="n">norm</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">hfft2</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">s</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="p">(</span><span class="o">-</span><span class="mi">2</span><span class="p">,</span> <span class="o">-</span><span class="mi">1</span><span class="p">),</span> <span class="n">norm</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">ihfft2</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">s</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="p">(</span><span class="o">-</span><span class="mi">2</span><span class="p">,</span> <span class="o">-</span><span class="mi">1</span><span class="p">),</span> <span class="n">norm</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">hfftn</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">s</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dim</span><span class="o">=-</span><span class="mi">1</span><span class="p">,</span> <span class="n">norm</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">ihfftn</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">s</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dim</span><span class="o">=-</span><span class="mi">1</span><span class="p">,</span> <span class="n">norm</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">fftn</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">s</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">norm</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">ifftn</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">s</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">norm</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">rfftn</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">s</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">norm</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">irfftn</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">s</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">norm</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">fft2</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">s</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="p">(</span><span class="o">-</span><span class="mi">2</span><span class="p">,</span> <span class="o">-</span><span class="mi">1</span><span class="p">),</span> <span class="n">norm</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">ifft2</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">s</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="p">(</span><span class="o">-</span><span class="mi">2</span><span class="p">,</span> <span class="o">-</span><span class="mi">1</span><span class="p">),</span> <span class="n">norm</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">rfft2</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">s</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="p">(</span><span class="o">-</span><span class="mi">2</span><span class="p">,</span> <span class="o">-</span><span class="mi">1</span><span class="p">),</span> <span class="n">norm</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">irfft2</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">s</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="p">(</span><span class="o">-</span><span class="mi">2</span><span class="p">,</span> <span class="o">-</span><span class="mi">1</span><span class="p">),</span> <span class="n">norm</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">fftshift</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">ifftshift</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">fft</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">n</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dim</span><span class="o">=-</span><span class="mi">1</span><span class="p">,</span> <span class="n">norm</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fix</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">flatten</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">start_dim</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">end_dim</span><span class="o">=-</span><span class="mi">1</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">flip</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dims</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fliplr</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">flipud</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">frobenius_norm</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">keepdim</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">floor</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">floor_divide</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">float_power</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">exponent</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fmod</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">frac</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">frexp</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">full_like</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">fill_value</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">layout</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">strided</span><span class="p">,</span> <span class="n">device</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">requires_grad</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>  <span class="c1"># noqa: B950</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">_functional_assert_async</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">msg</span><span class="p">,</span> <span class="n">dep_token</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">lu_unpack</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">LU_data</span><span class="p">,</span> <span class="n">LU_pivots</span><span class="p">,</span> <span class="n">unpack_data</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">unpack_pivots</span><span class="o">=</span><span class="kc">True</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">gather</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="p">,</span> <span class="n">index</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">sparse_grad</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">gcd</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">ge</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">get_device</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">greater_equal</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">geqrf</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">i0</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">inner</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">outer</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">vec2</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">ger</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">vec2</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>  <span class="c1"># alias for torch.outer</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">gradient</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">spacing</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">edge_order</span><span class="o">=</span><span class="mi">1</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">grid_sampler</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">grid</span><span class="p">,</span> <span class="n">interpolation_mode</span><span class="p">,</span> <span class="n">padding_mode</span><span class="p">,</span> <span class="n">align_corners</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">grid_sampler_2d</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">grid</span><span class="p">,</span> <span class="n">interpolation_mode</span><span class="p">,</span> <span class="n">padding_mode</span><span class="p">,</span> <span class="n">align_corners</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">grid_sampler_3d</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">grid</span><span class="p">,</span> <span class="n">interpolation_mode</span><span class="p">,</span> <span class="n">padding_mode</span><span class="p">,</span> <span class="n">align_corners</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">group_norm</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">num_groups</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">bias</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="mf">1e-05</span><span class="p">,</span> <span class="n">cudnn_enabled</span><span class="o">=</span><span class="kc">True</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">gru</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">hx</span><span class="p">,</span> <span class="n">params</span><span class="p">,</span> <span class="n">has_biases</span><span class="p">,</span> <span class="n">num_layers</span><span class="p">,</span> <span class="n">dropout</span><span class="p">,</span> <span class="n">train</span><span class="p">,</span> <span class="n">bidirectional</span><span class="p">,</span> <span class="n">batch_first</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">gru_cell</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">hx</span><span class="p">,</span> <span class="n">w_ih</span><span class="p">,</span> <span class="n">w_hh</span><span class="p">,</span> <span class="n">b_ih</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">b_hh</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">gt</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">greater</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">hardshrink</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">lambd</span><span class="o">=</span><span class="mf">0.5</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">heaviside</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">values</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">hinge_embedding_loss</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">margin</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span> <span class="n">size_average</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduce</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduction</span><span class="o">=</span><span class="s2">&quot;mean&quot;</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>  <span class="c1"># noqa: B950</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">histc</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">bins</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="nb">min</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="nb">max</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">histogram</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">bins</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="nb">min</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="nb">max</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">density</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">histogramdd</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">bins</span><span class="p">,</span> <span class="nb">range</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">density</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">householder_product</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">tau</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">hspmm</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">mat1</span><span class="p">,</span> <span class="n">mat2</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">hsplit</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">indices_or_sections</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">hstack</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">tensors</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">hypot</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">igamma</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">igammac</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">imag</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">index_add</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="p">,</span> <span class="n">index</span><span class="p">,</span> <span class="n">source</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">index_copy</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="p">,</span> <span class="n">index</span><span class="p">,</span> <span class="n">source</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">index_put</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">indices</span><span class="p">,</span> <span class="n">values</span><span class="p">,</span> <span class="n">accumulate</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">index_select</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="p">,</span> <span class="n">index</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">index_fill</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="p">,</span> <span class="n">index</span><span class="p">,</span> <span class="n">value</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">index_reduce</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="p">,</span> <span class="n">index</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">reduce</span><span class="p">,</span> <span class="n">include_input</span><span class="o">=</span><span class="kc">True</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">isfinite</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">tensor</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">isin</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">e</span><span class="p">,</span> <span class="n">te</span><span class="p">,</span> <span class="n">assume_unique</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">invert</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">isinf</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">tensor</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">isreal</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">tensor</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">isposinf</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">isneginf</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">instance_norm</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">running_mean</span><span class="p">,</span> <span class="n">running_var</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">bias</span><span class="p">,</span> <span class="n">use_input_stats</span><span class="p">,</span> <span class="n">momentum</span><span class="p">,</span> <span class="n">eps</span><span class="p">,</span> <span class="n">cudnn_enabled</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">int_repr</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">inverse</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">inv</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">inv_ex</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">check_errors</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">is_complex</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">is_conj</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">is_neg</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">is_distributed</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">is_inference</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">is_floating_point</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">is_nonzero</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">is_same_size</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">is_signed</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">isclose</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">rtol</span><span class="o">=</span><span class="mf">1e-05</span><span class="p">,</span> <span class="n">atol</span><span class="o">=</span><span class="mf">1e-08</span><span class="p">,</span> <span class="n">equal_nan</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">isnan</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">istft</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">n_fft</span><span class="p">,</span> <span class="n">hop_length</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">win_length</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">window</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">center</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">normalized</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">onesided</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">length</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">return_complex</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>  <span class="c1"># noqa: B950</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">kl_div</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">size_average</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduce</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduction</span><span class="o">=</span><span class="s2">&quot;mean&quot;</span><span class="p">,</span> <span class="n">log_target</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">kron</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">kthvalue</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">k</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">keepdim</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">ldl_factor_ex</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">hermitian</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">check_errors</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">ldl_factor</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">hermitian</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">ldl_solve</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">LD</span><span class="p">,</span> <span class="n">pivots</span><span class="p">,</span> <span class="n">B</span><span class="p">,</span> <span class="n">hermitian</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">layer_norm</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">normalized_shape</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">bias</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">esp</span><span class="o">=</span><span class="mf">1e-05</span><span class="p">,</span> <span class="n">cudnn_enabled</span><span class="o">=</span><span class="kc">True</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">lcm</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">ldexp</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">le</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">less_equal</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">lerp</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">end</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">lgamma</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">lobpcg</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">k</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">B</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">X</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">n</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">iK</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">niter</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">tol</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">largest</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">method</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">tracker</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">ortho_iparams</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">ortho_fparams</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">ortho_bparams</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>  <span class="c1"># noqa: B950</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">log</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">log_softmax</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">log10</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">log1p</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">log2</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">logaddexp</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">logaddexp2</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">logdet</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">xlogy</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">logical_and</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">logical_not</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">logical_or</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">logical_xor</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">logit</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">logsumexp</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">names</span><span class="p">,</span> <span class="n">keepdim</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">lstm</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">data</span><span class="p">,</span> <span class="n">batch_sizes</span><span class="p">,</span> <span class="n">hx</span><span class="p">,</span> <span class="n">params</span><span class="p">,</span> <span class="n">has_biases</span><span class="p">,</span> <span class="n">num_layers</span><span class="p">,</span> <span class="n">dropout</span><span class="p">,</span> <span class="n">train</span><span class="p">,</span> <span class="n">bidirectional</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">lstm_cell</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">hx</span><span class="p">,</span> <span class="n">w_ih</span><span class="p">,</span> <span class="n">w_hh</span><span class="p">,</span> <span class="n">b_ih</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">b_hh</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">lt</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">less</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">lu</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">A</span><span class="p">,</span> <span class="n">pivot</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">get_infos</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">lu_solve</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">b</span><span class="p">,</span> <span class="n">LU_data</span><span class="p">,</span> <span class="n">LU_pivots</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">margin_ranking_loss</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">input1</span><span class="p">,</span> <span class="n">input2</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">margin</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">size_average</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduce</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduction</span><span class="o">=</span><span class="s2">&quot;mean&quot;</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>  <span class="c1"># type: ignore[attr-defined]  # noqa: B950</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">masked_fill</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">mask</span><span class="p">,</span> <span class="n">value</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">masked_scatter</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">mask</span><span class="p">,</span> <span class="n">source</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">masked_select</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">mask</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">matmul</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">lu</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">pivot</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">lu_factor</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">pivot</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">lu_factor_ex</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">pivot</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">check_errors</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">lu_solve</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">LU</span><span class="p">,</span> <span class="n">pivots</span><span class="p">,</span> <span class="n">B</span><span class="p">,</span> <span class="n">left</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">adjoint</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">matmul</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>  <span class="c1"># alias for torch.matmul</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">matrix_power</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">n</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">matrix_power</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">n</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">matrix_rank</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">tol</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">hermitian</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">multi_dot</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">tensors</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">matrix_exp</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">matrix_exp</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">max</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">maximum</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fmax</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">max_pool1d</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">padding</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">dilation</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">ceil_mode</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">max_pool2d</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">padding</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">dilation</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">ceil_mode</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">max_pool3d</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">padding</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">dilation</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">ceil_mode</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">max_pool1d_with_indices</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">padding</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">dilation</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">return_indices</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">ceil_mode</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">mean</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nanmean</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">keepdim</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">median</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nanmedian</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">meshgrid</span><span class="p">:</span> <span class="k">lambda</span> <span class="o">*</span><span class="n">tensors</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">min</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">minimum</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">fmin</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">miopen_batch_norm</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">bias</span><span class="p">,</span> <span class="n">running_mean</span><span class="p">,</span> <span class="n">running_var</span><span class="p">,</span> <span class="n">training</span><span class="p">,</span> <span class="n">exponential_average_factor</span><span class="p">,</span> <span class="n">epsilon</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">miopen_convolution</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">bias</span><span class="p">,</span> <span class="n">padding</span><span class="p">,</span> <span class="n">stride</span><span class="p">,</span> <span class="n">dilation</span><span class="p">,</span> <span class="n">groups</span><span class="p">,</span> <span class="n">benchmark</span><span class="p">,</span> <span class="n">deterministic</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>  <span class="c1"># noqa: B950</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">miopen_convolution_add_relu</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">z</span><span class="p">,</span> <span class="n">alpha</span><span class="p">,</span> <span class="n">bias</span><span class="p">,</span> <span class="n">stride</span><span class="p">,</span> <span class="n">padding</span><span class="p">,</span> <span class="n">dilation</span><span class="p">,</span> <span class="n">groups</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">miopen_convolution_relu</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">bias</span><span class="p">,</span> <span class="n">stride</span><span class="p">,</span> <span class="n">padding</span><span class="p">,</span> <span class="n">dilation</span><span class="p">,</span> <span class="n">groups</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">miopen_convolution_transpose</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">bias</span><span class="p">,</span> <span class="n">padding</span><span class="p">,</span> <span class="n">output_padding</span><span class="p">,</span> <span class="n">stride</span><span class="p">,</span> <span class="n">dilation</span><span class="p">,</span> <span class="n">groups</span><span class="p">,</span> <span class="n">benchmark</span><span class="p">,</span> <span class="n">deterministic</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">miopen_depthwise_convolution</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">bias</span><span class="p">,</span> <span class="n">padding</span><span class="p">,</span> <span class="n">stride</span><span class="p">,</span> <span class="n">dilation</span><span class="p">,</span> <span class="n">groups</span><span class="p">,</span> <span class="n">benchmark</span><span class="p">,</span> <span class="n">deterministic</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">miopen_rnn</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">weight_stride0</span><span class="p">,</span> <span class="n">hx</span><span class="p">,</span> <span class="n">cx</span><span class="p">,</span> <span class="n">mode</span><span class="p">,</span> <span class="n">hidden_size</span><span class="p">,</span> <span class="n">num_layers</span><span class="p">,</span> <span class="n">batch_first</span><span class="p">,</span> <span class="n">dropout</span><span class="p">,</span> <span class="n">train</span><span class="p">,</span> <span class="n">bidirectional</span><span class="p">,</span> <span class="n">batch_sizes</span><span class="p">,</span> <span class="n">dropout_state</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>  <span class="c1"># noqa: B950</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">mm</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">mat2</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">mode</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="o">=-</span><span class="mi">1</span><span class="p">,</span> <span class="n">keepdim</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">movedim</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">destination</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">moveaxis</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">destination</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">msort</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">descending</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">mul</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">multiply</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">multinomial</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">num_samples</span><span class="p">,</span> <span class="n">replacement</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">mv</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">vec</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">mvlgamma</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">p</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">narrow</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="p">,</span> <span class="n">start</span><span class="p">,</span> <span class="n">length</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nan_to_num</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">nan</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">posinf</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">neginf</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">native_batch_norm</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">bias</span><span class="p">,</span> <span class="n">running_mean</span><span class="p">,</span> <span class="n">running_var</span><span class="p">,</span> <span class="n">training</span><span class="p">,</span> <span class="n">momentum</span><span class="p">,</span> <span class="n">eps</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">_native_batch_norm_legit</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">bias</span><span class="p">,</span> <span class="n">training</span><span class="p">,</span> <span class="n">momentum</span><span class="p">,</span> <span class="n">eps</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">native_dropout</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">p</span><span class="p">,</span> <span class="n">train</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">native_layer_norm</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">normalized_shape</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">bias</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="mf">1e-05</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">native_group_norm</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">bias</span><span class="p">,</span> <span class="n">N</span><span class="p">,</span> <span class="n">C</span><span class="p">,</span> <span class="n">HxW</span><span class="p">,</span> <span class="n">group</span><span class="p">,</span> <span class="n">eps</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">native_norm</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">p</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">keepdim</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">native_channel_shuffle</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">groups</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">ne</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">not_equal</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">neg</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">negative</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nextafter</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">adaptive_avg_pool2d</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">output_size</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">adaptive_avg_pool3d</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">output_size</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">adaptive_max_pool1d</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">output_size</span><span class="p">,</span> <span class="n">return_indices</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">adaptive_max_pool1d_with_indices</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">output_size</span><span class="p">,</span> <span class="n">return_indices</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">adaptive_max_pool2d</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">output_size</span><span class="p">,</span> <span class="n">return_indices</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">adaptive_max_pool2d_with_indices</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">output_size</span><span class="p">,</span> <span class="n">return_indices</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">adaptive_max_pool3d</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">output_size</span><span class="p">,</span> <span class="n">return_indices</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">adaptive_max_pool3d_with_indices</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">output_size</span><span class="p">,</span> <span class="n">return_indices</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">affine_grid</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">theta</span><span class="p">,</span> <span class="n">size</span><span class="p">,</span> <span class="n">align_corners</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">alpha_dropout</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">p</span><span class="o">=</span><span class="mf">0.5</span><span class="p">,</span> <span class="n">training</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">avg_pool2d</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">padding</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">ceil_mode</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">count_include_pad</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">divisor_override</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>  <span class="c1"># noqa: B950</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">avg_pool3d</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">padding</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">ceil_mode</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">count_include_pad</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">divisor_override</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>  <span class="c1"># noqa: B950</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">batch_norm</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">running_mean</span><span class="p">,</span> <span class="n">running_var</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">bias</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">training</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">momentum</span><span class="o">=</span><span class="mf">0.1</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="mf">1e-05</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">bilinear</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">input1</span><span class="p">,</span> <span class="n">input2</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">bias</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">binary_cross_entropy</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">size_average</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduce</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduction</span><span class="o">=</span><span class="s2">&quot;mean&quot;</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">binary_cross_entropy_with_logits</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">size_average</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduce</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduction</span><span class="o">=</span><span class="s2">&quot;mean&quot;</span><span class="p">,</span> <span class="n">pos_weight</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">celu</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">cosine_embedding_loss</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="n">input1</span><span class="p">,</span> <span class="n">input2</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">margin</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">size_average</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduce</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduction</span><span class="o">=</span><span class="s2">&quot;mean&quot;</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">cross_entropy</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">size_average</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">ignore_index</span><span class="o">=-</span><span class="mi">100</span><span class="p">,</span> <span class="n">reduce</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduction</span><span class="o">=</span><span class="s2">&quot;mean&quot;</span><span class="p">,</span> <span class="n">label_smoothing</span><span class="o">=</span><span class="mf">0.0</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>  <span class="c1"># noqa: B950</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">ctc_loss</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="n">log_probs</span><span class="p">,</span> <span class="n">targets</span><span class="p">,</span> <span class="n">input_lengths</span><span class="p">,</span> <span class="n">target_lengths</span><span class="p">,</span> <span class="n">blank</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">reduction</span><span class="o">=</span><span class="s2">&quot;mean&quot;</span><span class="p">,</span> <span class="n">zero_infinity</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">dropout</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">p</span><span class="o">=</span><span class="mf">0.5</span><span class="p">,</span> <span class="n">training</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">dropout1d</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">p</span><span class="o">=</span><span class="mf">0.5</span><span class="p">,</span> <span class="n">training</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">dropout2d</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">p</span><span class="o">=</span><span class="mf">0.5</span><span class="p">,</span> <span class="n">training</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">dropout3d</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">p</span><span class="o">=</span><span class="mf">0.5</span><span class="p">,</span> <span class="n">training</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">elu</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">embedding</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">padding_idx</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">max_norm</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">norm_type</span><span class="o">=</span><span class="mf">2.0</span><span class="p">,</span> <span class="n">scale_grad_by_freq</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">sparse</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>  <span class="c1"># noqa: B950</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">embedding_bag</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">offsets</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">max_norm</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">norm_type</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">scale_grad_by_freq</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">&quot;mean&quot;</span><span class="p">,</span> <span class="n">sparse</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">per_sample_weights</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">include_last_offset</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">padding_idx</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>  <span class="c1"># noqa: B950</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">feature_alpha_dropout</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">p</span><span class="o">=</span><span class="mf">0.5</span><span class="p">,</span> <span class="n">training</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">fold</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">output_size</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">dilation</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">padding</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="mi">1</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">fractional_max_pool2d</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">output_size</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">output_ratio</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">return_indices</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">_random_samples</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>  <span class="c1"># noqa: B950</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">fractional_max_pool2d_with_indices</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">output_size</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">output_ratio</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">return_indices</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">_random_samples</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>  <span class="c1"># noqa: B950</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">fractional_max_pool3d</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">output_size</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">output_ratio</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">return_indices</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">_random_samples</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>  <span class="c1"># noqa: B950</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">fractional_max_pool3d_with_indices</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">output_size</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">output_ratio</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">return_indices</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">_random_samples</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>  <span class="c1"># noqa: B950</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">gaussian_nll_loss</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">var</span><span class="p">,</span> <span class="n">full</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="mf">1e-06</span><span class="p">,</span> <span class="n">reduction</span><span class="o">=</span><span class="s2">&quot;mean&quot;</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">gelu</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">approximate</span><span class="o">=</span><span class="s2">&quot;none&quot;</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">glu</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="o">=-</span><span class="mi">1</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">grid_sample</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">grid</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">&quot;bilinear&quot;</span><span class="p">,</span> <span class="n">padding_mode</span><span class="o">=</span><span class="s2">&quot;zeros&quot;</span><span class="p">,</span> <span class="n">align_corners</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>  <span class="c1"># noqa: B950</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">group_norm</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">num_groups</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">bias</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="mf">1e-05</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">gumbel_softmax</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">logits</span><span class="p">,</span> <span class="n">tau</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">hard</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="mf">1e-10</span><span class="p">,</span> <span class="n">dim</span><span class="o">=-</span><span class="mi">1</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">hardshrink</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">lambd</span><span class="o">=</span><span class="mf">0.5</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">hardtanh</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">min_val</span><span class="o">=-</span><span class="mf">1.0</span><span class="p">,</span> <span class="n">max_val</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">hinge_embedding_loss</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">margin</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span> <span class="n">size_average</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduce</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduction</span><span class="o">=</span><span class="s2">&quot;mean&quot;</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">instance_norm</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">running_mean</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">running_var</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">bias</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">use_input_stats</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">momentum</span><span class="o">=</span><span class="mf">0.1</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="mf">1e-05</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>  <span class="c1"># noqa: B950</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">interpolate</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">scale_factor</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">&quot;nearest&quot;</span><span class="p">,</span> <span class="n">align_corners</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">recompute_scale_factor</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">antialias</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>  <span class="c1"># noqa: B950</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">kl_div</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">size_average</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduce</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduction</span><span class="o">=</span><span class="s2">&quot;mean&quot;</span><span class="p">,</span> <span class="n">log_target</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>  <span class="c1"># noqa: B950</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">l1_loss</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">size_average</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduce</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduction</span><span class="o">=</span><span class="s2">&quot;mean&quot;</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">layer_norm</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">normalized_shape</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">bias</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="mf">1e-05</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">leaky_relu</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">negative_slope</span><span class="o">=</span><span class="mf">0.01</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">linear</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">bias</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">local_response_norm</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">size</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.0001</span><span class="p">,</span> <span class="n">beta</span><span class="o">=</span><span class="mf">0.75</span><span class="p">,</span> <span class="n">k</span><span class="o">=</span><span class="mf">1.0</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">log_softmax</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">_stacklevel</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">logsigmoid</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">lp_pool1d</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">norm_type</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">ceil_mode</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">lp_pool2d</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">norm_type</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">ceil_mode</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">lp_pool3d</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">norm_type</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">ceil_mode</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">margin_ranking_loss</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="n">input1</span><span class="p">,</span> <span class="n">input2</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">margin</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">size_average</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduce</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduction</span><span class="o">=</span><span class="s2">&quot;mean&quot;</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">max_pool1d</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">padding</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">dilation</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">ceil_mode</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">return_indices</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">max_pool1d_with_indices</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">padding</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">dilation</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">return_indices</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">ceil_mode</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">max_pool2d</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">padding</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">dilation</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">ceil_mode</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">return_indices</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">max_pool2d_with_indices</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">padding</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">dilation</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">return_indices</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">ceil_mode</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">max_pool3d</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">padding</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">dilation</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">return_indices</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">ceil_mode</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">max_pool3d_with_indices</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">padding</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">dilation</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">return_indices</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">ceil_mode</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">max_unpool1d</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">indices</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">padding</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">output_size</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>  <span class="c1"># noqa: B950</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">max_unpool2d</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">indices</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">padding</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">output_size</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>  <span class="c1"># noqa: B950</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">max_unpool3d</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">indices</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">padding</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">output_size</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>  <span class="c1"># noqa: B950</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">mse_loss</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">size_average</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduce</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduction</span><span class="o">=</span><span class="s2">&quot;mean&quot;</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">multi_head_attention_forward</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="n">query</span><span class="p">,</span> <span class="n">key</span><span class="p">,</span> <span class="n">value</span><span class="p">,</span> <span class="n">embed_dim_to_check</span><span class="p">,</span> <span class="n">num_heads</span><span class="p">,</span> <span class="n">in_proj_weight</span><span class="p">,</span> <span class="n">in_proj_bias</span><span class="p">,</span> <span class="n">bias_k</span><span class="p">,</span> <span class="n">bias_v</span><span class="p">,</span> <span class="n">add_zero_attn</span><span class="p">,</span> <span class="n">dropout_p</span><span class="p">,</span> <span class="n">out_proj_weight</span><span class="p">,</span> <span class="n">out_proj_bias</span><span class="p">,</span> <span class="n">training</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">key_padding_mask</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">need_weights</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">attn_mask</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">use_separate_proj_weight</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">q_proj_weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">k_proj_weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">v_proj_weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">static_k</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">static_v</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">average_attn_weights</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">is_causal</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>  <span class="c1"># noqa: B950</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">multi_margin_loss</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">p</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">margin</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">size_average</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduce</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduction</span><span class="o">=</span><span class="s2">&quot;mean&quot;</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">multilabel_margin_loss</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">size_average</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduce</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduction</span><span class="o">=</span><span class="s2">&quot;mean&quot;</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">multilabel_soft_margin_loss</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">size_average</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduce</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduction</span><span class="o">=</span><span class="s2">&quot;mean&quot;</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">nll_loss</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">size_average</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">ignore_index</span><span class="o">=-</span><span class="mi">100</span><span class="p">,</span> <span class="n">reduce</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduction</span><span class="o">=</span><span class="s2">&quot;mean&quot;</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">normalize</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">p</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="mf">1e-12</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">one_hot</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">tensor</span><span class="p">,</span> <span class="n">num_classes</span><span class="o">=-</span><span class="mi">1</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">pad</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">pad</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">&quot;constant&quot;</span><span class="p">,</span> <span class="n">value</span><span class="o">=</span><span class="mi">0</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">pairwise_distance</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">x1</span><span class="p">,</span> <span class="n">x2</span><span class="p">,</span> <span class="n">p</span><span class="o">=</span><span class="mf">2.0</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="mf">1e-06</span><span class="p">,</span> <span class="n">keepdim</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">poisson_nll_loss</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">log_input</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">full</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">size_average</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="mf">1e-08</span><span class="p">,</span> <span class="n">reduce</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduction</span><span class="o">=</span><span class="s2">&quot;mean&quot;</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>  <span class="c1"># noqa: B950</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">prelu</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">weight</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">relu</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">relu6</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">rms_norm</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">normalized_shape</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="mf">1e-6</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">rrelu</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">lower</span><span class="o">=</span><span class="mf">0.125</span><span class="p">,</span> <span class="n">upper</span><span class="o">=</span><span class="mf">0.3333333333333333</span><span class="p">,</span> <span class="n">training</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>  <span class="c1"># noqa: B950</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">selu</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">silu</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">mish</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">scaled_dot_product_attention</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">query</span><span class="p">,</span> <span class="n">key</span><span class="p">,</span> <span class="n">value</span><span class="p">,</span> <span class="n">attn_mask</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dropout_p</span><span class="o">=</span><span class="mf">0.0</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">smooth_l1_loss</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">size_average</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduce</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduction</span><span class="o">=</span><span class="s2">&quot;mean&quot;</span><span class="p">,</span> <span class="n">beta</span><span class="o">=</span><span class="mf">1.0</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>  <span class="c1"># noqa: B950</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">huber_loss</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">reduction</span><span class="o">=</span><span class="s2">&quot;mean&quot;</span><span class="p">,</span> <span class="n">delta</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">soft_margin_loss</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">size_average</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduce</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduction</span><span class="o">=</span><span class="s2">&quot;mean&quot;</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>  <span class="c1"># noqa: B950</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">softmax</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">_stacklevel</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">softmin</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">_stacklevel</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">softplus</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">beta</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">threshold</span><span class="o">=</span><span class="mi">20</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">softshrink</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">lambd</span><span class="o">=</span><span class="mf">0.5</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">softsign</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">tanhshrink</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">threshold</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">threshold</span><span class="p">,</span> <span class="n">value</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">triplet_margin_loss</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="n">anchor</span><span class="p">,</span> <span class="n">positive</span><span class="p">,</span> <span class="n">negative</span><span class="p">,</span> <span class="n">margin</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span> <span class="n">p</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="mf">1e-06</span><span class="p">,</span> <span class="n">swap</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">size_average</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduce</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduction</span><span class="o">=</span><span class="s2">&quot;mean&quot;</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>  <span class="c1"># noqa: B950</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">triplet_margin_with_distance_loss</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="n">anchor</span><span class="p">,</span> <span class="n">positive</span><span class="p">,</span> <span class="n">negative</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">distance_function</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">margin</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span> <span class="n">swap</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">reduction</span><span class="o">=</span><span class="s2">&quot;mean&quot;</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">unfold</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">dilation</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">padding</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="mi">1</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">init</span><span class="o">.</span><span class="n">uniform_</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">tensor</span><span class="p">,</span> <span class="n">a</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">b</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span> <span class="n">generator</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">init</span><span class="o">.</span><span class="n">normal_</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">tensor</span><span class="p">,</span> <span class="n">mean</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">std</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span> <span class="n">generator</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">init</span><span class="o">.</span><span class="n">constant_</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">tensor</span><span class="p">,</span> <span class="n">val</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">init</span><span class="o">.</span><span class="n">kaiming_uniform_</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">tensor</span><span class="p">,</span> <span class="n">a</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">&quot;fan_in&quot;</span><span class="p">,</span> <span class="n">nonlinearity</span><span class="o">=</span><span class="s2">&quot;leaky_relu&quot;</span><span class="p">,</span> <span class="n">generator</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>  <span class="c1"># noqa: B950</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nonzero</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">as_tuple</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nonzero_static</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">size</span><span class="p">,</span> <span class="n">fill_value</span><span class="o">=-</span><span class="mi">1</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">argwhere</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">norm</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">p</span><span class="o">=</span><span class="s2">&quot;fro&quot;</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">keepdim</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">norm</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="nb">ord</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">keepdim</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">vector_norm</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="nb">ord</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">keepdim</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">matrix_norm</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="nb">ord</span><span class="o">=</span><span class="s2">&quot;fro&quot;</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="p">(</span>
