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‎docs/master/__config__.html

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<span class="k">return</span> <span class="n">module</span> <span class="o">+</span> <span class="n">class_name</span>
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<div class="viewcode-block" id="is_tensor"><a class="viewcode-back" href="../generated/torch.is_tensor.html#torch.is_tensor">[docs]</a><span class="k">def</span> <span class="nf">is_tensor</span><span class="p">(</span><span class="n">obj</span><span class="p">):</span>
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<span class="k">def</span> <span class="nf">is_tensor</span><span class="p">(</span><span class="n">obj</span><span class="p">):</span>
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<span class="sa">r</span><span class="sd">&quot;&quot;&quot;Returns True if `obj` is a PyTorch tensor.</span>
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<span class="sd"> Note that this function is simply doing ``isinstance(obj, Tensor)``.</span>
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<span class="sd"> True</span>
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<span class="sd"> &quot;&quot;&quot;</span>
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<span class="k">return</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">obj</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">)</span></div>
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<span class="k">return</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">obj</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">)</span>
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<div class="viewcode-block" id="is_storage"><a class="viewcode-back" href="../generated/torch.is_storage.html#torch.is_storage">[docs]</a><span class="k">def</span> <span class="nf">is_storage</span><span class="p">(</span><span class="n">obj</span><span class="p">):</span>
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<span class="sa">r</span><span class="sd">&quot;&quot;&quot;Returns True if `obj` is a PyTorch storage object.</span>
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<span class="sd"> Args:</span>
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<span class="sd"> obj (Object): Object to test</span>
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<span class="sd"> &quot;&quot;&quot;</span>
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<span class="n">_C</span><span class="o">.</span><span class="n">_set_warnAlways</span><span class="p">(</span><span class="n">b</span><span class="p">)</span>
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<span class="k">def</span> <span class="nf">is_warn_always_enabled</span><span class="p">():</span>
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<span class="sa">r</span><span class="sd">&quot;&quot;&quot;Returns True if the global warn_always flag is turned on. Refer to</span>
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<span class="sd"> :func:`torch.set_warn_always` documentation for more details.</span>
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<span class="c1">################################################################################</span>
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<span class="c1"># Define numeric constants</span>

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<span class="sd">&quot;&quot;&quot;</span>
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<span class="n">fn</span><span class="o">.</span><span class="n">_torchscript_modifier</span> <span class="o">=</span> <span class="n">FunctionModifiers</span><span class="o">.</span><span class="n">UNUSED</span>
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<span class="c1"># No op context manager from python side</span>
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<span class="k">def</span> <span class="fm">__exit__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">exc_type</span><span class="p">:</span> <span class="n">Any</span><span class="p">,</span> <span class="n">exc_value</span><span class="p">:</span> <span class="n">Any</span><span class="p">,</span> <span class="n">traceback</span><span class="p">:</span> <span class="n">Any</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
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<span class="sd"> This decorator indicates to the compiler that a function or method should</span>
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<span class="k">else</span><span class="p">:</span>
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<span class="n">fn</span><span class="o">.</span><span class="n">_torchscript_modifier</span> <span class="o">=</span> <span class="n">FunctionModifiers</span><span class="o">.</span><span class="n">IGNORE</span>
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<span class="n">new_tensor</span><span class="o">.</span><span class="n">set_</span><span class="p">(</span><span class="n">new_storage</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">storage_offset</span><span class="p">(),</span> <span class="bp">self</span><span class="o">.</span><span class="n">size</span><span class="p">(),</span> <span class="bp">self</span><span class="o">.</span><span class="n">stride</span><span class="p">())</span>
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<span class="n">new_tensor</span> <span class="o">=</span> <span class="n">new_tensor</span><span class="o">.</span><span class="n">conj_physical</span><span class="p">()</span>
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<span class="n">new_tensor</span><span class="o">.</span><span class="n">requires_grad</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">requires_grad</span>
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<span class="n">new_tensor</span><span class="o">.</span><span class="n">grad</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">grad</span><span class="o">.</span><span class="n">__deepcopy__</span><span class="p">(</span><span class="n">memo</span><span class="p">)</span>

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<span class="bp">self</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">rename</span><span class="p">(</span><span class="kc">None</span><span class="p">)</span>
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<span class="n">summarize</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">numel</span><span class="p">()</span> <span class="o">&gt;</span> <span class="n">PRINT_OPTS</span><span class="o">.</span><span class="n">threshold</span>
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<span class="bp">self</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">resolve_neg</span><span class="p">()</span>
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<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">dtype</span> <span class="ow">is</span> <span class="n">torch</span><span class="o">.</span><span class="n">float16</span> <span class="ow">or</span> <span class="bp">self</span><span class="o">.</span><span class="n">dtype</span> <span class="ow">is</span> <span class="n">torch</span><span class="o">.</span><span class="n">bfloat16</span><span class="p">:</span>
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