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<h1>Source code for torch.cuda.random</h1><div class="highlight"><pre>
<span></span><span class="kn">import</span> <span class="nn">torch</span>
<span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">cast</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">Union</span>
<span class="kn">from</span> <span class="nn">.</span> <span class="kn">import</span> <span class="n">_lazy_init</span><span class="p">,</span> <span class="n">_lazy_call</span><span class="p">,</span> <span class="n">device_count</span><span class="p">,</span> <span class="n">current_device</span>
<span class="kn">from</span> <span class="nn">..</span> <span class="kn">import</span> <span class="n">Tensor</span>
<span class="n">__all__</span> <span class="o">=</span> <span class="p">[</span><span class="s1">'get_rng_state'</span><span class="p">,</span> <span class="s1">'get_rng_state_all'</span><span class="p">,</span>
<span class="s1">'set_rng_state'</span><span class="p">,</span> <span class="s1">'set_rng_state_all'</span><span class="p">,</span>
<span class="s1">'manual_seed'</span><span class="p">,</span> <span class="s1">'manual_seed_all'</span><span class="p">,</span>
<span class="s1">'seed'</span><span class="p">,</span> <span class="s1">'seed_all'</span><span class="p">,</span> <span class="s1">'initial_seed'</span><span class="p">]</span>
<div class="viewcode-block" id="get_rng_state"><a class="viewcode-back" href="../../../generated/torch.cuda.get_rng_state.html#torch.cuda.get_rng_state">[docs]</a><span class="k">def</span> <span class="nf">get_rng_state</span><span class="p">(</span><span class="n">device</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="nb">str</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="o">=</span> <span class="s1">'cuda'</span><span class="p">)</span> <span class="o">-></span> <span class="n">Tensor</span><span class="p">:</span>
<span class="sa">r</span><span class="sd">"""Returns the random number generator state of the specified GPU as a ByteTensor.</span>
<span class="sd"> Args:</span>
<span class="sd"> device (torch.device or int, optional): The device to return the RNG state of.</span>
<span class="sd"> Default: ``'cuda'`` (i.e., ``torch.device('cuda')``, the current CUDA device).</span>
<span class="sd"> .. warning::</span>
<span class="sd"> This function eagerly initializes CUDA.</span>
<span class="sd"> """</span>
<span class="n">_lazy_init</span><span class="p">()</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">device</span><span class="p">,</span> <span class="nb">str</span><span class="p">):</span>
<span class="n">device</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">device</span><span class="p">(</span><span class="n">device</span><span class="p">)</span>
<span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">device</span><span class="p">,</span> <span class="nb">int</span><span class="p">):</span>
<span class="n">device</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">device</span><span class="p">(</span><span class="s1">'cuda'</span><span class="p">,</span> <span class="n">device</span><span class="p">)</span>
<span class="n">idx</span> <span class="o">=</span> <span class="n">device</span><span class="o">.</span><span class="n">index</span>
<span class="k">if</span> <span class="n">idx</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">idx</span> <span class="o">=</span> <span class="n">current_device</span><span class="p">()</span>
<span class="n">default_generator</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">default_generators</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span>
<span class="k">return</span> <span class="n">default_generator</span><span class="o">.</span><span class="n">get_state</span><span class="p">()</span></div>
<div class="viewcode-block" id="get_rng_state_all"><a class="viewcode-back" href="../../../generated/torch.cuda.get_rng_state_all.html#torch.cuda.get_rng_state_all">[docs]</a><span class="k">def</span> <span class="nf">get_rng_state_all</span><span class="p">()</span> <span class="o">-></span> <span class="n">List</span><span class="p">[</span><span class="n">Tensor</span><span class="p">]:</span>
<span class="sa">r</span><span class="sd">"""Returns a list of ByteTensor representing the random number states of all devices."""</span>
<span class="n">results</span> <span class="o">=</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">device_count</span><span class="p">()):</span>
<span class="n">results</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">get_rng_state</span><span class="p">(</span><span class="n">i</span><span class="p">))</span>
<span class="k">return</span> <span class="n">results</span></div>
<div class="viewcode-block" id="set_rng_state"><a class="viewcode-back" href="../../../generated/torch.cuda.set_rng_state.html#torch.cuda.set_rng_state">[docs]</a><span class="k">def</span> <span class="nf">set_rng_state</span><span class="p">(</span><span class="n">new_state</span><span class="p">:</span> <span class="n">Tensor</span><span class="p">,</span> <span class="n">device</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="nb">str</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="o">=</span> <span class="s1">'cuda'</span><span class="p">)</span> <span class="o">-></span> <span class="kc">None</span><span class="p">:</span>
<span class="sa">r</span><span class="sd">"""Sets the random number generator state of the specified GPU.</span>
<span class="sd"> Args:</span>
