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<h1>Source code for torch.fx.node</h1><div class="highlight"><pre>
<span></span><span class="c1"># Nodes represent a definition of a value in our graph of operators.</span>
<span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">TYPE_CHECKING</span><span class="p">,</span> <span class="n">Union</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">Tuple</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">Dict</span><span class="p">,</span> <span class="n">Set</span>
<span class="kn">from</span> <span class="nn">._compatibility</span> <span class="kn">import</span> <span class="n">compatibility</span>
<span class="kn">from</span> <span class="nn">.immutable_collections</span> <span class="kn">import</span> <span class="n">immutable_dict</span><span class="p">,</span> <span class="n">immutable_list</span>
<span class="kn">import</span> <span class="nn">torch</span>
<span class="kn">import</span> <span class="nn">builtins</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">torch.fx.operator_schemas</span> <span class="kn">import</span> <span class="n">normalize_function</span><span class="p">,</span> <span class="n">normalize_module</span><span class="p">,</span> <span class="n">ArgsKwargsPair</span>
<span class="kn">from</span> <span class="nn">.._ops</span> <span class="kn">import</span> <span class="n">ops</span> <span class="k">as</span> <span class="n">_ops</span>
<span class="k">if</span> <span class="n">TYPE_CHECKING</span><span class="p">:</span>
<span class="kn">from</span> <span class="nn">.graph</span> <span class="kn">import</span> <span class="n">Graph</span>
<span class="n">__all__</span> <span class="o">=</span> <span class="p">[</span><span class="s1">'Node'</span><span class="p">,</span> <span class="s1">'map_arg'</span><span class="p">,</span> <span class="s1">'map_aggregate'</span><span class="p">]</span>
<span class="n">BaseArgumentTypes</span> <span class="o">=</span> <span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">int</span><span class="p">,</span> <span class="nb">float</span><span class="p">,</span> <span class="nb">bool</span><span class="p">,</span> <span class="nb">complex</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">Tensor</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">memory_format</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">base_types</span> <span class="o">=</span> <span class="n">BaseArgumentTypes</span><span class="o">.</span><span class="n">__args__</span> <span class="c1"># type: ignore[attr-defined]</span>
<span class="n">Target</span> <span class="o">=</span> <span class="n">Union</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">Any</span><span class="p">],</span> <span class="nb">str</span><span class="p">]</span>
<span class="n">Argument</span> <span class="o">=</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span>
<span class="n">Tuple</span><span class="p">[</span><span class="n">Any</span><span class="p">,</span> <span class="o">...</span><span class="p">],</span> <span class="c1"># actually Argument, but mypy can't represent recursive types</span>
<span class="n">List</span><span class="p">[</span><span class="n">Any</span><span class="p">],</span> <span class="c1"># actually Argument</span>
<span class="n">Dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">],</span> <span class="c1"># actually Argument</span>
<span class="nb">slice</span><span class="p">,</span> <span class="c1"># Slice[Argument, Argument, Argument], but slice is not a templated type in typing</span>
<span class="nb">range</span><span class="p">,</span>
<span class="s1">'Node'</span><span class="p">,</span>
<span class="n">BaseArgumentTypes</span>
<span class="p">]]</span>
<span class="n">_side_effectful_functions</span><span class="p">:</span> <span class="n">Set</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">_assert</span><span class="p">,</span>
<span class="n">_ops</span><span class="o">.</span><span class="n">profiler</span><span class="o">.</span><span class="n">_record_function_enter</span><span class="p">,</span>
<span class="n">_ops</span><span class="o">.</span><span class="n">profiler</span><span class="o">.</span><span class="n">_record_function_enter_new</span><span class="p">,</span>
<span class="n">_ops</span><span class="o">.</span><span class="n">profiler</span><span class="o">.</span><span class="n">_record_function_exit</span><span class="p">}</span>
<span class="c1"># this is fixed on master, WAR for 1.5</span>
<span class="k">def</span> <span class="nf">_find_module_of_method</span><span class="p">(</span><span class="n">orig_method</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">Any</span><span class="p">])</span> <span class="o">-></span> <span class="nb">str</span><span class="p">:</span>
<span class="n">name</span> <span class="o">=</span> <span class="n">orig_method</span><span class="o">.</span><span class="vm">__name__</span>
<span class="n">module</span> <span class="o">=</span> <span class="n">orig_method</span><span class="o">.</span><span class="vm">__module__</span>
<span class="k">if</span> <span class="n">module</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="k">return</span> <span class="n">module</span>
<span class="k">for</span> <span class="n">guess</span> <span class="ow">in</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">nn</span><span class="o">.</span><span class="n">functional</span><span class="p">]:</span>
<span class="k">if</span> <span class="nb">getattr</span><span class="p">(</span><span class="n">guess</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="ow">is</span> <span class="n">orig_method</span><span class="p">:</span>
<span class="k">return</span> <span class="n">guess</span><span class="o">.</span><span class="vm">__name__</span>
<span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span><span class="sa">f</span><span class="s1">'cannot find module for </span><span class="si">{</span><span class="n">orig_method</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
<span class="c1"># Borrowed from CPython typing module</span>
<span class="c1"># https://github.com/python/cpython/blob/f90dc36c15d7fee0efaf6d39e97be0bdf2683e93/Lib/typing.py#L156</span>
<span class="k">def</span> <span class="nf">_type_repr</span><span class="p">(</span><span class="n">obj</span><span class="p">):</span>
<span class="sd">"""Return the repr() of an object, special-casing types (internal helper).</span>
<span class="sd"> If obj is a type, we return a shorter version than the default</span>
<span class="sd"> type.__repr__, based on the module and qualified name, which is</span>
<span class="sd"> typically enough to uniquely identify a type. For everything</span>
<span class="sd"> else, we fall back on repr(obj).</span>
<span class="sd"> """</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">obj</span><span class="p">,</span> <span class="nb">type</span><span class="p">):</span>
<span class="k">if</span> <span class="n">obj</span><span class="o">.</span><span class="vm">__module__</span> <span class="o">==</span> <span class="s1">'builtins'</span><span class="p">:</span>
<span class="k">return</span> <span class="n">obj</span><span class="o">.</span><span class="vm">__qualname__</span>
<span class="k">return</span> <span class="sa">f</span><span class="s1">'</span><span class="si">{</span><span class="n">obj</span><span class="o">.</span><span class="vm">__module__</span><span class="si">}</span><span class="s1">.</span><span class="si">{</span><span class="n">obj</span><span class="o">.</span><span class="vm">__qualname__</span><span class="si">}</span><span class="s1">'</span>
<span class="k">if</span> <span class="n">obj</span> <span class="ow">is</span> <span class="o">...</span><span class="p">:</span>
<span class="k">return</span><span class="p">(</span><span class="s1">'...'</span><span class="p">)</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">obj</span><span class="p">,</span> <span class="n">types</span><span class="o">.</span><span class="n">FunctionType</span><span class="p">):</span>