            <span class="o">-</span><span class="mi">2</span><span class="p">,</span>
            <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="p">),</span> <span class="n">keepdim</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">norm_except_dim</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">v</span><span class="p">,</span> <span class="nb">pow</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nuclear_norm</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">p</span><span class="o">=</span><span class="s2">&quot;fro&quot;</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">keepdim</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">numel</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">orgqr</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">tau</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">ormqr</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">input2</span><span class="p">,</span> <span class="n">input3</span><span class="p">,</span> <span class="n">left</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">transpose</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">pairwise_distance</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">x1</span><span class="p">,</span> <span class="n">x2</span><span class="p">,</span> <span class="n">p</span><span class="o">=</span><span class="mf">2.0</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="mf">1e-06</span><span class="p">,</span> <span class="n">keepdim</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">permute</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">dim</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">pca_lowrank</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">q</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">center</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">niter</span><span class="o">=</span><span class="mi">2</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">pdist</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">p</span><span class="o">=</span><span class="mi">2</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">pinverse</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">rcond</span><span class="o">=</span><span class="mf">1e-15</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">pinv</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">rcond</span><span class="o">=</span><span class="mf">1e-15</span><span class="p">,</span> <span class="n">hermitian</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">pixel_shuffle</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">upscale_factor</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">pixel_unshuffle</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">downscale_factor</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">poisson</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">generator</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">poisson_nll_loss</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">log_input</span><span class="p">,</span> <span class="n">full</span><span class="p">,</span> <span class="n">eps</span><span class="p">,</span> <span class="n">reduction</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">polygamma</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">n</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">positive</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">prelu</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">weight</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">ones_like</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">layout</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">device</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">requires_grad</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">pow</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">exponent</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">prod</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">put</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">index</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">accumulate</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">q_per_channel_axis</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">q_per_channel_scales</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">q_per_channel_zero_points</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">q_scale</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">q_zero_point</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">qr</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">some</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">qr</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">&quot;reduced&quot;</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">quantile</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">q</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">keepdim</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">interpolation</span><span class="o">=</span><span class="s2">&quot;linear&quot;</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nanquantile</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">q</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">keepdim</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">interpolation</span><span class="o">=</span><span class="s2">&quot;linear&quot;</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">quantize_per_channel</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">scales</span><span class="p">,</span> <span class="n">zero_points</span><span class="p">,</span> <span class="n">axis</span><span class="p">,</span> <span class="n">dtype</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">quantize_per_tensor</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">scale</span><span class="p">,</span> <span class="n">zero_point</span><span class="p">,</span> <span class="n">dtype</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">quantize_per_tensor_dynamic</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dtype</span><span class="p">,</span> <span class="n">reduce_range</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">quantized_batch_norm</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">bias</span><span class="p">,</span> <span class="n">mean</span><span class="p">,</span> <span class="n">var</span><span class="p">,</span> <span class="n">eps</span><span class="p">,</span> <span class="n">output_scale</span><span class="p">,</span> <span class="n">output_zero_point</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">quantized_gru_cell</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">hx</span><span class="p">,</span> <span class="n">w_ih</span><span class="p">,</span> <span class="n">w_hh</span><span class="p">,</span> <span class="n">b_ih</span><span class="p">,</span> <span class="n">b_hh</span><span class="p">,</span> <span class="n">packed_ih</span><span class="p">,</span> <span class="n">packed_hh</span><span class="p">,</span> <span class="n">col_offsets_ih</span><span class="p">,</span> <span class="n">col_offsets_hh</span><span class="p">,</span> <span class="n">scale_ih</span><span class="p">,</span> <span class="n">scale_hh</span><span class="p">,</span> <span class="n">zero_point_ih</span><span class="p">,</span> <span class="n">zero_point_hh</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>  <span class="c1"># noqa: B950</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">quantized_lstm_cell</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">hx</span><span class="p">,</span> <span class="n">w_ih</span><span class="p">,</span> <span class="n">w_hh</span><span class="p">,</span> <span class="n">b_ih</span><span class="p">,</span> <span class="n">b_hh</span><span class="p">,</span> <span class="n">packed_ih</span><span class="p">,</span> <span class="n">packed_hh</span><span class="p">,</span> <span class="n">col_offsets_ih</span><span class="p">,</span> <span class="n">col_offsets_hh</span><span class="p">,</span> <span class="n">scale_ih</span><span class="p">,</span> <span class="n">scale_hh</span><span class="p">,</span> <span class="n">zero_point_ih</span><span class="p">,</span> <span class="n">zero_point_hh</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>  <span class="c1"># noqa: B950</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">quantized_max_pool1d</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="p">(),</span> <span class="n">padding</span><span class="o">=</span><span class="p">(</span><span class="mi">0</span><span class="p">,),</span> <span class="n">dilation</span><span class="o">=</span><span class="p">(</span>
                <span class="mi">1</span><span class="p">,</span>
            <span class="p">),</span> <span class="n">ceil_mode</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">quantized_max_pool2d</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="p">(),</span> <span class="n">padding</span><span class="o">=</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">dilation</span><span class="o">=</span><span class="p">(</span>
                <span class="mi">1</span><span class="p">,</span>
                <span class="mi">1</span><span class="p">,</span>
            <span class="p">),</span> <span class="n">ceil_mode</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">quantized_max_pool3d</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="p">(),</span> <span class="n">padding</span><span class="o">=</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">dilation</span><span class="o">=</span><span class="p">(</span>
                <span class="mi">1</span><span class="p">,</span>
                <span class="mi">1</span><span class="p">,</span>
                <span class="mi">1</span><span class="p">,</span>
            <span class="p">),</span> <span class="n">ceil_mode</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">quantized_rnn_relu_cell</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">hx</span><span class="p">,</span> <span class="n">w_ih</span><span class="p">,</span> <span class="n">w_hh</span><span class="p">,</span> <span class="n">b_ih</span><span class="p">,</span> <span class="n">b_hh</span><span class="p">,</span> <span class="n">packed_ih</span><span class="p">,</span> <span class="n">packed_hh</span><span class="p">,</span> <span class="n">col_offsets_ih</span><span class="p">,</span> <span class="n">col_offsets_hh</span><span class="p">,</span> <span class="n">scale_ih</span><span class="p">,</span> <span class="n">scale_hh</span><span class="p">,</span> <span class="n">zero_point_ih</span><span class="p">,</span> <span class="n">zero_point_hh</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>  <span class="c1"># noqa: B950</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">quantized_rnn_tanh_cell</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">hx</span><span class="p">,</span> <span class="n">w_ih</span><span class="p">,</span> <span class="n">w_hh</span><span class="p">,</span> <span class="n">b_ih</span><span class="p">,</span> <span class="n">b_hh</span><span class="p">,</span> <span class="n">packed_ih</span><span class="p">,</span> <span class="n">packed_hh</span><span class="p">,</span> <span class="n">col_offsets_ih</span><span class="p">,</span> <span class="n">col_offsets_hh</span><span class="p">,</span> <span class="n">scale_ih</span><span class="p">,</span> <span class="n">scale_hh</span><span class="p">,</span> <span class="n">zero_point_ih</span><span class="p">,</span> <span class="n">zero_point_hh</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>  <span class="c1"># noqa: B950</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">rad2deg</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">rand_like</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">layout</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">device</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">requires_grad</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">randint_like</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">high</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">layout</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">strided</span><span class="p">,</span> <span class="n">device</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">requires_grad</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">randn_like</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">layout</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">device</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">requires_grad</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">ravel</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">real</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">vdot</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">vecdot</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">dim</span><span class="o">=-</span><span class="mi">1</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">view_as_real</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">view_as_complex</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">reciprocal</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">relu</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">remainder</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">renorm</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">p</span><span class="p">,</span> <span class="n">dim</span><span class="p">,</span> <span class="n">maxnorm</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">repeat_interleave</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">reshape</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">shape</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">rms_norm</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">normalized_shape</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="mf">1e-6</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">rnn_relu</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">hx</span><span class="p">,</span> <span class="n">params</span><span class="p">,</span> <span class="n">has_biases</span><span class="p">,</span> <span class="n">num_layers</span><span class="p">,</span> <span class="n">dropout</span><span class="p">,</span> <span class="n">train</span><span class="p">,</span> <span class="n">bidirectional</span><span class="p">,</span> <span class="n">batch_first</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>  <span class="c1"># noqa: B950</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">rnn_relu_cell</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">hx</span><span class="p">,</span> <span class="n">w_ih</span><span class="p">,</span> <span class="n">w_hh</span><span class="p">,</span> <span class="n">b_ih</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">b_hh</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">rnn_tanh</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">hx</span><span class="p">,</span> <span class="n">params</span><span class="p">,</span> <span class="n">has_biases</span><span class="p">,</span> <span class="n">num_layers</span><span class="p">,</span> <span class="n">dropout</span><span class="p">,</span> <span class="n">train</span><span class="p">,</span> <span class="n">bidirectional</span><span class="p">,</span> <span class="n">batch_first</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>  <span class="c1"># noqa: B950</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">rnn_tanh_cell</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">hx</span><span class="p">,</span> <span class="n">w_ih</span><span class="p">,</span> <span class="n">w_hh</span><span class="p">,</span> <span class="n">b_ih</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">b_hh</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">roll</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">shifts</span><span class="p">,</span> <span class="n">dims</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">rot90</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">k</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">dims</span><span class="o">=</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">):</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">round</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">row_stack</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">tensors</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>  <span class="c1"># alias for torch.vstack</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">_rowwise_prune</span><span class="p">:</span> <span class="p">(</span><span class="k">lambda</span> <span class="n">weight</span><span class="p">,</span> <span class="n">mask</span><span class="p">,</span> <span class="n">compressed_indices_dtype</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">rrelu</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">lower</span><span class="o">=</span><span class="mf">1.0</span> <span class="o">/</span> <span class="mi">8</span><span class="p">,</span> <span class="n">upper</span><span class="o">=</span><span class="mf">1.0</span> <span class="o">/</span> <span class="mi">3</span><span class="p">,</span> <span class="n">training</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">rsqrt</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">rsub</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mi">1</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">saddmm</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">mat1</span><span class="p">,</span> <span class="n">mat2</span><span class="p">,</span> <span class="n">beta</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">scatter</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="p">,</span> <span class="n">index</span><span class="p">,</span> <span class="n">src</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">scatter_add</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="p">,</span> <span class="n">index</span><span class="p">,</span> <span class="n">src</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">scatter_reduce</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="p">,</span> <span class="n">index</span><span class="p">,</span> <span class="n">src</span><span class="p">,</span> <span class="n">reduce</span><span class="p">,</span> <span class="n">include_self</span><span class="o">=</span><span class="kc">True</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">searchsorted</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">sorted_sequence</span><span class="p">,</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out_int32</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">right</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">_segment_reduce</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">data</span><span class="p">,</span> <span class="n">reduce</span><span class="o">=</span><span class="s2">&quot;max&quot;</span><span class="p">,</span> <span class="n">lengths</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">indices</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">offsets</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">unsafe</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>  <span class="c1"># noqa: B950</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">select</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="p">,</span> <span class="n">index</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">select_scatter</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">src</span><span class="p">,</span> <span class="n">dim</span><span class="p">,</span> <span class="n">index</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">slice_inverse</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">src</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">start</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">end</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">step</span><span class="o">=</span><span class="mi">1</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">slice_scatter</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">src</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">start</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">end</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">step</span><span class="o">=</span><span class="mi">1</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">selu</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">sigmoid</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">sign</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">signbit</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">sgn</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">sin</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">sinc</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">sinh</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">slogdet</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">slogdet</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">smm</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">mat2</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">spmm</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">mat2</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">softmax</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">solve</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">A</span><span class="p">,</span> <span class="n">B</span><span class="p">,</span> <span class="n">left</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">solve_ex</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">A</span><span class="p">,</span> <span class="n">B</span><span class="p">,</span> <span class="n">left</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">check_errors</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">sort</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="o">=-</span><span class="mi">1</span><span class="p">,</span> <span class="n">descending</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">stable</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">split</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">tensor</span><span class="p">,</span> <span class="n">split_size_or_sections</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">split_with_sizes</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">tensor</span><span class="p">,</span> <span class="n">split_size_or_sections</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">sqrt</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">square</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">squeeze</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">sspaddmm</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">mat1</span><span class="p">,</span> <span class="n">mat2</span><span class="p">,</span> <span class="n">beta</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">stack</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">tensors</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">std</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">std_mean</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">stft</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">n_fft</span><span class="p">,</span> <span class="n">hop_length</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">win_length</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">window</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">center</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">pad_mode</span><span class="o">=</span><span class="s2">&quot;reflect&quot;</span><span class="p">,</span> <span class="n">normalized</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">onesided</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">return_complex</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>  <span class="c1"># noqa: B950</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">sub</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">subtract</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">sum</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">sym_float</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">sym_int</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">sym_max</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">sym_min</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">sym_not</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">sym_ite</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">,</span> <span class="n">c</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">sym_sum</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">args</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">_sym_sqrt</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">_sym_cos</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">_sym_cosh</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">_sym_sin</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">_sym_sinh</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">_sym_tan</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">_sym_tanh</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">_sym_asin</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">_sym_acos</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">_sym_atan</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nansum</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">svd</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">some</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">compute_uv</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">svd_lowrank</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">q</span><span class="o">=</span><span class="mi">6</span><span class="p">,</span> <span class="n">niter</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">M</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">svd</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">full_matrices</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">svdvals</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">swapaxes</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim0</span><span class="p">,</span> <span class="n">dim1</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">swapdims</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">axis0</span><span class="p">,</span> <span class="n">axis1</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">airy_ai</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">bessel_j0</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">bessel_j1</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">bessel_y0</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">bessel_y1</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">chebyshev_polynomial_t</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">n</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">chebyshev_polynomial_u</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">n</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">chebyshev_polynomial_v</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">n</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">chebyshev_polynomial_w</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">n</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">digamma</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">entr</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">erf</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">erfc</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">erfcx</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">erfinv</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">exp2</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">expit</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">expm1</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">gammainc</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">gammaincc</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">gammaln</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">hermite_polynomial_h</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">n</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">hermite_polynomial_he</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">n</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">i0</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">i0e</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">i1</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">i1e</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">laguerre_polynomial_l</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">n</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">legendre_polynomial_p</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">n</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">log1p</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">log_ndtr</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">log_softmax</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">logit</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">logsumexp</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="p">,</span> <span class="n">keepdim</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">modified_bessel_i0</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">modified_bessel_i1</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">modified_bessel_k0</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">modified_bessel_k1</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">multigammaln</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">p</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">ndtr</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">ndtri</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">polygamma</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">n</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">psi</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">round</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">scaled_modified_bessel_k0</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">scaled_modified_bessel_k1</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">shifted_chebyshev_polynomial_t</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">n</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">shifted_chebyshev_polynomial_u</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">n</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">shifted_chebyshev_polynomial_v</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">n</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">shifted_chebyshev_polynomial_w</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">n</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">sinc</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">softmax</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">spherical_bessel_j0</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">xlog1py</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">xlogy</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">zeta</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">t</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">take</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">index</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">take_along_dim</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">indices</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">tan</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">tanh</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">tensorinv</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">a</span><span class="p">,</span> <span class="n">ind</span><span class="o">=</span><span class="mi">2</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">tensorsolve</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">,</span> <span class="n">dims</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">tensordot</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">,</span> <span class="n">dims</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">tensor_split</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">indices_or_sections</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">threshold</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">threshold</span><span class="p">,</span> <span class="n">value</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">tile</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dims</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">topk</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">k</span><span class="p">,</span> <span class="n">dim</span><span class="o">=-</span><span class="mi">1</span><span class="p">,</span> <span class="n">descending</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">trace</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">transpose</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim0</span><span class="p">,</span> <span class="n">dim1</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">trapz</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">y</span><span class="p">,</span> <span class="n">x</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dim</span><span class="o">=-</span><span class="mi">1</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">trapezoid</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">y</span><span class="p">,</span> <span class="n">x</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dim</span><span class="o">=-</span><span class="mi">1</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">triangular_solve</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">A</span><span class="p">,</span> <span class="n">upper</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">transpose</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">unitriangular</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">solve_triangular</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">B</span><span class="p">,</span> <span class="n">upper</span><span class="p">,</span> <span class="n">left</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">unitriangular</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">tril</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">diagonal</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">triplet_margin_loss</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="n">anchor</span><span class="p">,</span> <span class="n">positive</span><span class="p">,</span> <span class="n">negative</span><span class="p">,</span> <span class="n">margin</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span> <span class="n">p</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="mf">1e-06</span><span class="p">,</span> <span class="n">swap</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">size_average</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduce</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">reduction</span><span class="o">=</span><span class="s2">&quot;mean&quot;</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>  <span class="c1"># noqa: B950</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">triu</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">diagonal</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">true_divide</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">other</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">trunc</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">unbind</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">unflatten</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="p">,</span> <span class="n">sizes</span><span class="p">,</span> <span class="n">names</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">unique</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="nb">sorted</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">return_inverse</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">return_counts</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">unique_consecutive</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">return_inverse</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">return_counts</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">unravel_index</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">indices</span><span class="p">,</span> <span class="n">shape</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">unsafe_chunk</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">chunks</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">unsafe_split</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">tensor</span><span class="p">,</span> <span class="n">split_size_or_sections</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">unsafe_split_with_sizes</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">tensor</span><span class="p">,</span> <span class="n">split_size_or_sections</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">unsqueeze</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">vander</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="n">N</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">var</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">var_mean</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">vsplit</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">indices_or_sections</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">vstack</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">tensors</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">where</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">condition</span><span class="p">,</span> <span class="n">x</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">y</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">_wrapped_linear_prepack</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">weight</span><span class="p">,</span> <span class="n">weight_scale</span><span class="p">,</span> <span class="n">weight_zero_point</span><span class="p">,</span> <span class="n">bias</span> <span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">_wrapped_quantized_linear_prepacked</span><span class="p">:</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">input_scale</span><span class="p">,</span> <span class="n">input_zero_point</span><span class="p">,</span> <span class="n">prepacked</span><span class="p">,</span> <span class="n">out_scale</span><span class="p">,</span> <span class="n">out_zero_point</span><span class="p">,</span> <span class="n">out_channel</span> <span class="p">:</span> <span class="o">-</span><span class="mi">1</span>  <span class="c1"># noqa: B950</span>
        <span class="p">),</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">zeros_like</span><span class="p">:</span> <span class="k">lambda</span> <span class="nb">input</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">layout</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">device</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">requires_grad</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">_fw_primal_copy</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">level</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">_make_dual_copy</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">primal</span><span class="p">,</span> <span class="n">tangent</span><span class="p">,</span> <span class="n">level</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">view_as_real_copy</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">view_as_complex_copy</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">_conj_copy</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">_neg_view_copy</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">as_strided_copy</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">size</span><span class="p">,</span> <span class="n">stride</span><span class="p">,</span> <span class="n">storage_offset</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">_sparse_broadcast_to_copy</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">size</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">diagonal_copy</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">offset</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">dim1</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">dim2</span><span class="o">=</span><span class="mi">1</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">expand_copy</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">size</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">implicit</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">narrow_copy</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">dim</span><span class="p">,</span> <span class="n">start</span><span class="p">,</span> <span class="n">length</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">permute_copy</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">dims</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">_reshape_alias_copy</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">size</span><span class="p">,</span> <span class="n">stride</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">select_copy</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">dim</span><span class="p">,</span> <span class="n">index</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">detach_copy</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">slice_copy</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">start</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">end</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">step</span><span class="o">=</span><span class="mi">1</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">split_copy</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">split_size</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">split_with_sizes_copy</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">split_sizes</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">squeeze_copy</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">dim</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">t_copy</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">transpose_copy</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">dim0</span><span class="p">,</span> <span class="n">dim1</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">unsqueeze_copy</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">dim</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">_indices_copy</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">_values_copy</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">indices_copy</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">values_copy</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">crow_indices_copy</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">col_indices_copy</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">ccol_indices_copy</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">row_indices_copy</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">unbind_copy</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">view_copy</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">dtype</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">unfold_copy</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">dimension</span><span class="p">,</span> <span class="n">size</span><span class="p">,</span> <span class="n">step</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">alias_copy</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__floordiv__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__rfloordiv__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__ifloordiv__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__truediv__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__rtruediv__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__itruediv__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__lshift__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__rlshift__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__ilshift__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__rshift__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__rrshift__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__irshift__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__and__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__or__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__xor__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__float__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__complex__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">__array__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">dtype</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__bool__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__contains__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__neg__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__invert__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__mod__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__rmod__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__imod__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">__array_wrap__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">array</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__getitem__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">idx</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">__deepcopy__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">memo</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__int__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">__long__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__index__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__len__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__format__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">format_spec</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">__reduce_ex__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">proto</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__reversed__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__repr__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">tensor_contents</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="fm">__setitem__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">__setstate__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">d</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">T</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">H</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">mT</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">mH</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_backward_hooks</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_post_accumulate_grad_hooks</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_base</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_cdata</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">grad</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_grad</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_grad_fn</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">grad_fn</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_version</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_autocast_to_reduced_precision</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">cuda_enabled</span><span class="p">,</span> <span class="n">cpu_enabled</span><span class="p">,</span> <span class="n">cuda_dtype</span><span class="p">,</span> <span class="n">cpu_dtype</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_autocast_to_full_precision</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">cuda_enabled</span><span class="p">,</span> <span class="n">cpu_enabled</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_clear_non_serializable_cached_data</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">device</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">dtype</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">is_cuda</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">is_cpu</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">is_xla</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">is_xpu</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">is_ipu</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">is_leaf</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">retains_grad</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">is_meta</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">is_mps</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">is_mtia</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">is_nested</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">is_maia</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">is_mkldnn</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">is_quantized</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">is_sparse</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">is_sparse_csr</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">is_vulkan</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">itemsize</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">layout</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">name</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">names</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">nbytes</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">ndim</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">output_nr</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">requires_grad</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">shape</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">volatile</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">real</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">imag</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">__cuda_array_interface__</span><span class="o">.</span><span class="fm">__get__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">type</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">non_blocking</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_dimI</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_dimV</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_indices</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_is_view</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_nnz</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">crow_indices</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">col_indices</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">ccol_indices</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">row_indices</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_update_names</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">names</span><span class="p">,</span> <span class="n">inplace</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_values</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">adjoint</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">align_as</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">align_to</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">order</span><span class="p">,</span> <span class="n">ellipsis_idx</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">apply_</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="nb">callable</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">as_strided</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">size</span><span class="p">,</span> <span class="n">stride</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">as_strided_</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">size</span><span class="p">,</span> <span class="n">stride</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">backward</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">gradient</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">retain_graph</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">create_graph</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">inputs</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">bfloat16</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">memory_format</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">preserve_format</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">bool</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">memory_format</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">preserve_format</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">byte</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">memory_format</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">preserve_format</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">char</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">memory_format</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">preserve_format</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">cauchy_</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">median</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">sigma</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">generator</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">coalesce</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_coalesced_</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">coalesced</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">contiguous</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">memory_format</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">contiguous_format</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">copy_</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">src</span><span class="p">,</span> <span class="n">non_blocking</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">cpu</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">memory_format</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">preserve_format</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">cuda</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">memory_format</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">preserve_format</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">mtia</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">memory_format</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">preserve_format</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">xpu</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">memory_format</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">preserve_format</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">ipu</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">memory_format</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">preserve_format</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">data_ptr</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">dense_dim</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">diagonal_scatter</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">src</span><span class="p">,</span> <span class="n">offset</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">dim1</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">dim2</span><span class="o">=</span><span class="mi">1</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">dim</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">dim_order</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">ambiguity_check</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">double</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">memory_format</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">preserve_format</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">cdouble</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">memory_format</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">preserve_format</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">element_size</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">expand</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">size</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">expand_as</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">exponential_</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">lambd</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">generator</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">fill_</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">value</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">fill_diagonal_</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">value</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">float</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">memory_format</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">preserve_format</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">cfloat</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">memory_format</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">preserve_format</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">geometric_</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">p</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">generator</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">get_device</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">half</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">memory_format</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">preserve_format</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">chalf</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">memory_format</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">preserve_format</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">has_names</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">indices</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">int</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">memory_format</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">preserve_format</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">is_coalesced</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">is_contiguous</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">is_inference</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">is_pinned</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">is_set_to</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">tensor</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">is_shared</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">item</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">log_normal_</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">mean</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">std</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">generator</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">log_softmax</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">dim</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">long</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">memory_format</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">preserve_format</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">map_</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">tensor</span><span class="p">,</span> <span class="nb">callable</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">map2_</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="nb">callable</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">mm</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">mat2</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">module_load</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">assign</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">narrow_copy</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">dimension</span><span class="p">,</span> <span class="n">start</span><span class="p">,</span> <span class="n">length</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">ndimension</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">nelement</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_nested_tensor_size</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_nested_tensor_storage_offsets</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_nested_tensor_strides</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">normal_</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">numpy</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">permute</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">dim</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">pin_memory</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">put_</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">indices</span><span class="p">,</span> <span class="n">tensor</span><span class="p">,</span> <span class="n">accumulate</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">qscheme</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">random_</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">from_</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">to</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">generator</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">record_stream</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">stream</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">refine_names</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">names</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">register_hook</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">hook</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">register_post_accumulate_grad_hook</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">hook</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">rename</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">name</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">repeat</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">size</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">requires_grad_</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">requires_grad</span><span class="o">=</span><span class="kc">True</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">reshape_as</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">resize</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">size</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">resize_</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">size</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">resize_as</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">resize_as_sparse_</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">retain_grad</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">set_</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">source</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">storage_offset</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">select_scatter</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">src</span><span class="p">,</span> <span class="n">dim</span><span class="p">,</span> <span class="n">index</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">share_memory_</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">short</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">memory_format</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">preserve_format</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">size</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">slice_scatter</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">src</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">start</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">end</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">step</span><span class="o">=</span><span class="mi">1</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">sparse_dim</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">sparse_mask</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">mask</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_sparse_mask_projection</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">mask</span><span class="p">,</span> <span class="n">accumulate_matches</span><span class="o">=</span><span class="kc">False</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">sparse_resize_</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">size1</span><span class="p">,</span> <span class="n">size2</span><span class="p">,</span> <span class="n">dense_dim</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">sparse_resize_and_clear_</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">size1</span><span class="p">,</span> <span class="n">size2</span><span class="p">,</span> <span class="n">dense_dim</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">sspaddmm</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">mat1</span><span class="p">,</span> <span class="n">mat2</span><span class="p">,</span> <span class="n">beta</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">storage</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">untyped_storage</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">storage_offset</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">storage_type</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">sum_to_size</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">size</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">tile</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">reps</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">to</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">dtype</span><span class="p">,</span> <span class="n">non_blocking</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">copy</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">memory_format</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">preserve_format</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">to_dense</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">masked_grad</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">_to_dense</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">masked_grad</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">to_sparse</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">tolist</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">to_mkldnn</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">type_as</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">unfold</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">dimension</span><span class="p">,</span> <span class="n">size</span><span class="p">,</span> <span class="n">step</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">uniform_</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">from_</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">to</span><span class="o">=</span><span class="mi">1</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">values</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">view</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">shape</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">view_as</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">zero_</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">__dlpack__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">stream</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">Tensor</span><span class="o">.</span><span class="n">__dlpack_device__</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">lstsq</span><span class="p">:</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">b</span><span class="p">,</span> <span class="n">cond</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">driver</span><span class="o">=</span><span class="kc">None</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
    <span class="p">}</span>  <span class="c1"># fmt: skip</span>