<span class="sd"> new_state (torch.ByteTensor): The desired state</span>
<span class="sd"> device (torch.device or int, optional): The device to set the RNG state.</span>
<span class="sd"> Default: ``'cuda'`` (i.e., ``torch.device('cuda')``, the current CUDA device).</span>
<span class="sd"> """</span>
<span class="n">new_state_copy</span> <span class="o">=</span> <span class="n">new_state</span><span class="o">.</span><span class="n">clone</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="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">device</span><span class="p">,</span> <span class="nb">str</span><span class="p">):</span>
<span class="n">device</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">device</span><span class="p">(</span><span class="n">device</span><span class="p">)</span>
<span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">device</span><span class="p">,</span> <span class="nb">int</span><span class="p">):</span>
<span class="n">device</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">device</span><span class="p">(</span><span class="s1">'cuda'</span><span class="p">,</span> <span class="n">device</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">cb</span><span class="p">():</span>
<span class="n">idx</span> <span class="o">=</span> <span class="n">cast</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">device</span><span class="p">)</span><span class="o">.</span><span class="n">index</span>
<span class="k">if</span> <span class="n">idx</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">idx</span> <span class="o">=</span> <span class="n">current_device</span><span class="p">()</span>
<span class="n">default_generator</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">default_generators</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span>
<span class="n">default_generator</span><span class="o">.</span><span class="n">set_state</span><span class="p">(</span><span class="n">new_state_copy</span><span class="p">)</span>
<span class="n">_lazy_call</span><span class="p">(</span><span class="n">cb</span><span class="p">)</span></div>
<div class="viewcode-block" id="set_rng_state_all"><a class="viewcode-back" href="../../../generated/torch.cuda.set_rng_state_all.html#torch.cuda.set_rng_state_all">[docs]</a><span class="k">def</span> <span class="nf">set_rng_state_all</span><span class="p">(</span><span class="n">new_states</span><span class="p">:</span> <span class="n">Iterable</span><span class="p">[</span><span class="n">Tensor</span><span class="p">])</span> <span class="o">-></span> <span class="kc">None</span><span class="p">:</span>
<span class="sa">r</span><span class="sd">"""Sets the random number generator state of all devices.</span>
<span class="sd"> Args:</span>
<span class="sd"> new_states (Iterable of torch.ByteTensor): The desired state for each device"""</span>
<span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">state</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">new_states</span><span class="p">):</span>
<span class="n">set_rng_state</span><span class="p">(</span><span class="n">state</span><span class="p">,</span> <span class="n">i</span><span class="p">)</span></div>
<div class="viewcode-block" id="manual_seed"><a class="viewcode-back" href="../../../generated/torch.cuda.manual_seed.html#torch.cuda.manual_seed">[docs]</a><span class="k">def</span> <span class="nf">manual_seed</span><span class="p">(</span><span class="n">seed</span><span class="p">:</span> <span class="nb">int</span><span class="p">)</span> <span class="o">-></span> <span class="kc">None</span><span class="p">:</span>
<span class="sa">r</span><span class="sd">"""Sets the seed for generating random numbers for the current GPU.</span>
<span class="sd"> It's safe to call this function if CUDA is not available; in that</span>
<span class="sd"> case, it is silently ignored.</span>
<span class="sd"> Args:</span>
<span class="sd"> seed (int): The desired seed.</span>
<span class="sd"> .. warning::</span>
<span class="sd"> If you are working with a multi-GPU model, this function is insufficient</span>
<span class="sd"> to get determinism. To seed all GPUs, use :func:`manual_seed_all`.</span>
<span class="sd"> """</span>
<span class="n">seed</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">seed</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">cb</span><span class="p">():</span>
<span class="n">idx</span> <span class="o">=</span> <span class="n">current_device</span><span class="p">()</span>
<span class="n">default_generator</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">default_generators</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span>
<span class="n">default_generator</span><span class="o">.</span><span class="n">manual_seed</span><span class="p">(</span><span class="n">seed</span><span class="p">)</span>
<span class="n">_lazy_call</span><span class="p">(</span><span class="n">cb</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span></div>
<div class="viewcode-block" id="manual_seed_all"><a class="viewcode-back" href="../../../generated/torch.cuda.manual_seed_all.html#torch.cuda.manual_seed_all">[docs]</a><span class="k">def</span> <span class="nf">manual_seed_all</span><span class="p">(</span><span class="n">seed</span><span class="p">:</span> <span class="nb">int</span><span class="p">)</span> <span class="o">-></span> <span class="kc">None</span><span class="p">:</span>
<span class="sa">r</span><span class="sd">"""Sets the seed for generating random numbers on all GPUs.</span>