<span class="k">return</span> <span class="n">obj</span><span class="o">.</span><span class="vm">__name__</span>
<span class="k">return</span> <span class="nb">repr</span><span class="p">(</span><span class="n">obj</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">_get_qualified_name</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">...</span><span class="p">,</span> <span class="n">Any</span><span class="p">])</span> <span class="o">-></span> <span class="nb">str</span><span class="p">:</span>
<span class="c1"># things like getattr just appear in builtins</span>
<span class="k">if</span> <span class="nb">getattr</span><span class="p">(</span><span class="n">builtins</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="kc">None</span><span class="p">)</span> <span class="ow">is</span> <span class="n">func</span><span class="p">:</span>
<span class="k">return</span> <span class="n">func</span><span class="o">.</span><span class="vm">__name__</span>
<span class="c1"># torch.Tensor.{fn}</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">MethodDescriptorType</span><span class="p">)</span> <span class="ow">and</span> <span class="n">func</span> <span class="ow">is</span> <span class="nb">getattr</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">func</span><span class="o">.</span><span class="vm">__name__</span><span class="p">,</span> <span class="kc">None</span><span class="p">):</span>
<span class="k">return</span> <span class="sa">f</span><span class="s2">"torch.Tensor.</span><span class="si">{</span><span class="n">func</span><span class="o">.</span><span class="vm">__name__</span><span class="si">}</span><span class="s2">"</span>
<span class="n">name</span> <span class="o">=</span> <span class="n">func</span><span class="o">.</span><span class="vm">__name__</span>
<span class="n">module</span> <span class="o">=</span> <span class="n">_find_module_of_method</span><span class="p">(</span><span class="n">func</span><span class="p">)</span>
<span class="n">module</span> <span class="o">=</span> <span class="n">module</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="s1">'torch._ops'</span><span class="p">,</span> <span class="s1">'torch.ops'</span><span class="p">)</span> <span class="c1"># WAR for bug in how torch.ops assigns module</span>
<span class="c1"># Fixup segment_reduce mismatch</span>
<span class="k">if</span> <span class="n">module</span> <span class="o">==</span> <span class="s2">"torch"</span> <span class="ow">and</span> <span class="n">name</span> <span class="o">==</span> <span class="s2">"segment_reduce"</span><span class="p">:</span>
<span class="n">name</span> <span class="o">=</span> <span class="s2">"_"</span> <span class="o">+</span> <span class="n">name</span>
<span class="k">return</span> <span class="sa">f</span><span class="s1">'</span><span class="si">{</span><span class="n">module</span><span class="si">}</span><span class="s1">.</span><span class="si">{</span><span class="n">name</span><span class="si">}</span><span class="s1">'</span>
<span class="k">def</span> <span class="nf">_format_arg</span><span class="p">(</span><span class="n">arg</span><span class="p">,</span> <span class="n">max_list_len</span><span class="o">=</span><span class="nb">float</span><span class="p">(</span><span class="s1">'inf'</span><span class="p">))</span> <span class="o">-></span> <span class="nb">str</span><span class="p">:</span>
<span class="k">if</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">arg</span><span class="p">,</span> <span class="s1">'_custom_fx_repr_fn'</span><span class="p">):</span>
<span class="k">return</span> <span class="n">arg</span><span class="o">.</span><span class="n">_custom_fx_repr_fn</span><span class="p">()</span>
<span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">arg</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span>
<span class="n">items</span> <span class="o">=</span> <span class="s1">', '</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">_format_arg</span><span class="p">(</span><span class="n">a</span><span class="p">)</span> <span class="k">for</span> <span class="n">idx</span><span class="p">,</span> <span class="n">a</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">arg</span><span class="p">)</span> <span class="k">if</span> <span class="n">idx</span> <span class="o"><</span> <span class="n">max_list_len</span><span class="p">)</span>
<span class="n">maybe_len</span> <span class="o">=</span> <span class="s1">''</span> <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">arg</span><span class="p">)</span> <span class="o"><</span> <span class="n">max_list_len</span> <span class="o">+</span> <span class="mi">1</span> <span class="k">else</span> <span class="sa">f</span><span class="s1">', ...[total_len=</span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">arg</span><span class="p">)</span><span class="si">}</span><span class="s1">]'</span>
<span class="k">return</span> <span class="sa">f</span><span class="s1">'[</span><span class="si">{</span><span class="n">items</span><span class="si">}{</span><span class="n">maybe_len</span><span class="si">}</span><span class="s1">]'</span>
<span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">arg</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">):</span>
<span class="n">items</span> <span class="o">=</span> <span class="s1">', '</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">_format_arg</span><span class="p">(</span><span class="n">a</span><span class="p">)</span> <span class="k">for</span> <span class="n">idx</span><span class="p">,</span> <span class="n">a</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">arg</span><span class="p">)</span> <span class="k">if</span> <span class="n">idx</span> <span class="o"><</span> <span class="n">max_list_len</span><span class="p">)</span>
<span class="n">maybe_len</span> <span class="o">=</span> <span class="s1">''</span> <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">arg</span><span class="p">)</span> <span class="o"><</span> <span class="n">max_list_len</span> <span class="o">+</span> <span class="mi">1</span> <span class="k">else</span> <span class="sa">f</span><span class="s1">', ...[total_len=</span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">arg</span><span class="p">)</span><span class="si">}</span><span class="s1">]'</span>
<span class="n">maybe_comma</span> <span class="o">=</span> <span class="s1">','</span> <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">arg</span><span class="p">)</span> <span class="o">==</span> <span class="mi">1</span> <span class="k">else</span> <span class="s1">''</span>
<span class="k">return</span> <span class="sa">f</span><span class="s1">'(</span><span class="si">{</span><span class="n">items</span><span class="si">}{</span><span class="n">maybe_comma</span><span class="si">}{</span><span class="n">maybe_len</span><span class="si">}</span><span class="s1">)'</span>
<span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">arg</span><span class="p">,</span> <span class="nb">dict</span><span class="p">):</span>
<span class="n">items_str</span> <span class="o">=</span> <span class="s1">', '</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="sa">f</span><span class="s1">'</span><span class="si">{</span><span class="n">k</span><span class="si">}</span><span class="s1">: </span><span class="si">{</span><span class="n">_format_arg</span><span class="p">(</span><span class="n">v</span><span class="p">)</span><span class="si">}</span><span class="s1">'</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">arg</span><span class="o">.</span><span class="n">items</span><span class="p">())</span>
<span class="k">return</span> <span class="sa">f</span><span class="s1">'</span><span class="se">{{</span><span class="si">{</span><span class="n">items_str</span><span class="si">}</span><span class="se">}}</span><span class="s1">'</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">arg</span><span class="p">,</span> <span class="n">Node</span><span class="p">):</span>