    <span class="n">privateuse1_backend_name</span> <span class="o">=</span> <span class="p">(</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">utils</span><span class="o">.</span><span class="n">backend_registration</span><span class="o">.</span><span class="n">_privateuse1_backend_name</span>
    <span class="p">)</span>
    <span class="k">if</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">Tensor</span><span class="p">,</span> <span class="n">privateuse1_backend_name</span><span class="p">):</span>
        <span class="n">ret</span><span class="p">[</span><span class="nb">getattr</span><span class="p">(</span><span class="n">Tensor</span><span class="p">,</span> <span class="n">privateuse1_backend_name</span><span class="p">)]</span> <span class="o">=</span> <span class="p">(</span>
            <span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">device</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">non_blocking</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>
        <span class="p">)</span>
        <span class="n">ret</span><span class="p">[</span><span class="nb">getattr</span><span class="p">(</span><span class="n">Tensor</span><span class="p">,</span> <span class="sa">f</span><span class="s2">&quot;is_</span><span class="si">{</span><span class="n">privateuse1_backend_name</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span><span class="o">.</span><span class="fm">__get__</span><span class="p">]</span> <span class="o">=</span> <span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="o">-</span><span class="mi">1</span>

    <span class="n">ret2</span> <span class="o">=</span> <span class="p">{}</span>
    <span class="n">ignored</span> <span class="o">=</span> <span class="n">get_ignored_functions</span><span class="p">()</span>