<span class="sd"> It's safe to call this function if CUDA is not available; in that</span>
<span class="sd"> case, it is silently ignored.</span>
<span class="sd"> Args:</span>
<span class="sd"> seed (int): The desired seed.</span>
<span class="sd"> """</span>
<span class="n">seed</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">seed</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">cb</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">device_count</span><span class="p">()):</span>
<span class="n">default_generator</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">default_generators</span><span class="p">[</span><span class="n">i</span><span class="p">]</span>
<span class="n">default_generator</span><span class="o">.</span><span class="n">manual_seed</span><span class="p">(</span><span class="n">seed</span><span class="p">)</span>
<span class="n">_lazy_call</span><span class="p">(</span><span class="n">cb</span><span class="p">,</span> <span class="n">seed_all</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span></div>
<div class="viewcode-block" id="seed"><a class="viewcode-back" href="../../../generated/torch.cuda.seed.html#torch.cuda.seed">[docs]</a><span class="k">def</span> <span class="nf">seed</span><span class="p">()</span> <span class="o">-></span> <span class="kc">None</span><span class="p">:</span>
<span class="sa">r</span><span class="sd">"""Sets the seed for generating random numbers to a random number for the current GPU.</span>
<span class="sd"> It's safe to call this function if CUDA is not available; in that</span>
<span class="sd"> case, it is silently ignored.</span>
<span class="sd"> .. warning::</span>
<span class="sd"> If you are working with a multi-GPU model, this function will only initialize</span>
<span class="sd"> the seed on one GPU. To initialize all GPUs, use :func:`seed_all`.</span>
<span class="sd"> """</span>
<span class="k">def</span> <span class="nf">cb</span><span class="p">():</span>
<span class="n">idx</span> <span class="o">=</span> <span class="n">current_device</span><span class="p">()</span>
<span class="n">default_generator</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">default_generators</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span>
<span class="n">default_generator</span><span class="o">.</span><span class="n">seed</span><span class="p">()</span>
<span class="n">_lazy_call</span><span class="p">(</span><span class="n">cb</span><span class="p">)</span></div>
<div class="viewcode-block" id="seed_all"><a class="viewcode-back" href="../../../generated/torch.cuda.seed_all.html#torch.cuda.seed_all">[docs]</a><span class="k">def</span> <span class="nf">seed_all</span><span class="p">()</span> <span class="o">-></span> <span class="kc">None</span><span class="p">:</span>
<span class="sa">r</span><span class="sd">"""Sets the seed for generating random numbers to a random number on all GPUs.</span>
<span class="sd"> It's safe to call this function if CUDA is not available; in that</span>
<span class="sd"> case, it is silently ignored.</span>
<span class="sd"> """</span>
<span class="k">def</span> <span class="nf">cb</span><span class="p">():</span>
<span class="n">random_seed</span> <span class="o">=</span> <span class="mi">0</span>
<span class="n">seeded</span> <span class="o">=</span> <span class="kc">False</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">device_count</span><span class="p">()):</span>
<span class="n">default_generator</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">default_generators</span><span class="p">[</span><span class="n">i</span><span class="p">]</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">seeded</span><span class="p">:</span>
<span class="n">default_generator</span><span class="o">.</span><span class="n">seed</span><span class="p">()</span>
<span class="n">random_seed</span> <span class="o">=</span> <span class="n">default_generator</span><span class="o">.</span><span class="n">initial_seed</span><span class="p">()</span>
<span class="n">seeded</span> <span class="o">=</span> <span class="kc">True</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">default_generator</span><span class="o">.</span><span class="n">manual_seed</span><span class="p">(</span><span class="n">random_seed</span><span class="p">)</span>
<span class="n">_lazy_call</span><span class="p">(</span><span class="n">cb</span><span class="p">)</span></div>
<div class="viewcode-block" id="initial_seed"><a class="viewcode-back" href="../../../generated/torch.cuda.initial_seed.html#torch.cuda.initial_seed">[docs]</a><span class="k">def</span> <span class="nf">initial_seed</span><span class="p">()</span> <span class="o">-></span> <span class="nb">int</span><span class="p">:</span>
<span class="sa">r</span><span class="sd">"""Returns the current random seed of the current GPU.</span>
<span class="sd"> .. warning::</span>
<span class="sd"> This function eagerly initializes CUDA.</span>
<span class="sd"> """</span>
<span class="n">_lazy_init</span><span class="p">()</span>
<span class="n">idx</span> <span class="o">=</span> <span class="n">current_device</span><span class="p">()</span>
<span class="n">default_generator</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">default_generators</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span>
<span class="k">return</span> <span class="n">default_generator</span><span class="o">.</span><span class="n">initial_seed</span><span class="p">()</span></div>
</pre></div>
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