<span class="k">return</span> <span class="s1">'%'</span> <span class="o">+</span> <span class="nb">str</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="k">return</span> <span class="nb">str</span><span class="p">(</span><span class="n">arg</span><span class="p">)</span>
<div class="viewcode-block" id="Node"><a class="viewcode-back" href="../../../fx.html#torch.fx.Node">[docs]</a><span class="nd">@compatibility</span><span class="p">(</span><span class="n">is_backward_compatible</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="k">class</span> <span class="nc">Node</span><span class="p">:</span>
<span class="sd">"""</span>
<span class="sd"> ``Node`` is the data structure that represents individual operations within</span>
<span class="sd"> a ``Graph``. For the most part, Nodes represent callsites to various entities,</span>
<span class="sd"> such as operators, methods, and Modules (some exceptions include nodes that</span>
<span class="sd"> specify function inputs and outputs). Each ``Node`` has a function specified</span>
<span class="sd"> by its ``op`` property. The ``Node`` semantics for each value of ``op`` are as follows:</span>
<span class="sd"> - ``placeholder`` represents a function input. The ``name`` attribute specifies the name this value will take on.</span>
<span class="sd"> ``target`` is similarly the name of the argument. ``args`` holds either: 1) nothing, or 2) a single argument</span>
<span class="sd"> denoting the default parameter of the function input. ``kwargs`` is don't-care. Placeholders correspond to</span>
<span class="sd"> the function parameters (e.g. ``x``) in the graph printout.</span>
<span class="sd"> - ``get_attr`` retrieves a parameter from the module hierarchy. ``name`` is similarly the name the result of the</span>
<span class="sd"> fetch is assigned to. ``target`` is the fully-qualified name of the parameter's position in the module hierarchy.</span>
<span class="sd"> ``args`` and ``kwargs`` are don't-care</span>
<span class="sd"> - ``call_function`` applies a free function to some values. ``name`` is similarly the name of the value to assign</span>
<span class="sd"> to. ``target`` is the function to be applied. ``args`` and ``kwargs`` represent the arguments to the function,</span>
<span class="sd"> following the Python calling convention</span>
<span class="sd"> - ``call_module`` applies a module in the module hierarchy's ``forward()`` method to given arguments. ``name`` is</span>
<span class="sd"> as previous. ``target`` is the fully-qualified name of the module in the module hierarchy to call.</span>
<span class="sd"> ``args`` and ``kwargs`` represent the arguments to invoke the module on, *excluding the self argument*.</span>
<span class="sd"> - ``call_method`` calls a method on a value. ``name`` is as similar. ``target`` is the string name of the method</span>
<span class="sd"> to apply to the ``self`` argument. ``args`` and ``kwargs`` represent the arguments to invoke the module on,</span>
<span class="sd"> *including the self argument*</span>
<span class="sd"> - ``output`` contains the output of the traced function in its ``args[0]`` attribute. This corresponds to the "return" statement</span>
<span class="sd"> in the Graph printout.</span>
<span class="sd"> """</span>
<span class="nd">@compatibility</span><span class="p">(</span><span class="n">is_backward_compatible</span><span class="o">=</span><span class="kc">True</span><span class="p">)</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="n">graph</span><span class="p">:</span> <span class="s1">'Graph'</span><span class="p">,</span> <span class="n">name</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">op</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">target</span><span class="p">:</span> <span class="s1">'Target'</span><span class="p">,</span>
<span class="n">args</span><span class="p">:</span> <span class="n">Tuple</span><span class="p">[</span><span class="s1">'Argument'</span><span class="p">,</span> <span class="o">...</span><span class="p">],</span> <span class="n">kwargs</span><span class="p">:</span> <span class="n">Dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="s1">'Argument'</span><span class="p">],</span>
<span class="n">return_type</span> <span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Any</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">)</span> <span class="o">-></span> <span class="kc">None</span><span class="p">:</span>
<span class="sd">"""</span>
<span class="sd"> Instantiate an instance of ``Node``. Note: most often, you want to use the</span>
<span class="sd"> Graph APIs, i.e. ``Graph.call_module``, ``Graph.call_method``, etc. rather</span>
<span class="sd"> than instantiating a ``Node`` directly.</span>
<span class="sd"> Args:</span>
<span class="sd"> graph (Graph): The ``Graph`` to which this ``Node`` should belong.</span>
<span class="sd"> name (str): The name to which the output of this ``Node`` should be assigned</span>
<span class="sd"> op (str): The opcode for this ``Node``. Can be one of 'placeholder',</span>
<span class="sd"> 'call_method', 'call_module', 'call_function', 'get_attr',</span>
<span class="sd"> 'output'</span>
<span class="sd"> target ('Target'): The target this op should call. See the broader</span>
<span class="sd"> ``Node`` docstring for more details.</span>
<span class="sd"> args (Tuple['Argument']): The args to be passed to ``target``</span>
<span class="sd"> kwargs (Dict[str, 'Argument']): The kwargs to be passed to ``target``</span>
<span class="sd"> return_type (Optional[Any]): The python type expression representing the</span>
<span class="sd"> type of the output of this node. This field can be used for</span>
<span class="sd"> annotation of values in the generated code or for other types</span>
<span class="sd"> of analyses.</span>
<span class="sd"> """</span>
<span class="bp">self</span><span class="o">.</span><span class="n">graph</span> <span class="o">=</span> <span class="n">graph</span>
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="n">name</span> <span class="c1"># unique name of value being created</span>
<span class="k">assert</span> <span class="n">op</span> <span class="ow">in</span> <span class="p">[</span><span class="s1">'placeholder'</span><span class="p">,</span> <span class="s1">'call_method'</span><span class="p">,</span> <span class="s1">'call_module'</span><span class="p">,</span> <span class="s1">'call_function'</span><span class="p">,</span> <span class="s1">'get_attr'</span><span class="p">,</span> <span class="s1">'output'</span><span class="p">,</span> <span class="s1">'root'</span><span class="p">]</span>
<span class="bp">self</span><span class="o">.</span><span class="n">op</span> <span class="o">=</span> <span class="n">op</span> <span class="c1"># the kind of operation = placeholder|call_method|call_module|call_function|get_attr</span>
<span class="k">if</span> <span class="n">op</span> <span class="o">==</span> <span class="s1">'call_function'</span><span class="p">:</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">callable</span><span class="p">(</span><span class="n">target</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="sa">f</span><span class="s1">'Node [graph = </span><span class="si">{</span><span class="n">graph</span><span class="si">}</span><span class="s1">, name = </span><span class="se">\'</span><span class="si">{</span><span class="n">name</span><span class="si">}</span><span class="se">\'</span><span class="s1">] target </span><span class="si">{</span><span class="n">target</span><span class="si">}</span><span class="s1"> has type </span><span class="si">{</span><span class="n">torch</span><span class="o">.</span><span class="n">typename</span><span class="p">(</span><span class="n">target</span><span class="p">)</span><span class="si">}</span><span class="s1"> '</span>