    <span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">ret</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
        <span class="c1"># Generate methods like __add__ and add_ by default from add</span>
        <span class="n">names</span> <span class="o">=</span> <span class="p">[</span>
            <span class="n">k</span><span class="o">.</span><span class="vm">__name__</span><span class="p">,</span>  <span class="c1"># Default method</span>
            <span class="n">k</span><span class="o">.</span><span class="vm">__name__</span> <span class="o">+</span> <span class="s2">&quot;_&quot;</span><span class="p">,</span>  <span class="c1"># Inplace variant</span>
            <span class="s2">&quot;__&quot;</span> <span class="o">+</span> <span class="n">k</span><span class="o">.</span><span class="vm">__name__</span> <span class="o">+</span> <span class="s2">&quot;__&quot;</span><span class="p">,</span>  <span class="c1"># Dunder method</span>
            <span class="s2">&quot;__i&quot;</span> <span class="o">+</span> <span class="n">k</span><span class="o">.</span><span class="vm">__name__</span> <span class="o">+</span> <span class="s2">&quot;__&quot;</span><span class="p">,</span>  <span class="c1"># Inplace dunder method</span>
            <span class="s2">&quot;__r&quot;</span> <span class="o">+</span> <span class="n">k</span><span class="o">.</span><span class="vm">__name__</span> <span class="o">+</span> <span class="s2">&quot;__&quot;</span><span class="p">,</span>  <span class="c1"># Reverse dunder method</span>
        <span class="p">]</span>