<span class="s1">'but a Callable is expected'</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">target</span><span class="p">,</span> <span class="nb">str</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="sa">f</span><span class="s1">'Node [graph = </span><span class="si">{</span><span class="n">graph</span><span class="si">}</span><span class="s1">, name = </span><span class="se">\'</span><span class="si">{</span><span class="n">name</span><span class="si">}</span><span class="se">\'</span><span class="s1">] target </span><span class="si">{</span><span class="n">target</span><span class="si">}</span><span class="s1"> has type </span><span class="si">{</span><span class="n">torch</span><span class="o">.</span><span class="n">typename</span><span class="p">(</span><span class="n">target</span><span class="p">)</span><span class="si">}</span><span class="s1"> '</span>
<span class="s1">'but a str is expected'</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">target</span> <span class="o">=</span> <span class="n">target</span> <span class="c1"># for method/module/function, the name of the method/module/function/attr</span>
<span class="c1"># being invoked, e.g add, layer1, or torch.add</span>
<span class="c1"># All `Node`-valued inputs. Key is the Node, value is don't-care.</span>
<span class="c1"># The public API for this is `all_input_nodes`, this private attribute</span>
<span class="c1"># should not be accessed directly.</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_input_nodes</span> <span class="p">:</span> <span class="n">Dict</span><span class="p">[</span><span class="n">Node</span><span class="p">,</span> <span class="kc">None</span><span class="p">]</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">__update_args_kwargs</span><span class="p">(</span><span class="n">map_arg</span><span class="p">(</span><span class="n">args</span><span class="p">,</span> <span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">x</span><span class="p">),</span> <span class="n">map_arg</span><span class="p">(</span><span class="n">kwargs</span><span class="p">,</span> <span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">x</span><span class="p">))</span> <span class="c1"># type: ignore[arg-type]</span>
<span class="c1"># All of the nodes that use the value produced by this Node</span>
<span class="c1"># Note one user may correspond to several uses, e.g. the node fo ``x + x``</span>
<span class="c1"># would appear once here, but represents two uses.</span>
<span class="c1">#</span>
<span class="c1"># Is a dict to act as an "ordered set". Keys are significant, value dont-care</span>
<span class="bp">self</span><span class="o">.</span><span class="n">users</span> <span class="p">:</span> <span class="n">Dict</span><span class="p">[</span><span class="s1">'Node'</span><span class="p">,</span> <span class="kc">None</span><span class="p">]</span> <span class="o">=</span> <span class="p">{}</span>
<span class="c1"># Type expression representing the output value of this node.</span>
<span class="c1"># This should contain the same class of Type objects that would appear</span>
<span class="c1"># as type annotations for function inputs/outputs.</span>
<span class="c1">#</span>
<span class="c1"># For placeholder nodes, this value will be used to type-annotate the</span>
<span class="c1"># generated function parameters.</span>
<span class="c1"># For the return node, this value will be used to type-annotate the</span>
<span class="c1"># generated function return type. (Note this is a special case. ``return``</span>
<span class="c1"># does not produce a value, it's more of a notation. Thus, this value</span>
<span class="c1"># describes the type of args[0] in the ``return`` node.</span>
<span class="bp">self</span><span class="o">.</span><span class="n">type</span> <span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Any</span><span class="p">]</span> <span class="o">=</span> <span class="n">return_type</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_prev</span> <span class="o">=</span> <span class="bp">self</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_next</span> <span class="o">=</span> <span class="bp">self</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_erased</span> <span class="o">=</span> <span class="kc">False</span>
<span class="c1"># If set, use this fn to print this node</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_repr_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">Node</span><span class="p">],</span> <span class="nb">str</span><span class="p">]]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="c1"># Dictionary to store metadata passes need to do their</span>
<span class="c1"># transformations. This metadata is preserved across node copies</span>
<span class="bp">self</span><span class="o">.</span><span class="n">meta</span> <span class="p">:</span> <span class="n">Dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">]</span> <span class="o">=</span> <span class="p">{}</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">next</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-></span> <span class="s1">'Node'</span><span class="p">:</span>
<span class="sd">"""</span>
<span class="sd"> Returns the next ``Node`` in the linked list of Nodes.</span>
<span class="sd"> Returns:</span>
<span class="sd"> The next ``Node`` in the linked list of Nodes.</span>
<span class="sd"> """</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_next</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">prev</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-></span> <span class="s1">'Node'</span><span class="p">:</span>
<span class="sd">"""</span>
<span class="sd"> Returns the previous ``Node`` in the linked list of Nodes.</span>
<span class="sd"> Returns:</span>
<span class="sd"> The previous ``Node`` in the linked list of Nodes.</span>
<span class="sd"> """</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_prev</span>
<div class="viewcode-block" id="Node.prepend"><a class="viewcode-back" href="../../../fx.html#torch.fx.Node.prepend">[docs]</a> <span class="nd">@compatibility</span><span class="p">(</span><span class="n">is_backward_compatible</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">prepend</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">:</span> <span class="s1">'Node'</span><span class="p">)</span> <span class="o">-></span> <span class="kc">None</span><span class="p">:</span>
<span class="sd">"""</span>
<span class="sd"> Insert x before this node in the list of nodes in the graph. Example::</span>
<span class="sd"> Before: p -> self</span>
<span class="sd"> bx -> x -> ax</span>
<span class="sd"> After: p -> x -> self</span>
<span class="sd"> bx -> ax</span>
<span class="sd"> Args:</span>
<span class="sd"> x (Node): The node to put before this node. Must be a member of the same graph.</span>
<span class="sd"> """</span>
<span class="k">assert</span> <span class="bp">self</span><span class="o">.</span><span class="n">graph</span> <span class="o">==</span> <span class="n">x</span><span class="o">.</span><span class="n">graph</span><span class="p">,</span> <span class="s2">"Attempting to move a Node into a different Graph"</span>
<span class="k">if</span> <span class="bp">self</span> <span class="o">==</span> <span class="n">x</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">"Trying to prepend a node to itself. This behavior has no effect on the graph."</span><span class="p">)</span>
<span class="k">return</span>
<span class="n">x</span><span class="o">.</span><span class="n">_remove_from_list</span><span class="p">()</span>
<span class="n">p</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_prev</span>
<span class="n">p</span><span class="o">.</span><span class="n">_next</span><span class="p">,</span> <span class="n">x</span><span class="o">.</span><span class="n">_prev</span> <span class="o">=</span> <span class="n">x</span><span class="p">,</span> <span class="n">p</span>
<span class="n">x</span><span class="o">.</span><span class="n">_next</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">_prev</span> <span class="o">=</span> <span class="bp">self</span><span class="p">,</span> <span class="n">x</span></div>