        <span class="k">if</span> <span class="n">k</span><span class="o">.</span><span class="vm">__name__</span><span class="o">.</span><span class="n">startswith</span><span class="p">(</span><span class="s2">&quot;bitwise_&quot;</span><span class="p">):</span>
            <span class="c1"># bitwise_&lt;op&gt; have dunder methods of the form __&lt;op&gt;__</span>
            <span class="c1"># And so on.</span>
            <span class="n">subname</span> <span class="o">=</span> <span class="n">k</span><span class="o">.</span><span class="vm">__name__</span><span class="p">[</span><span class="nb">len</span><span class="p">(</span><span class="s2">&quot;bitwise_&quot;</span><span class="p">)</span> <span class="p">:]</span>
            <span class="n">names</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span>
                <span class="p">[</span><span class="s2">&quot;__&quot;</span> <span class="o">+</span> <span class="n">subname</span> <span class="o">+</span> <span class="s2">&quot;__&quot;</span><span class="p">,</span> <span class="s2">&quot;__i&quot;</span> <span class="o">+</span> <span class="n">subname</span> <span class="o">+</span> <span class="s2">&quot;__&quot;</span><span class="p">,</span> <span class="s2">&quot;__r&quot;</span> <span class="o">+</span> <span class="n">subname</span> <span class="o">+</span> <span class="s2">&quot;__&quot;</span><span class="p">]</span>
            <span class="p">)</span>

        <span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">names</span><span class="p">:</span>
            <span class="n">func</span> <span class="o">=</span> <span class="nb">getattr</span><span class="p">(</span><span class="n">Tensor</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
            <span class="k">if</span> <span class="nb">callable</span><span class="p">(</span><span class="n">func</span><span class="p">)</span> <span class="ow">and</span> <span class="n">func</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">ret</span> <span class="ow">and</span> <span class="n">func</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">ignored</span><span class="p">:</span>
                <span class="n">ret2</span><span class="p">[</span><span class="n">func</span><span class="p">]</span> <span class="o">=</span> <span class="n">v</span>

    <span class="n">ret</span><span class="o">.</span><span class="n">update</span><span class="p">(</span><span class="n">ret2</span><span class="p">)</span>
    <span class="k">return</span> <span class="n">ret</span></div>


<div class="viewcode-block" id="wrap_torch_function"><a class="viewcode-back" href="../../torch.overrides.html#torch.overrides.wrap_torch_function">[docs]</a><span class="k">def</span> <span class="nf">wrap_torch_function</span><span class="p">(</span><span class="n">dispatcher</span><span class="p">:</span> <span class="n">Callable</span><span class="p">):</span>
<span class="w">    </span><span class="sd">&quot;&quot;&quot;Wraps a given function with ``__torch_function__`` -related functionality.</span>

<span class="sd">    Parameters</span>
<span class="sd">    ----------</span>
<span class="sd">    dispatcher: Callable</span>
<span class="sd">        A callable that returns an iterable of Tensor-likes passed into the function.</span>

<span class="sd">    Note</span>
<span class="sd">    ----</span>
<span class="sd">    This decorator may reduce the performance of your code. Generally, it&#39;s enough to express</span>
<span class="sd">    your code as a series of functions that, themselves, support __torch_function__. If you</span>
<span class="sd">    find yourself in the rare situation where this is not the case, e.g. if you&#39;re wrapping a</span>
<span class="sd">    low-level library and you also need it to work for Tensor-likes, then this function is available.</span>

<span class="sd">    Examples</span>
<span class="sd">    --------</span>
<span class="sd">    &gt;&gt;&gt; def dispatcher(a):  # Must have the same signature as func</span>
<span class="sd">    ...     return (a,)</span>
<span class="sd">    &gt;&gt;&gt; @torch.overrides.wrap_torch_function(dispatcher)</span>
<span class="sd">    &gt;&gt;&gt; def func(a):  # This will make func dispatchable by __torch_function__</span>
<span class="sd">    ...     return a + 0</span>
<span class="sd">    &quot;&quot;&quot;</span>

    <span class="k">def</span> <span class="nf">inner</span><span class="p">(</span><span class="n">func</span><span class="p">):</span>
        <span class="nd">@functools</span><span class="o">.</span><span class="n">wraps</span><span class="p">(</span><span class="n">func</span><span class="p">)</span>
        <span class="k">def</span> <span class="nf">wrapped</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
            <span class="n">relevant_args</span> <span class="o">=</span> <span class="n">dispatcher</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
            <span class="k">if</span> <span class="n">has_torch_function</span><span class="p">(</span><span class="n">relevant_args</span><span class="p">):</span>
                <span class="k">return</span> <span class="n">handle_torch_function</span><span class="p">(</span><span class="n">wrapped</span><span class="p">,</span> <span class="n">relevant_args</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>

            <span class="k">return</span> <span class="n">func</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>

        <span class="k">return</span> <span class="n">wrapped</span>

    <span class="k">return</span> <span class="n">inner</span></div>


<span class="k">def</span> <span class="nf">_get_overloaded_args</span><span class="p">(</span>
    <span class="n">relevant_args</span><span class="p">:</span> <span class="n">Iterable</span><span class="p">[</span><span class="n">Any</span><span class="p">],</span>
    <span class="n">get_type_fn</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Callable</span><span class="p">[[</span><span class="n">Any</span><span class="p">],</span> <span class="n">Type</span><span class="p">]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
<span class="p">)</span> <span class="o">-&gt;</span> <span class="n">List</span><span class="p">[</span><span class="n">Any</span><span class="p">]:</span>
<span class="w">    </span><span class="sd">&quot;&quot;&quot;Returns a list of arguments on which to call __torch_function__.</span>

<span class="sd">    Checks arguments in relevant_args for __torch_function__ implementations,</span>
<span class="sd">    storing references to the arguments and their types in overloaded_args and</span>
<span class="sd">    overloaded_types in order of calling precedence. Only distinct types are</span>
<span class="sd">    considered. If a type is a subclass of another type it will have higher</span>
<span class="sd">    precedence, otherwise the precedence order is the same as the order of</span>
<span class="sd">    arguments in relevant_args, that is, from left-to-right in the argument list.</span>

<span class="sd">    The precedence-determining algorithm implemented in this function is</span>
<span class="sd">    described in `NEP-0018`_.</span>

<span class="sd">    See torch::append_overloaded_arg for the equivalent function in the C++</span>
<span class="sd">    implementation.</span>

<span class="sd">    Parameters</span>
<span class="sd">    ----------</span>
<span class="sd">    relevant_args : iterable of array-like</span>
<span class="sd">        Iterable of array-like arguments to check for __torch_function__</span>
<span class="sd">        methods.</span>

<span class="sd">    get_type_fn : callable, optional</span>
<span class="sd">        Function to call on each argument in relevant_args to get its type.</span>

<span class="sd">    Returns</span>
<span class="sd">    -------</span>
<span class="sd">    overloaded_args : list</span>
<span class="sd">        Arguments from relevant_args on which to call __torch_function__</span>
<span class="sd">        methods, in the order in which they should be called.</span>

<span class="sd">    .. _NEP-0018:</span>
<span class="sd">       https://numpy.org/neps/nep-0018-array-function-protocol.html</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="k">if</span> <span class="n">get_type_fn</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
        <span class="n">get_type_fn</span> <span class="o">=</span> <span class="nb">type</span>

    <span class="c1"># If torch function is not enabled, there are no overloaded types</span>
    <span class="k">if</span> <span class="ow">not</span> <span class="n">torch</span><span class="o">.</span><span class="n">_C</span><span class="o">.</span><span class="n">_is_torch_function_enabled</span><span class="p">():</span>
        <span class="k">return</span> <span class="p">[]</span>
    <span class="c1"># Runtime is O(num_arguments * num_unique_types)</span>
    <span class="n">overloaded_types</span><span class="p">:</span> <span class="n">Set</span><span class="p">[</span><span class="n">Type</span><span class="p">]</span> <span class="o">=</span> <span class="nb">set</span><span class="p">()</span>
    <span class="n">overloaded_args</span><span class="p">:</span> <span class="n">List</span><span class="p">[</span><span class="n">Any</span><span class="p">]</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="k">for</span> <span class="n">arg</span> <span class="ow">in</span> <span class="n">relevant_args</span><span class="p">:</span>
        <span class="n">arg_type</span> <span class="o">=</span> <span class="n">get_type_fn</span><span class="p">(</span><span class="n">arg</span><span class="p">)</span>
        <span class="c1"># We only collect arguments if they have a unique type, which ensures</span>
        <span class="c1"># reasonable performance even with a long list of possibly overloaded</span>
        <span class="c1"># arguments.</span>
        <span class="c1">#</span>
        <span class="c1"># NB: Important to exclude _disabled_torch_function_impl, otherwise</span>
        <span class="c1"># https://github.com/pytorch/pytorch/issues/64687</span>
        <span class="k">if</span> <span class="p">(</span>
            <span class="n">arg_type</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">overloaded_types</span>
            <span class="ow">and</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">arg_type</span><span class="p">,</span> <span class="s2">&quot;__torch_function__&quot;</span><span class="p">)</span>
            <span class="ow">and</span> <span class="n">arg_type</span><span class="o">.</span><span class="n">__torch_function__</span> <span class="o">!=</span> <span class="n">torch</span><span class="o">.</span><span class="n">_C</span><span class="o">.</span><span class="n">_disabled_torch_function_impl</span>
        <span class="p">):</span>
            <span class="c1"># Create lists explicitly for the first type (usually the only one</span>
            <span class="c1"># done) to avoid setting up the iterator for overloaded_args.</span>
            <span class="k">if</span> <span class="n">overloaded_types</span><span class="p">:</span>
                <span class="n">overloaded_types</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">arg_type</span><span class="p">)</span>
                <span class="c1"># By default, insert argument at the end, but if it is</span>
                <span class="c1"># subclass of another argument, insert it before that argument.</span>
                <span class="c1"># This ensures &quot;subclasses before superclasses&quot;.</span>
                <span class="n">index</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">overloaded_args</span><span class="p">)</span>
                <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">old_arg</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">overloaded_args</span><span class="p">):</span>
                    <span class="k">if</span> <span class="nb">issubclass</span><span class="p">(</span><span class="n">arg_type</span><span class="p">,</span> <span class="n">get_type_fn</span><span class="p">(</span><span class="n">old_arg</span><span class="p">)):</span>
                        <span class="n">index</span> <span class="o">=</span> <span class="n">i</span>
                        <span class="k">break</span>
                <span class="n">overloaded_args</span><span class="o">.</span><span class="n">insert</span><span class="p">(</span><span class="n">index</span><span class="p">,</span> <span class="n">arg</span><span class="p">)</span>
            <span class="k">else</span><span class="p">:</span>
                <span class="n">overloaded_types</span> <span class="o">=</span> <span class="p">{</span><span class="n">arg_type</span><span class="p">}</span>
                <span class="n">overloaded_args</span> <span class="o">=</span> <span class="p">[</span><span class="n">arg</span><span class="p">]</span>
    <span class="k">return</span> <span class="n">overloaded_args</span>


<div class="viewcode-block" id="handle_torch_function"><a class="viewcode-back" href="../../torch.overrides.html#torch.overrides.handle_torch_function">[docs]</a><span class="k">def</span> <span class="nf">handle_torch_function</span><span class="p">(</span>
    <span class="n">public_api</span><span class="p">:</span> <span class="n">Callable</span><span class="p">,</span>
    <span class="n">relevant_args</span><span class="p">:</span> <span class="n">Iterable</span><span class="p">[</span><span class="n">Any</span><span class="p">],</span>
    <span class="o">*</span><span class="n">args</span><span class="p">,</span>
    <span class="o">**</span><span class="n">kwargs</span><span class="p">,</span>
<span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Any</span><span class="p">:</span>
<span class="w">    </span><span class="sd">&quot;&quot;&quot;Implement a function with checks for ``__torch_function__`` overrides.</span>

<span class="sd">    See torch::autograd::handle_torch_function for the equivalent of this</span>
<span class="sd">    function in the C++ implementation.</span>

<span class="sd">    Arguments</span>
<span class="sd">    ---------</span>
<span class="sd">    public_api : function</span>
<span class="sd">        Function exposed by the public torch API originally called like</span>
<span class="sd">        ``public_api(*args, **kwargs)`` on which arguments are now being</span>
<span class="sd">        checked.</span>
<span class="sd">    relevant_args : iterable</span>
<span class="sd">        Iterable of arguments to check for __torch_function__ methods.</span>
<span class="sd">    args : tuple</span>
<span class="sd">        Arbitrary positional arguments originally passed into ``public_api``.</span>
<span class="sd">    kwargs : tuple</span>
<span class="sd">        Arbitrary keyword arguments originally passed into ``public_api``.</span>

<span class="sd">    Returns</span>
<span class="sd">    -------</span>
<span class="sd">    object</span>
<span class="sd">        Result from calling ``implementation`` or an ``__torch_function__``</span>
<span class="sd">        method, as appropriate.</span>

<span class="sd">    Raises</span>
<span class="sd">    ------</span>
<span class="sd">    TypeError : if no implementation is found.</span>

<span class="sd">    Example</span>
<span class="sd">    -------</span>
<span class="sd">    &gt;&gt;&gt; def func(a):</span>
<span class="sd">    ...     if has_torch_function_unary(a):</span>
<span class="sd">    ...         return handle_torch_function(func, (a,), a)</span>
<span class="sd">    ...     return a + 0</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="c1"># Check for __torch_function__ methods.</span>
    <span class="n">overloaded_args</span> <span class="o">=</span> <span class="n">_get_overloaded_args</span><span class="p">(</span><span class="n">relevant_args</span><span class="p">)</span>
    <span class="c1"># overloaded_args already have unique types.</span>
    <span class="n">types</span> <span class="o">=</span> <span class="nb">tuple</span><span class="p">(</span><span class="nb">map</span><span class="p">(</span><span class="nb">type</span><span class="p">,</span> <span class="n">overloaded_args</span><span class="p">))</span>

    <span class="c1"># Check for __torch_function__ mode.</span>
    <span class="k">if</span> <span class="n">_is_torch_function_mode_enabled</span><span class="p">():</span>
        <span class="c1"># if we&#39;re here, the mode must be set to a TorchFunctionStackMode</span>
        <span class="c1"># this unsets it and calls directly into TorchFunctionStackMode&#39;s torch function</span>
        <span class="k">with</span> <span class="n">_pop_mode_temporarily</span><span class="p">()</span> <span class="k">as</span> <span class="n">mode</span><span class="p">:</span>
            <span class="n">result</span> <span class="o">=</span> <span class="n">mode</span><span class="o">.</span><span class="n">__torch_function__</span><span class="p">(</span><span class="n">public_api</span><span class="p">,</span> <span class="n">types</span><span class="p">,</span> <span class="n">args</span><span class="p">,</span> <span class="n">kwargs</span><span class="p">)</span>
        <span class="k">if</span> <span class="n">result</span> <span class="ow">is</span> <span class="ow">not</span> <span class="bp">NotImplemented</span><span class="p">:</span>
            <span class="k">return</span> <span class="n">result</span>

    <span class="c1"># Call overrides</span>
    <span class="k">for</span> <span class="n">overloaded_arg</span> <span class="ow">in</span> <span class="n">overloaded_args</span><span class="p">:</span>
        <span class="c1"># This call needs to become a classmethod call in the future.</span>
        <span class="c1"># See https://github.com/pytorch/pytorch/issues/63767</span>
        <span class="n">torch_func_method</span> <span class="o">=</span> <span class="n">overloaded_arg</span><span class="o">.</span><span class="n">__torch_function__</span>
        <span class="k">if</span> <span class="p">(</span>
            <span class="nb">hasattr</span><span class="p">(</span><span class="n">torch_func_method</span><span class="p">,</span> <span class="s2">&quot;__self__&quot;</span><span class="p">)</span>
            <span class="ow">and</span> <span class="n">torch_func_method</span><span class="o">.</span><span class="vm">__self__</span> <span class="ow">is</span> <span class="n">overloaded_arg</span>
            <span class="ow">and</span> <span class="n">torch_func_method</span> <span class="ow">is</span> <span class="ow">not</span> <span class="n">torch</span><span class="o">.</span><span class="n">_C</span><span class="o">.</span><span class="n">_disabled_torch_function_impl</span>
        <span class="p">):</span>
            <span class="n">warnings</span><span class="o">.</span><span class="n">warn</span><span class="p">(</span>
                <span class="s2">&quot;Defining your `__torch_function__ as a plain method is deprecated and &quot;</span>
                <span class="s2">&quot;will be an error in future, please define it as a classmethod.&quot;</span><span class="p">,</span>
                <span class="ne">DeprecationWarning</span><span class="p">,</span>
            <span class="p">)</span>

        <span class="c1"># Use `public_api` instead of `implementation` so __torch_function__</span>
        <span class="c1"># implementations can do equality/identity comparisons.</span>
        <span class="n">result</span> <span class="o">=</span> <span class="n">torch_func_method</span><span class="p">(</span><span class="n">public_api</span><span class="p">,</span> <span class="n">types</span><span class="p">,</span> <span class="n">args</span><span class="p">,</span> <span class="n">kwargs</span><span class="p">)</span>

        <span class="k">if</span> <span class="n">result</span> <span class="ow">is</span> <span class="ow">not</span> <span class="bp">NotImplemented</span><span class="p">:</span>
            <span class="k">return</span> <span class="n">result</span>

    <span class="n">func_name</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">public_api</span><span class="o">.</span><span class="vm">__module__</span><span class="si">}</span><span class="s2">.</span><span class="si">{</span><span class="n">public_api</span><span class="o">.</span><span class="vm">__name__</span><span class="si">}</span><span class="s2">&quot;</span>
    <span class="n">msg</span> <span class="o">=</span> <span class="p">(</span>
        <span class="sa">f</span><span class="s2">&quot;no implementation found for &#39;</span><span class="si">{</span><span class="n">func_name</span><span class="si">}</span><span class="s2">&#39; on types that implement &quot;</span>
        <span class="sa">f</span><span class="s2">&quot;__torch_function__: </span><span class="si">{</span><span class="p">[</span><span class="nb">type</span><span class="p">(</span><span class="n">arg</span><span class="p">)</span><span class="w"> </span><span class="k">for</span><span class="w"> </span><span class="n">arg</span><span class="w"> </span><span class="ow">in</span><span class="w"> </span><span class="n">overloaded_args</span><span class="p">]</span><span class="si">}</span><span class="s2">&quot;</span>
    <span class="p">)</span>
    <span class="k">if</span> <span class="n">_is_torch_function_mode_enabled</span><span class="p">():</span>
        <span class="n">msg</span> <span class="o">+=</span> <span class="sa">f</span><span class="s2">&quot; nor in mode </span><span class="si">{</span><span class="n">_get_current_function_mode</span><span class="p">()</span><span class="si">}</span><span class="s2">&quot;</span>
    <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span></div>


<span class="n">has_torch_function</span> <span class="o">=</span> <span class="n">_add_docstr</span><span class="p">(</span>
    <span class="n">_has_torch_function</span><span class="p">,</span>
<span class="w">    </span><span class="sa">r</span><span class="sd">&quot;&quot;&quot;Check for __torch_function__ implementations in the elements of an iterable</span>
<span class="sd">    or if a __torch_function__ mode is enabled.  Considers exact ``Tensor`` s</span>
<span class="sd">    and ``Parameter`` s non-dispatchable.  Use this to guard a call to</span>
<span class="sd">    :func:`handle_torch_function`; don&#39;t use it to test if something</span>
<span class="sd">    is Tensor-like, use :func:`is_tensor_like` instead.</span>
<span class="sd">    Arguments</span>
<span class="sd">    ---------</span>
<span class="sd">    relevant_args : iterable</span>
<span class="sd">        Iterable or arguments to check for __torch_function__ methods.</span>
<span class="sd">    Returns</span>
<span class="sd">    -------</span>
<span class="sd">    bool</span>
<span class="sd">        True if any of the elements of relevant_args have __torch_function__</span>
<span class="sd">        implementations, False otherwise.</span>
<span class="sd">    See Also</span>
<span class="sd">    ________</span>
<span class="sd">    torch.is_tensor_like</span>
<span class="sd">        Checks if something is a Tensor-like, including an exact ``Tensor``.</span>
<span class="sd">    &quot;&quot;&quot;</span><span class="p">,</span>
<span class="p">)</span>