<div class="viewcode-block" id="Node.append"><a class="viewcode-back" href="../../../fx.html#torch.fx.Node.append">[docs]</a> <span class="nd">@compatibility</span><span class="p">(</span><span class="n">is_backward_compatible</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">append</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">:</span> <span class="s1">'Node'</span><span class="p">)</span> <span class="o">-></span> <span class="kc">None</span><span class="p">:</span>
<span class="sd">"""</span>
<span class="sd"> Insert ``x`` after this node in the list of nodes in the graph.</span>
<span class="sd"> Equivalent to ``self.next.prepend(x)``</span>
<span class="sd"> Args:</span>
<span class="sd"> x (Node): The node to put after this node. Must be a member of the same graph.</span>
<span class="sd"> """</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_next</span><span class="o">.</span><span class="n">prepend</span><span class="p">(</span><span class="n">x</span><span class="p">)</span></div>
<span class="k">def</span> <span class="nf">_remove_from_list</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="n">p</span><span class="p">,</span> <span class="n">n</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_prev</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">_next</span>
<span class="n">p</span><span class="o">.</span><span class="n">_next</span><span class="p">,</span> <span class="n">n</span><span class="o">.</span><span class="n">_prev</span> <span class="o">=</span> <span class="n">n</span><span class="p">,</span> <span class="n">p</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">args</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-></span> <span class="n">Tuple</span><span class="p">[</span><span class="n">Argument</span><span class="p">,</span> <span class="o">...</span><span class="p">]:</span>
<span class="sd">"""</span>
<span class="sd"> The tuple of arguments to this ``Node``. The interpretation of arguments</span>
<span class="sd"> depends on the node's opcode. See the :class:`Node` docstring for more</span>
<span class="sd"> information.</span>
<span class="sd"> Assignment to this property is allowed. All accounting of uses and users</span>
<span class="sd"> is updated automatically on assignment.</span>
<span class="sd"> """</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_args</span>
<span class="nd">@args</span><span class="o">.</span><span class="n">setter</span>
<span class="k">def</span> <span class="nf">args</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">a</span> <span class="p">:</span> <span class="n">Tuple</span><span class="p">[</span><span class="n">Argument</span><span class="p">,</span> <span class="o">...</span><span class="p">]):</span>
<span class="sd">"""</span>
<span class="sd"> Set the tuple of arguments to this Node. The interpretation of arguments</span>
<span class="sd"> depends on the node's opcode. See the ``fx.Graph`` docstring for more</span>
<span class="sd"> information.</span>
<span class="sd"> """</span>
<span class="c1"># DO NOT CALL `__update_args_kwargs` directly. The correct way to</span>
<span class="c1"># set `args` is via direct assignment, i.e. `node.args = new_args`</span>
<span class="bp">self</span><span class="o">.</span><span class="n">__update_args_kwargs</span><span class="p">(</span><span class="n">map_arg</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">x</span><span class="p">),</span> <span class="bp">self</span><span class="o">.</span><span class="n">_kwargs</span><span class="p">)</span> <span class="c1"># type: ignore[arg-type]</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">kwargs</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-></span> <span class="n">Dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Argument</span><span class="p">]:</span>
<span class="sd">"""</span>
<span class="sd"> The dict of keyword arguments to this ``Node``. The interpretation of arguments</span>
<span class="sd"> depends on the node's opcode. See the :class:`Node` docstring for more</span>
<span class="sd"> information.</span>
<span class="sd"> Assignment to this property is allowed. All accounting of uses and users</span>
<span class="sd"> is updated automatically on assignment.</span>
<span class="sd"> """</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_kwargs</span>
<span class="nd">@kwargs</span><span class="o">.</span><span class="n">setter</span>
<span class="k">def</span> <span class="nf">kwargs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">k</span> <span class="p">:</span> <span class="n">Dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Argument</span><span class="p">]):</span>
<span class="sd">"""</span>
<span class="sd"> Set the dict of kwargs to this Node. The interpretation of arguments</span>
<span class="sd"> depends on the node's opcode. See the ``fx.Graph`` docstring for more</span>
<span class="sd"> information.</span>
<span class="sd"> """</span>
<span class="c1"># DO NOT CALL `__update_args_kwargs` directly. The correct way to</span>
<span class="c1"># set `args` is via direct assignment, i.e. `node.kwargs = new_kwargs`</span>
<span class="bp">self</span><span class="o">.</span><span class="n">__update_args_kwargs</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_args</span><span class="p">,</span> <span class="n">map_arg</span><span class="p">(</span><span class="n">k</span><span class="p">,</span> <span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">x</span><span class="p">))</span> <span class="c1"># type: ignore[arg-type]</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">all_input_nodes</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-></span> <span class="n">List</span><span class="p">[</span><span class="s1">'Node'</span><span class="p">]:</span>
<span class="sd">"""</span>
<span class="sd"> Return all Nodes that are inputs to this Node. This is equivalent to</span>
<span class="sd"> iterating over ``args`` and ``kwargs`` and only collecting the values that</span>
<span class="sd"> are Nodes.</span>
<span class="sd"> Returns:</span>
<span class="sd"> List of ``Nodes`` that appear in the ``args`` and ``kwargs`` of this</span>
<span class="sd"> ``Node``, in that order.</span>
<span class="sd"> """</span>
<span class="k">return</span> <span class="nb">list</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_input_nodes</span><span class="o">.</span><span class="n">keys</span><span class="p">())</span>
<div class="viewcode-block" id="Node.update_arg"><a class="viewcode-back" href="../../../fx.html#torch.fx.Node.update_arg">[docs]</a> <span class="nd">@compatibility</span><span class="p">(</span><span class="n">is_backward_compatible</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">update_arg</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">idx</span> <span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">arg</span> <span class="p">:</span> <span class="n">Argument</span><span class="p">)</span> <span class="o">-></span> <span class="kc">None</span><span class="p">:</span>
<span class="sd">"""</span>
<span class="sd"> Update an existing positional argument to contain the new value</span>
<span class="sd"> ``arg``. After calling, ``self.args[idx] == arg``.</span>
<span class="sd"> Args:</span>
<span class="sd"> idx (int): The index into ``self.args`` of the element to update</span>
<span class="sd"> arg (Argument): The new argument value to write into ``args``</span>
<span class="sd"> """</span>
<span class="n">args</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">args</span><span class="p">)</span>
<span class="n">args</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span> <span class="o">=</span> <span class="n">arg</span>
<span class="bp">self</span><span class="o">.</span><span class="n">args</span> <span class="o">=</span> <span class="nb">tuple</span><span class="p">(</span><span class="n">args</span><span class="p">)</span></div>