<span class="n">has_torch_function_unary</span> <span class="o">=</span> <span class="n">_add_docstr</span><span class="p">(</span>
    <span class="n">_has_torch_function_unary</span><span class="p">,</span>
<span class="w">    </span><span class="sa">r</span><span class="sd">&quot;&quot;&quot;Special case of `has_torch_function` for single inputs.</span>
<span class="sd">    Instead of:</span>
<span class="sd">      `has_torch_function((t,))`</span>
<span class="sd">    call:</span>
<span class="sd">      `has_torch_function_unary(t)`</span>
<span class="sd">    which skips unnecessary packing and unpacking work.</span>
<span class="sd">    &quot;&quot;&quot;</span><span class="p">,</span>
<span class="p">)</span>

<span class="n">has_torch_function_variadic</span> <span class="o">=</span> <span class="n">_add_docstr</span><span class="p">(</span>
    <span class="n">_has_torch_function_variadic</span><span class="p">,</span>
<span class="w">    </span><span class="sa">r</span><span class="sd">&quot;&quot;&quot;Special case of `has_torch_function` that skips tuple creation.</span>

<span class="sd">    This uses the METH_FASTCALL protocol introduced in Python 3.7</span>

<span class="sd">    Instead of:</span>
<span class="sd">      `has_torch_function((a, b))`</span>
<span class="sd">    call:</span>
<span class="sd">      `has_torch_function_variadic(a, b)`</span>
<span class="sd">    which skips unnecessary packing and unpacking work.</span>
<span class="sd">    &quot;&quot;&quot;</span><span class="p">,</span>
<span class="p">)</span>


<span class="nd">@functools</span><span class="o">.</span><span class="n">lru_cache</span><span class="p">(</span><span class="kc">None</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">_get_overridable_functions</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="p">(</span>
    <span class="n">Tuple</span><span class="p">[</span><span class="n">Dict</span><span class="p">[</span><span class="n">Any</span><span class="p">,</span> <span class="n">List</span><span class="p">[</span><span class="n">Callable</span><span class="p">]],</span> <span class="n">Dict</span><span class="p">[</span><span class="n">Callable</span><span class="p">,</span> <span class="nb">str</span><span class="p">]]</span>
<span class="p">):</span>
    <span class="n">overridable_funcs</span> <span class="o">=</span> <span class="n">collections</span><span class="o">.</span><span class="n">defaultdict</span><span class="p">(</span><span class="nb">list</span><span class="p">)</span>
    <span class="n">index</span> <span class="o">=</span> <span class="p">{}</span>
    <span class="n">tested_namespaces</span> <span class="o">=</span> <span class="p">[</span>
        <span class="p">(</span><span class="s2">&quot;torch&quot;</span><span class="p">,</span> <span class="n">torch</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">__all__</span><span class="p">),</span>
        <span class="p">(</span><span class="s2">&quot;torch.functional&quot;</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">functional</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">__all__</span><span class="p">),</span>
        <span class="p">(</span><span class="s2">&quot;torch.nn.functional&quot;</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="p">,</span> <span class="nb">dir</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">functional</span><span class="p">)),</span>
        <span class="p">(</span><span class="s2">&quot;torch.nn.init&quot;</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">init</span><span class="p">,</span> <span class="nb">dir</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">init</span><span class="p">)),</span>
        <span class="p">(</span><span class="s2">&quot;torch.Tensor&quot;</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">,</span> <span class="nb">dir</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">)),</span>
        <span class="p">(</span><span class="s2">&quot;torch.linalg&quot;</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="p">,</span> <span class="nb">dir</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">linalg</span><span class="p">)),</span>
        <span class="p">(</span><span class="s2">&quot;torch.fft&quot;</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">fft</span><span class="p">,</span> <span class="nb">dir</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">fft</span><span class="p">)),</span>
        <span class="p">(</span><span class="s2">&quot;torch.special&quot;</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="p">,</span> <span class="nb">dir</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">special</span><span class="p">)),</span>
    <span class="p">]</span>
    <span class="k">for</span> <span class="n">namespace_str</span><span class="p">,</span> <span class="n">namespace</span><span class="p">,</span> <span class="n">ns_funcs</span> <span class="ow">in</span> <span class="n">tested_namespaces</span><span class="p">:</span>
        <span class="k">for</span> <span class="n">func_name</span> <span class="ow">in</span> <span class="n">ns_funcs</span><span class="p">:</span>
            <span class="n">ignore</span> <span class="o">=</span> <span class="kc">False</span>
            <span class="c1"># ignore private functions or functions that are deleted in torch.__init__</span>
            <span class="k">if</span> <span class="n">namespace</span> <span class="ow">is</span> <span class="ow">not</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">:</span>
                <span class="k">if</span> <span class="n">func_name</span><span class="o">.</span><span class="n">startswith</span><span class="p">(</span><span class="s2">&quot;__&quot;</span><span class="p">):</span>
                    <span class="k">continue</span>
                <span class="k">elif</span> <span class="n">func_name</span><span class="o">.</span><span class="n">startswith</span><span class="p">(</span><span class="s2">&quot;_&quot;</span><span class="p">):</span>
                    <span class="n">ignore</span> <span class="o">=</span> <span class="kc">True</span>
                <span class="k">elif</span> <span class="n">func_name</span><span class="o">.</span><span class="n">endswith</span><span class="p">(</span><span class="s2">&quot;_&quot;</span><span class="p">):</span>
                    <span class="n">ignore</span> <span class="o">=</span> <span class="kc">True</span>
                <span class="k">elif</span> <span class="ow">not</span> <span class="n">func_name</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">islower</span><span class="p">():</span>
                    <span class="n">ignore</span> <span class="o">=</span> <span class="kc">True</span>
                <span class="k">elif</span> <span class="n">func_name</span> <span class="o">==</span> <span class="s2">&quot;unique_dim&quot;</span><span class="p">:</span>
                    <span class="k">continue</span>
            <span class="k">else</span><span class="p">:</span>
                <span class="n">func</span> <span class="o">=</span> <span class="nb">getattr</span><span class="p">(</span><span class="n">namespace</span><span class="p">,</span> <span class="n">func_name</span><span class="p">)</span>
                <span class="k">if</span> <span class="nb">getattr</span><span class="p">(</span><span class="nb">object</span><span class="p">,</span> <span class="n">func_name</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span> <span class="o">==</span> <span class="n">func</span><span class="p">:</span>
                    <span class="k">continue</span>
                <span class="k">if</span> <span class="n">func_name</span> <span class="o">==</span> <span class="s2">&quot;__weakref__&quot;</span><span class="p">:</span>
                    <span class="k">continue</span>
            <span class="n">func</span> <span class="o">=</span> <span class="nb">getattr</span><span class="p">(</span><span class="n">namespace</span><span class="p">,</span> <span class="n">func_name</span><span class="p">)</span>
            <span class="k">if</span> <span class="n">namespace</span> <span class="ow">is</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span> <span class="ow">and</span> <span class="nb">getattr</span><span class="p">(</span><span class="nb">object</span><span class="p">,</span> <span class="n">func_name</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span> <span class="o">==</span> <span class="n">func</span><span class="p">:</span>
                <span class="k">continue</span>
            <span class="c1"># ignore re-exported modules</span>
            <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">func</span><span class="p">,</span> <span class="n">types</span><span class="o">.</span><span class="n">ModuleType</span><span class="p">):</span>
                <span class="k">continue</span>
            <span class="c1"># ignore __future__ imports</span>
            <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">func</span><span class="p">,</span> <span class="n">__future__</span><span class="o">.</span><span class="n">_Feature</span><span class="p">):</span>
                <span class="k">continue</span>

            <span class="k">if</span> <span class="ow">not</span> <span class="nb">callable</span><span class="p">(</span><span class="n">func</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">func</span><span class="p">,</span> <span class="s2">&quot;__get__&quot;</span><span class="p">):</span>
                <span class="n">index</span><span class="p">[</span><span class="n">func</span><span class="o">.</span><span class="fm">__get__</span><span class="p">]</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">namespace_str</span><span class="si">}</span><span class="s2">.</span><span class="si">{</span><span class="n">func_name</span><span class="si">}</span><span class="s2">.__get__&quot;</span>
                <span class="n">index</span><span class="p">[</span><span class="n">func</span><span class="o">.</span><span class="fm">__set__</span><span class="p">]</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">namespace_str</span><span class="si">}</span><span class="s2">.</span><span class="si">{</span><span class="n">func_name</span><span class="si">}</span><span class="s2">.__set__&quot;</span>
                <span class="k">if</span> <span class="n">ignore</span><span class="p">:</span>
                    <span class="k">continue</span>
                <span class="k">if</span> <span class="n">func</span><span class="o">.</span><span class="fm">__get__</span> <span class="ow">in</span> <span class="n">get_ignored_functions</span><span class="p">():</span>
                    <span class="n">msg</span> <span class="o">=</span> <span class="p">(</span>
                        <span class="s2">&quot;</span><span class="si">{}</span><span class="s2">.</span><span class="si">{}</span><span class="s2"> is in the tuple returned by torch._overrides.get_ignored_functions &quot;</span>
                        <span class="s2">&quot;but still has an explicit override&quot;</span>
                    <span class="p">)</span>
                    <span class="k">assert</span> <span class="n">func</span><span class="o">.</span><span class="fm">__get__</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">get_testing_overrides</span><span class="p">(),</span> <span class="n">msg</span><span class="o">.</span><span class="n">format</span><span class="p">(</span>
                        <span class="n">namespace</span><span class="p">,</span> <span class="n">func</span><span class="o">.</span><span class="vm">__name__</span>
                    <span class="p">)</span>
                    <span class="k">continue</span>
                <span class="k">else</span><span class="p">:</span>
                    <span class="n">overridable_funcs</span><span class="p">[</span><span class="n">func</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">func</span><span class="o">.</span><span class="fm">__get__</span><span class="p">)</span>
                    <span class="k">continue</span>

            <span class="k">if</span> <span class="ow">not</span> <span class="nb">callable</span><span class="p">(</span><span class="n">func</span><span class="p">):</span>
                <span class="k">continue</span>

            <span class="n">index</span><span class="p">[</span><span class="n">func</span><span class="p">]</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">namespace_str</span><span class="si">}</span><span class="s2">.</span><span class="si">{</span><span class="n">func_name</span><span class="si">}</span><span class="s2">&quot;</span>

            <span class="k">if</span> <span class="n">ignore</span><span class="p">:</span>
                <span class="k">continue</span>

            <span class="c1"># cannot be overriden by __torch_function__</span>
            <span class="k">if</span> <span class="n">func</span> <span class="ow">in</span> <span class="n">get_ignored_functions</span><span class="p">():</span>
                <span class="n">msg</span> <span class="o">=</span> <span class="p">(</span>
                    <span class="s2">&quot;</span><span class="si">{}</span><span class="s2">.</span><span class="si">{}</span><span class="s2"> is in the tuple returned by torch._overrides.get_ignored_functions &quot;</span>
                    <span class="s2">&quot;but still has an explicit override&quot;</span>
                <span class="p">)</span>
                <span class="k">assert</span> <span class="n">func</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">get_testing_overrides</span><span class="p">(),</span> <span class="n">msg</span><span class="o">.</span><span class="n">format</span><span class="p">(</span>
                    <span class="n">namespace</span><span class="p">,</span> <span class="n">func</span><span class="o">.</span><span class="vm">__name__</span>
                <span class="p">)</span>
                <span class="k">continue</span>
            <span class="n">overridable_funcs</span><span class="p">[</span><span class="n">namespace</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">func</span><span class="p">)</span>
    <span class="k">return</span> <span class="n">overridable_funcs</span><span class="p">,</span> <span class="n">index</span>


<div class="viewcode-block" id="get_overridable_functions"><a class="viewcode-back" href="../../torch.overrides.html#torch.overrides.get_overridable_functions">[docs]</a><span class="nd">@_disable_user_warnings</span>
<span class="k">def</span> <span class="nf">get_overridable_functions</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="n">Dict</span><span class="p">[</span><span class="n">Any</span><span class="p">,</span> <span class="n">List</span><span class="p">[</span><span class="n">Callable</span><span class="p">]]:</span>
<span class="w">    </span><span class="sd">&quot;&quot;&quot;List functions that are overridable via __torch_function__</span>

<span class="sd">    Returns</span>
<span class="sd">    -------</span>
<span class="sd">    Dict[Any, List[Callable]]</span>
<span class="sd">        A dictionary that maps namespaces that contain overridable functions</span>
<span class="sd">        to functions in that namespace that can be overridden.</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="k">return</span> <span class="n">_get_overridable_functions</span><span class="p">()[</span><span class="mi">0</span><span class="p">]</span></div>


<div class="viewcode-block" id="resolve_name"><a class="viewcode-back" href="../../torch.overrides.html#torch.overrides.resolve_name">[docs]</a><span class="nd">@_disable_user_warnings</span>
<span class="k">def</span> <span class="nf">resolve_name</span><span class="p">(</span><span class="n">f</span><span class="p">):</span>
<span class="w">    </span><span class="sd">&quot;&quot;&quot;Get a human readable string name for a function passed to</span>
<span class="sd">    __torch_function__</span>