<div class="viewcode-block" id="Node.update_kwarg"><a class="viewcode-back" href="../../../fx.html#torch.fx.Node.update_kwarg">[docs]</a> <span class="nd">@compatibility</span><span class="p">(</span><span class="n">is_backward_compatible</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">update_kwarg</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">key</span> <span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">arg</span> <span class="p">:</span> <span class="n">Argument</span><span class="p">)</span> <span class="o">-></span> <span class="kc">None</span><span class="p">:</span>
<span class="sd">"""</span>
<span class="sd"> Update an existing keyword argument to contain the new value</span>
<span class="sd"> ``arg``. After calling, ``self.kwargs[key] == arg``.</span>
<span class="sd"> Args:</span>
<span class="sd"> key (str): The key in ``self.kwargs`` of the element to update</span>
<span class="sd"> arg (Argument): The new argument value to write into ``kwargs``</span>
<span class="sd"> """</span>
<span class="n">kwargs</span> <span class="o">=</span> <span class="nb">dict</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">kwargs</span><span class="p">)</span>
<span class="n">kwargs</span><span class="p">[</span><span class="n">key</span><span class="p">]</span> <span class="o">=</span> <span class="n">arg</span>
<span class="bp">self</span><span class="o">.</span><span class="n">kwargs</span> <span class="o">=</span> <span class="n">kwargs</span></div>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">stack_trace</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-></span> <span class="n">Optional</span><span class="p">[</span><span class="nb">str</span><span class="p">]:</span>
<span class="sd">"""</span>
<span class="sd"> Return the Python stack trace that was recorded during tracing, if any.</span>
<span class="sd"> This property is usually populated by `Tracer.create_proxy`. To record</span>
<span class="sd"> stack traces during tracing for debug purposes, set</span>
<span class="sd"> `record_stack_traces = True` on the `Tracer` instance.</span>
<span class="sd"> """</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">meta</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"stack_trace"</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
<span class="nd">@stack_trace</span><span class="o">.</span><span class="n">setter</span>
<span class="k">def</span> <span class="nf">stack_trace</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">trace</span> <span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">str</span><span class="p">]):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">meta</span><span class="p">[</span><span class="s2">"stack_trace"</span><span class="p">]</span> <span class="o">=</span> <span class="n">trace</span>
<span class="k">def</span> <span class="nf">__update_args_kwargs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">new_args</span> <span class="p">:</span> <span class="n">Tuple</span><span class="p">[</span><span class="s1">'Argument'</span><span class="p">,</span> <span class="o">...</span><span class="p">],</span> <span class="n">new_kwargs</span> <span class="p">:</span> <span class="n">Dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="s1">'Argument'</span><span class="p">]):</span>
<span class="sd">"""</span>
<span class="sd"> This API is internal. Do *not* call it directly.</span>
<span class="sd"> """</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_args</span> <span class="o">=</span> <span class="n">new_args</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_kwargs</span> <span class="o">=</span> <span class="n">new_kwargs</span>
<span class="k">for</span> <span class="n">old_use</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">_input_nodes</span><span class="o">.</span><span class="n">keys</span><span class="p">():</span>
<span class="n">old_use</span><span class="o">.</span><span class="n">users</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_input_nodes</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">map_arg</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_args</span><span class="p">,</span> <span class="k">lambda</span> <span class="n">n</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">_input_nodes</span><span class="o">.</span><span class="n">setdefault</span><span class="p">(</span><span class="n">n</span><span class="p">))</span>
<span class="n">map_arg</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_kwargs</span><span class="p">,</span> <span class="k">lambda</span> <span class="n">n</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">_input_nodes</span><span class="o">.</span><span class="n">setdefault</span><span class="p">(</span><span class="n">n</span><span class="p">))</span>
<span class="k">for</span> <span class="n">new_use</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">_input_nodes</span><span class="o">.</span><span class="n">keys</span><span class="p">():</span>
<span class="n">new_use</span><span class="o">.</span><span class="n">users</span><span class="o">.</span><span class="n">setdefault</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span>
<span class="k">def</span> <span class="fm">__repr__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-></span> <span class="nb">str</span><span class="p">:</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_repr_fn</span><span class="p">:</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_repr_fn</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="o">.</span><span class="n">name</span>
<span class="k">def</span> <span class="nf">_pretty_print_target</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">target</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Make target printouts more user-friendly.</span>
<span class="sd"> 1) builtins will be printed as `builtins.xyz`</span>
<span class="sd"> 2) operators will be printed as `operator.xyz`</span>
<span class="sd"> 3) other callables will be printed with qualfied name, e.g. torch.add</span>
<span class="sd"> """</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">target</span><span class="p">,</span> <span class="nb">str</span><span class="p">):</span>
<span class="k">return</span> <span class="n">target</span>
<span class="k">if</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">target</span><span class="p">,</span> <span class="s1">'__module__'</span><span class="p">):</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">target</span><span class="p">,</span> <span class="s1">'__name__'</span><span class="p">):</span>
<span class="c1"># Just to be defensive, if we don't have `__name__`, get the</span>
<span class="c1"># qualname. Not sure if this happens for any members of `operator`</span>
<span class="c1"># or `builtins`. This fallback path is not as good, since e.g.</span>
<span class="c1"># things in `operator` have `_operator` as their __module__.</span>
<span class="k">return</span> <span class="n">_get_qualified_name</span><span class="p">(</span><span class="n">target</span><span class="p">)</span>
<span class="k">if</span> <span class="n">target</span><span class="o">.</span><span class="vm">__module__</span> <span class="o">==</span> <span class="s1">'builtins'</span><span class="p">:</span>
<span class="k">return</span> <span class="sa">f</span><span class="s1">'builtins.</span><span class="si">{</span><span class="n">target</span><span class="o">.</span><span class="vm">__name__</span><span class="si">}</span><span class="s1">'</span>
<span class="k">elif</span> <span class="n">target</span><span class="o">.</span><span class="vm">__module__</span> <span class="o">==</span> <span class="s1">'_operator'</span><span class="p">:</span>
<span class="k">return</span> <span class="sa">f</span><span class="s1">'operator.</span><span class="si">{</span><span class="n">target</span><span class="o">.</span><span class="vm">__name__</span><span class="si">}</span><span class="s1">'</span>
<span class="k">return</span> <span class="n">_get_qualified_name</span><span class="p">(</span><span class="n">target</span><span class="p">)</span>
<div class="viewcode-block" id="Node.format_node"><a class="viewcode-back" href="../../../fx.html#torch.fx.Node.format_node">[docs]</a> <span class="nd">@compatibility</span><span class="p">(</span><span class="n">is_backward_compatible</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">format_node</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span>
<span class="n">placeholder_names</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">List</span><span class="p">[</span><span class="nb">str</span><span class="p">]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
<span class="n">maybe_return_typename</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">List</span><span class="p">[</span><span class="nb">str</span><span class="p">]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">)</span> <span class="o">-></span> <span class="n">Optional</span><span class="p">[</span><span class="nb">str</span><span class="p">]:</span>
<span class="sd">"""</span>
<span class="sd"> Return a descriptive string representation of ``self``.</span>
<span class="sd"> This method can be used with no arguments as a debugging</span>
<span class="sd"> utility.</span>
<span class="sd"> This function is also used internally in the ``__str__`` method</span>
<span class="sd"> of ``Graph``. Together, the strings in ``placeholder_names``</span>
<span class="sd"> and ``maybe_return_typename`` make up the signature of the</span>
<span class="sd"> autogenerated ``forward`` function in this Graph's surrounding</span>
<span class="sd"> GraphModule. ``placeholder_names`` and ``maybe_return_typename``</span>
<span class="sd"> should not be used otherwise.</span>
<span class="sd"> Args:</span>
<span class="sd"> placeholder_names: A list that will store formatted strings</span>
<span class="sd"> representing the placeholders in the generated</span>
<span class="sd"> ``forward`` function. Internal use only.</span>
<span class="sd"> maybe_return_typename: A single-element list that will store</span>
<span class="sd"> a formatted string representing the output of the</span>
<span class="sd"> generated ``forward`` function. Internal use only.</span>
<span class="sd"> Returns:</span>
<span class="sd"> str: If 1) we're using ``format_node`` as an internal helper</span>
<span class="sd"> in the ``__str__`` method of ``Graph``, and 2) ``self``</span>
<span class="sd"> is a placeholder Node, return ``None``. Otherwise,</span>
<span class="sd"> return a descriptive string representation of the</span>
<span class="sd"> current Node.</span>
<span class="sd"> """</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">op</span> <span class="o">==</span> <span class="s1">'placeholder'</span><span class="p">:</span>
<span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">target</span><span class="p">,</span> <span class="nb">str</span><span class="p">)</span>
<span class="n">arg_str</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">target</span>
<span class="n">arg_str</span> <span class="o">+=</span> <span class="n">arg_str</span> <span class="o">+</span> <span class="sa">f</span><span class="s1">': </span><span class="si">{</span><span class="n">_type_repr</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">type</span><span class="p">)</span><span class="si">}</span><span class="s1">'</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">type</span> <span class="k">else</span> <span class="s1">''</span>
<span class="k">if</span> <span class="n">placeholder_names</span><span class="p">:</span>
<span class="n">placeholder_names</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">arg_str</span><span class="p">)</span>
<span class="k">return</span> <span class="kc">None</span>
<span class="n">maybe_typename</span> <span class="o">=</span> <span class="sa">f</span><span class="s1">'</span><span class="si">{</span><span class="n">_type_repr</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">type</span><span class="p">)</span><span class="si">}</span><span class="s1"> '</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">type</span> <span class="k">else</span> <span class="s1">''</span>
<span class="n">default_val</span> <span class="o">=</span> <span class="s1">'(default='</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">args</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span> <span class="o">+</span> <span class="s1">')'</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">args</span> <span class="k">else</span> <span class="s1">''</span>
<span class="k">return</span> <span class="sa">f</span><span class="s1">'%</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">name</span><span class="si">}</span><span class="s1"> : </span><span class="si">{</span><span class="n">maybe_typename</span><span class="si">}</span><span class="s1">[#users=</span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">users</span><span class="p">)</span><span class="si">}</span><span class="s1">] = </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">op</span><span class="si">}</span><span class="s1">[target=</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">target</span><span class="si">}</span><span class="s1">]</span><span class="si">{</span><span class="n">default_val</span><span class="si">}</span><span class="s1">'</span>
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">op</span> <span class="o">==</span> <span class="s1">'get_attr'</span><span class="p">:</span>
<span class="n">maybe_typename</span> <span class="o">=</span> <span class="sa">f</span><span class="s1">'</span><span class="si">{</span><span class="n">_type_repr</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">type</span><span class="p">)</span><span class="si">}</span><span class="s1"> '</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">type</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span> <span class="k">else</span> <span class="s1">''</span>
<span class="k">return</span> <span class="sa">f</span><span class="s1">'%</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">name</span><span class="si">}</span><span class="s1"> : </span><span class="si">{</span><span class="n">maybe_typename</span><span class="si">}</span><span class="s1">[#users=</span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">users</span><span class="p">)</span><span class="si">}</span><span class="s1">] = '</span> \
<span class="sa">f</span><span class="s1">'</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">op</span><span class="si">}</span><span class="s1">[target=</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">_pretty_print_target</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">target</span><span class="p">)</span><span class="si">}</span><span class="s1">]'</span>
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">op</span> <span class="o">==</span> <span class="s1">'output'</span><span class="p">:</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">type</span> <span class="ow">and</span> <span class="n">maybe_return_typename</span><span class="p">:</span>
<span class="n">maybe_return_typename</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="sa">f</span><span class="s1">' -> </span><span class="si">{</span><span class="n">_type_repr</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">type</span><span class="p">)</span><span class="si">}</span><span class="s1">'</span>
<span class="k">return</span> <span class="sa">f</span><span class="s1">'return </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">args</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">}</span><span class="s1">'</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">maybe_typename</span> <span class="o">=</span> <span class="sa">f</span><span class="s1">'</span><span class="si">{</span><span class="n">_type_repr</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">type</span><span class="p">)</span><span class="si">}</span><span class="s1"> '</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">type</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span> <span class="k">else</span> <span class="s1">''</span>