<span class="sd">    Arguments</span>
<span class="sd">    ---------</span>
<span class="sd">    f : Callable</span>
<span class="sd">        Function to resolve the name of.</span>

<span class="sd">    Returns</span>
<span class="sd">    -------</span>
<span class="sd">    str</span>
<span class="sd">        Name of the function; if eval&#39;ed it should give back the input</span>
<span class="sd">        function.</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">f</span><span class="p">,</span> <span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">_ops</span><span class="o">.</span><span class="n">OpOverload</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">_ops</span><span class="o">.</span><span class="n">OpOverloadPacket</span><span class="p">)):</span>
        <span class="k">return</span> <span class="nb">str</span><span class="p">(</span><span class="n">f</span><span class="p">)</span>
    <span class="k">return</span> <span class="n">_get_overridable_functions</span><span class="p">()[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">f</span><span class="p">)</span></div>


<span class="nd">@functools</span><span class="o">.</span><span class="n">lru_cache</span><span class="p">(</span><span class="kc">None</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">_get_tensor_methods</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="n">Set</span><span class="p">[</span><span class="n">Callable</span><span class="p">]:</span>
<span class="w">    </span><span class="sd">&quot;&quot;&quot;Returns a set of the overridable methods on ``torch.Tensor``&quot;&quot;&quot;</span>
    <span class="n">overridable_funcs</span> <span class="o">=</span> <span class="n">get_overridable_functions</span><span class="p">()</span>
    <span class="n">methods</span> <span class="o">=</span> <span class="nb">set</span><span class="p">(</span><span class="n">overridable_funcs</span><span class="p">[</span><span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">])</span>
    <span class="k">return</span> <span class="n">methods</span>


<div class="viewcode-block" id="is_tensor_method_or_property"><a class="viewcode-back" href="../../torch.overrides.html#torch.overrides.is_tensor_method_or_property">[docs]</a><span class="nd">@_disable_user_warnings</span>
<span class="k">def</span> <span class="nf">is_tensor_method_or_property</span><span class="p">(</span><span class="n">func</span><span class="p">:</span> <span class="n">Callable</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">bool</span><span class="p">:</span>
<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Returns True if the function passed in is a handler for a</span>
<span class="sd">    method or property belonging to ``torch.Tensor``, as passed</span>
<span class="sd">    into ``__torch_function__``.</span>

<span class="sd">    .. note::</span>
<span class="sd">       For properties, their ``__get__`` method must be passed in.</span>

<span class="sd">    This may be needed, in particular, for the following reasons:</span>

<span class="sd">    1. Methods/properties sometimes don&#39;t contain a `__module__` slot.</span>
<span class="sd">    2. They require that the first passed-in argument is an instance</span>
<span class="sd">       of ``torch.Tensor``.</span>

<span class="sd">    Examples</span>
<span class="sd">    --------</span>
<span class="sd">    &gt;&gt;&gt; is_tensor_method_or_property(torch.Tensor.add)</span>
<span class="sd">    True</span>
<span class="sd">    &gt;&gt;&gt; is_tensor_method_or_property(torch.add)</span>
<span class="sd">    False</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="k">return</span> <span class="n">func</span> <span class="ow">in</span> <span class="n">_get_tensor_methods</span><span class="p">()</span> <span class="ow">or</span> <span class="n">func</span><span class="o">.</span><span class="vm">__name__</span> <span class="o">==</span> <span class="s2">&quot;__get__&quot;</span></div>


<div class="viewcode-block" id="is_tensor_like"><a class="viewcode-back" href="../../torch.overrides.html#torch.overrides.is_tensor_like">[docs]</a><span class="k">def</span> <span class="nf">is_tensor_like</span><span class="p">(</span><span class="n">inp</span><span class="p">):</span>
<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Returns ``True`` if the passed-in input is a Tensor-like.</span>

<span class="sd">    Currently, this occurs whenever there&#39;s a ``__torch_function__``</span>
<span class="sd">    attribute on the type of the input.</span>

<span class="sd">    Examples</span>
<span class="sd">    --------</span>
<span class="sd">    A subclass of tensor is generally a Tensor-like.</span>

<span class="sd">    &gt;&gt;&gt; class SubTensor(torch.Tensor): ...</span>
<span class="sd">    &gt;&gt;&gt; is_tensor_like(SubTensor([0]))</span>
<span class="sd">    True</span>

<span class="sd">    Built-in or user types aren&#39;t usually Tensor-like.</span>

<span class="sd">    &gt;&gt;&gt; is_tensor_like(6)</span>
<span class="sd">    False</span>
<span class="sd">    &gt;&gt;&gt; is_tensor_like(None)</span>
<span class="sd">    False</span>
<span class="sd">    &gt;&gt;&gt; class NotATensor: ...</span>
<span class="sd">    &gt;&gt;&gt; is_tensor_like(NotATensor())</span>
<span class="sd">    False</span>

<span class="sd">    But, they can be made Tensor-like by implementing __torch_function__.</span>

<span class="sd">    &gt;&gt;&gt; class TensorLike:</span>
<span class="sd">    ...     @classmethod</span>
<span class="sd">    ...     def __torch_function__(cls, func, types, args, kwargs):</span>
<span class="sd">    ...         return -1</span>
<span class="sd">    &gt;&gt;&gt; is_tensor_like(TensorLike())</span>
<span class="sd">    True</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="k">return</span> <span class="nb">type</span><span class="p">(</span><span class="n">inp</span><span class="p">)</span> <span class="ow">is</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span> <span class="ow">or</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">inp</span><span class="p">,</span> <span class="s2">&quot;__torch_function__&quot;</span><span class="p">)</span></div>


<span class="k">class</span> <span class="nc">TorchFunctionMode</span><span class="p">:</span>
<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    A ``TorchFunctionMode`` allows you to override the meaning of all</span>
<span class="sd">    ``__torch_function__`` overrideable functions within a dynamic scope,</span>
<span class="sd">    without having to actually create a tensor subclass or manually</span>
<span class="sd">    monkey-patch functions in the PyTorch API.  Some common situations</span>
<span class="sd">    where you should use a mode:</span>

<span class="sd">        * You want to override the meaning of factory functions, or other</span>
<span class="sd">          functions that do not otherwise take a tensor as an argument</span>
<span class="sd">          (these cannot be overridden with tensor subclasses).</span>

<span class="sd">        * You want to override the behavior of all functions without needing</span>
<span class="sd">          to wrap your inputs in tensor subclasses; e.g., if you are just</span>
<span class="sd">          interested in logging intermediate computations.</span>

<span class="sd">        * You want to control the order of execution of various tensor</span>
<span class="sd">          subclasses explicitly, rather than implicitly via the return of</span>
<span class="sd">          ``NotImplemented``.</span>

<span class="sd">    Independent subclasses of :class:`TorchFunctionMode` are compositional:</span>
<span class="sd">    modes can be pushed onto a stack using ``with MyMode():``.</span>
<span class="sd">    When you call functions in the PyTorch API inside your</span>
<span class="sd">    ``__torch_function__`` implementation, by default, they will forward on to</span>
<span class="sd">    the next mode on the mode stack.  If you want recursively call back into</span>
<span class="sd">    your current ``__torch_function__`` implementation, either explicitly</span>
<span class="sd">    invoke ``self.__torch_function__(...)``, or use the context manager</span>
<span class="sd">    ``enable_torch_function_mode(self, replace=self.inner)`` to make PyTorch</span>
<span class="sd">    API self-referential (beware of infinite loops, in this case!)</span>
<span class="sd">    &quot;&quot;&quot;</span>

    <span class="n">inner</span><span class="p">:</span> <span class="s2">&quot;TorchFunctionMode&quot;</span>

    <span class="c1"># Force metaclass to generate constructor at the base of the hierarchy</span>
    <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
        <span class="k">pass</span>

    <span class="k">def</span> <span class="nf">__torch_function__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">func</span><span class="p">,</span> <span class="n">types</span><span class="p">,</span> <span class="n">args</span><span class="o">=</span><span class="p">(),</span> <span class="n">kwargs</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
        <span class="k">raise</span> <span class="ne">NotImplementedError</span>

    <span class="k">def</span> <span class="fm">__enter__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="n">_push_mode</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span>
        <span class="k">return</span> <span class="bp">self</span>

    <span class="k">def</span> <span class="fm">__exit__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">exc_type</span><span class="p">,</span> <span class="n">exc_val</span><span class="p">,</span> <span class="n">exc_tb</span><span class="p">):</span>
        <span class="n">_pop_mode</span><span class="p">()</span>

    <span class="nd">@classmethod</span>
    <span class="k">def</span> <span class="nf">push</span><span class="p">(</span><span class="bp">cls</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
        <span class="n">warnings</span><span class="o">.</span><span class="n">warn</span><span class="p">(</span>
            <span class="s2">&quot;`Mode.push()` is no longer necessary and can be replaced with just `with Mode()`&quot;</span>
        <span class="p">)</span>
        <span class="n">instance</span> <span class="o">=</span> <span class="bp">cls</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
        <span class="k">return</span> <span class="n">instance</span>


<span class="k">def</span> <span class="nf">_get_current_function_mode</span><span class="p">():</span>
    <span class="n">stack_len</span> <span class="o">=</span> <span class="n">_len_torch_function_stack</span><span class="p">()</span>
    <span class="k">return</span> <span class="n">_get_function_stack_at</span><span class="p">(</span><span class="n">stack_len</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)</span> <span class="k">if</span> <span class="n">stack_len</span> <span class="o">&gt;</span> <span class="mi">0</span> <span class="k">else</span> <span class="kc">None</span>


<span class="k">def</span> <span class="nf">_get_current_function_mode_stack</span><span class="p">():</span>
    <span class="n">stack_len</span> <span class="o">=</span> <span class="n">_len_torch_function_stack</span><span class="p">()</span>
    <span class="k">return</span> <span class="p">[</span><span class="n">_get_function_stack_at</span><span class="p">(</span><span class="n">i</span><span class="p">)</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">stack_len</span><span class="p">)]</span>


<span class="k">def</span> <span class="nf">_push_mode</span><span class="p">(</span><span class="n">mode</span><span class="p">):</span>
    <span class="n">_push_on_torch_function_stack</span><span class="p">(</span><span class="n">mode</span><span class="p">)</span>


<span class="k">def</span> <span class="nf">_pop_mode</span><span class="p">():</span>
    <span class="n">old</span> <span class="o">=</span> <span class="n">_pop_torch_function_stack</span><span class="p">()</span>
    <span class="k">return</span> <span class="n">old</span>


<span class="nd">@contextlib</span><span class="o">.</span><span class="n">contextmanager</span>
<span class="k">def</span> <span class="nf">_pop_mode_temporarily</span><span class="p">():</span>
    <span class="n">old</span> <span class="o">=</span> <span class="n">_pop_mode</span><span class="p">()</span>
    <span class="k">try</span><span class="p">:</span>
        <span class="k">yield</span> <span class="n">old</span>
    <span class="k">finally</span><span class="p">:</span>
        <span class="n">_push_mode</span><span class="p">(</span><span class="n">old</span><span class="p">)</span>


<span class="k">class</span> <span class="nc">BaseTorchFunctionMode</span><span class="p">(</span><span class="n">TorchFunctionMode</span><span class="p">):</span>
    <span class="k">def</span> <span class="nf">__torch_function__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">func</span><span class="p">,</span> <span class="n">types</span><span class="p">,</span> <span class="n">args</span><span class="o">=</span><span class="p">(),</span> <span class="n">kwargs</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
        <span class="k">if</span> <span class="n">kwargs</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
            <span class="n">kwargs</span> <span class="o">=</span> <span class="p">{}</span>
        <span class="k">return</span> <span class="n">func</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>


<span class="nd">@contextlib</span><span class="o">.</span><span class="n">contextmanager</span>
<span class="k">def</span> <span class="nf">_enable_torch_function</span><span class="p">():</span>
    <span class="n">old_state</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">_C</span><span class="o">.</span><span class="n">_get_torch_function_state</span><span class="p">()</span>
    <span class="k">try</span><span class="p">:</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">_C</span><span class="o">.</span><span class="n">_set_torch_function_state</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">_C</span><span class="o">.</span><span class="n">_TorchFunctionState</span><span class="o">.</span><span class="n">ENABLED</span><span class="p">)</span>
        <span class="k">yield</span>
    <span class="k">finally</span><span class="p">:</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">_C</span><span class="o">.</span><span class="n">_set_torch_function_state</span><span class="p">(</span><span class="n">old_state</span><span class="p">)</span>


<span class="nd">@contextlib</span><span class="o">.</span><span class="n">contextmanager</span>
<span class="k">def</span> <span class="nf">enable_reentrant_dispatch</span><span class="p">():</span>
    <span class="c1"># NB: this can&#39;t simply be</span>
    <span class="c1"># `enable_reentrant_dispatch = torch._C._RestorePythonTLSSnapshot`</span>
    <span class="c1"># because:</span>
    <span class="c1"># 1. torch._C._RestorePythonTLSSnapshot is unavailable when this file</span>
    <span class="c1">#    initially gets imported. Probably an import order thing.</span>
    <span class="c1"># 2. enable_reentrant_dispatch is technically public API; assigning</span>
    <span class="c1">#    it the object would change the __module__ to look private.</span>
    <span class="k">with</span> <span class="n">torch</span><span class="o">.</span><span class="n">_C</span><span class="o">.</span><span class="n">_RestorePythonTLSSnapshot</span><span class="p">():</span>
        <span class="k">try</span><span class="p">:</span>
            <span class="k">yield</span>
        <span class="k">finally</span><span class="p">:</span>
            <span class="k">pass</span>
</pre></div>

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