<span class="k">return</span> <span class="sa">f</span><span class="s1">'%</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">name</span><span class="si">}</span><span class="s1"> : </span><span class="si">{</span><span class="n">maybe_typename</span><span class="si">}</span><span class="s1">[#users=</span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">users</span><span class="p">)</span><span class="si">}</span><span class="s1">] = '</span> \
<span class="sa">f</span><span class="s1">'</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">op</span><span class="si">}</span><span class="s1">[target=</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">_pretty_print_target</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">target</span><span class="p">)</span><span class="si">}</span><span class="s1">]('</span> \
<span class="sa">f</span><span class="s1">'args = </span><span class="si">{</span><span class="n">_format_arg</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">args</span><span class="p">)</span><span class="si">}</span><span class="s1">, kwargs = </span><span class="si">{</span><span class="n">_format_arg</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">kwargs</span><span class="p">)</span><span class="si">}</span><span class="s1">)'</span></div>
<div class="viewcode-block" id="Node.replace_all_uses_with"><a class="viewcode-back" href="../../../fx.html#torch.fx.Node.replace_all_uses_with">[docs]</a> <span class="nd">@compatibility</span><span class="p">(</span><span class="n">is_backward_compatible</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">replace_all_uses_with</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span>
<span class="n">replace_with</span> <span class="p">:</span> <span class="s1">'Node'</span><span class="p">,</span>
<span class="n">delete_user_cb</span><span class="p">:</span> <span class="n">Callable</span><span class="p">[[</span><span class="s1">'Node'</span><span class="p">],</span> <span class="nb">bool</span><span class="p">]</span> <span class="o">=</span> <span class="k">lambda</span> <span class="n">user</span><span class="p">:</span> <span class="kc">True</span><span class="p">,</span>
<span class="o">*</span><span class="p">,</span>
<span class="n">propagate_meta</span><span class="o">=</span><span class="kc">False</span>
<span class="p">)</span> <span class="o">-></span> <span class="n">List</span><span class="p">[</span><span class="s1">'Node'</span><span class="p">]:</span>
<span class="sd">"""</span>
<span class="sd"> Replace all uses of ``self`` in the Graph with the Node ``replace_with``.</span>
<span class="sd"> Args:</span>
<span class="sd"> replace_with (Node): The node to replace all uses of ``self`` with.</span>
<span class="sd"> delete_user_cb (Callable): Callback that is called to determine</span>
<span class="sd"> whether a given user of the self node should be removed.</span>
<span class="sd"> propagate_meta (bool): Whether or not to copy all properties</span>
<span class="sd"> on the .meta field of the original node onto the replacement node.</span>
<span class="sd"> For safety, this is only valid to do if the replacement node</span>
<span class="sd"> doesn't already have an existing .meta field.</span>
<span class="sd"> Returns:</span>
<span class="sd"> The list of Nodes on which this change was made.</span>
<span class="sd"> """</span>
<span class="k">if</span> <span class="n">propagate_meta</span><span class="p">:</span>
<span class="k">assert</span> <span class="nb">len</span><span class="p">(</span><span class="n">replace_with</span><span class="o">.</span><span class="n">meta</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">,</span> \
<span class="s1">'Called node.replace_all_uses_with(replace_with, propagate_meta=True), '</span> \
<span class="s1">'but replace_with already has .meta keys'</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="bp">self</span><span class="o">.</span><span class="n">meta</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
<span class="n">replace_with</span><span class="o">.</span><span class="n">meta</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">=</span> <span class="n">v</span>
<span class="n">to_process</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">users</span><span class="p">)</span>
<span class="n">skipped</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">use_node</span> <span class="ow">in</span> <span class="n">to_process</span><span class="p">:</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">delete_user_cb</span><span class="p">(</span><span class="n">use_node</span><span class="p">):</span>
<span class="n">skipped</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">use_node</span><span class="p">)</span>
<span class="k">continue</span>
<span class="k">def</span> <span class="nf">maybe_replace_node</span><span class="p">(</span><span class="n">n</span> <span class="p">:</span> <span class="n">Node</span><span class="p">)</span> <span class="o">-></span> <span class="n">Node</span><span class="p">:</span>
<span class="k">if</span> <span class="n">n</span> <span class="o">==</span> <span class="bp">self</span><span class="p">:</span>
<span class="k">return</span> <span class="n">replace_with</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">n</span>
<span class="n">new_args</span> <span class="o">=</span> <span class="n">map_arg</span><span class="p">(</span><span class="n">use_node</span><span class="o">.</span><span class="n">args</span><span class="p">,</span> <span class="n">maybe_replace_node</span><span class="p">)</span>
<span class="n">new_kwargs</span> <span class="o">=</span> <span class="n">map_arg</span><span class="p">(</span><span class="n">use_node</span><span class="o">.</span><span class="n">kwargs</span><span class="p">,</span> <span class="n">maybe_replace_node</span><span class="p">)</span>
<span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">new_args</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">)</span>
<span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">new_kwargs</span><span class="p">,</span> <span class="nb">dict</span><span class="p">)</span>
<span class="n">use_node</span><span class="o">.</span><span class="n">__update_args_kwargs</span><span class="p">(</span><span class="n">new_args</span><span class="p">,</span> <span class="n">new_kwargs</span><span class="p">)</span>
<span class="k">assert</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">users</span><span class="p">)</span> <span class="o">-</span> <span class="nb">len</span><span class="p">(</span><span class="n">skipped</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span>
<span class="k">return</span> <span class="p">[</span><span class="n">n</span> <span class="k">for</span> <span class="n">n</span> <span class="ow">in</span> <span class="n">to_process</span> <span class="k">if</span> <span class="n">n</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">skipped</span><span class="p">]</span></div>
<div class="viewcode-block" id="Node.is_impure"><a class="viewcode-back" href="../../../fx.html#torch.fx.Node.is_impure">[docs]</a> <span class="nd">@compatibility</span><span class="p">(</span><span class="n">is_backward_compatible</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">is_impure</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Returns whether this op is impure, i.e. if its op is a placeholder or</span>
<span class="sd"> output, or if a call_function or call_module which is impure.</span>
<span class="sd"> Returns:</span>
<span class="sd"> bool: If the op is impure or not.</span>
<span class="sd"> """</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">op</span> <span class="ow">in</span> <span class="p">{</span><span class="s2">"placeholder"</span><span class="p">,</span> <span class="s2">"output"</span><span class="p">}:</span>
<span class="k">return</span> <span class="kc">True</span>
<span class="c1"># Check if an impure function.</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">op</span> <span class="o">==</span> <span class="s2">"call_function"</span><span class="p">:</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">target</span> <span class="ow">in</span> <span class="n">_side_effectful_functions</span>