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@@ -472,6 +472,7 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
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<span class="sd">on an NVIDIA GPU with compute capability &gt;= 3.0.</span>
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<span class="sd">&quot;&quot;&quot;</span>
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<span class="kn">import</span> <span class="nn">math</span>
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<span class="kn">import</span> <span class="nn">os</span>
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<span class="kn">import</span> <span class="nn">sys</span>
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<span class="kn">import</span> <span class="nn">platform</span>
@@ -511,7 +512,7 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
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<span class="s1">&#39;set_deterministic_debug_mode&#39;</span><span class="p">,</span> <span class="s1">&#39;get_deterministic_debug_mode&#39;</span><span class="p">,</span>
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<span class="s1">&#39;set_float32_matmul_precision&#39;</span><span class="p">,</span> <span class="s1">&#39;get_float32_matmul_precision&#39;</span><span class="p">,</span>
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<span class="s1">&#39;set_warn_always&#39;</span><span class="p">,</span> <span class="s1">&#39;is_warn_always_enabled&#39;</span><span class="p">,</span> <span class="s1">&#39;SymInt&#39;</span><span class="p">,</span> <span class="s1">&#39;SymFloat&#39;</span><span class="p">,</span>
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<span class="s1">&#39;compile&#39;</span><span class="p">,</span> <span class="s1">&#39;vmap&#39;</span><span class="p">,</span>
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<span class="s1">&#39;sym_int&#39;</span><span class="p">,</span> <span class="s1">&#39;sym_float&#39;</span><span class="p">,</span> <span class="s1">&#39;compile&#39;</span><span class="p">,</span> <span class="s1">&#39;vmap&#39;</span>
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<span class="p">]</span>
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<span class="c1">################################################################################</span>
@@ -772,6 +773,39 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
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<span class="k">def</span> <span class="nf">get_pyobj</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
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<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">node</span>
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<div class="viewcode-block" id="sym_float"><a class="viewcode-back" href="../generated/torch.sym_float.html#torch.sym_float">[docs]</a><span class="k">def</span> <span class="nf">sym_float</span><span class="p">(</span><span class="n">a</span><span class="p">):</span>
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<span class="sa">r</span><span class="sd">&quot;&quot;&quot; SymInt-aware utility for float casting.</span>
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<span class="sd"> Args:</span>
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<span class="sd"> a (SymInt, SymFloat, or object): Object to cast</span>
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<span class="sd"> &quot;&quot;&quot;</span>
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<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">SymFloat</span><span class="p">):</span>
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<span class="k">return</span> <span class="n">a</span><span class="o">.</span><span class="n">__sym_float__</span><span class="p">()</span>
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<span class="k">return</span> <span class="n">py_float</span><span class="p">(</span><span class="n">a</span><span class="p">)</span> <span class="c1"># type: ignore[operator]</span></div>
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<span class="c1"># Drop in replacement for math.floor/ceil. Actually, math.floor/ceil</span>
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<span class="c1"># directly usable, but this has a more relaxed type signature for mypy</span>
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<span class="c1"># (mypy requires SupportFloat which is too strict)</span>
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<span class="k">def</span> <span class="nf">_sym_floor</span><span class="p">(</span><span class="n">x</span><span class="p">):</span>
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<span class="k">return</span> <span class="n">math</span><span class="o">.</span><span class="n">floor</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="c1"># type: ignore[type]</span>
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<span class="k">def</span> <span class="nf">_sym_ceil</span><span class="p">(</span><span class="n">x</span><span class="p">):</span>
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<span class="k">return</span> <span class="n">math</span><span class="o">.</span><span class="n">ceil</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="c1"># type: ignore[type]</span>
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<div class="viewcode-block" id="sym_int"><a class="viewcode-back" href="../generated/torch.sym_int.html#torch.sym_int">[docs]</a><span class="k">def</span> <span class="nf">sym_int</span><span class="p">(</span><span class="n">a</span><span class="p">):</span>
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<span class="sa">r</span><span class="sd">&quot;&quot;&quot; SymInt-aware utility for int casting.</span>
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<span class="sd"> Args:</span>
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<span class="sd"> a (SymInt, SymFloat, or object): Object to cast</span>
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<span class="sd"> &quot;&quot;&quot;</span>
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<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">SymInt</span><span class="p">):</span>
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<span class="c1"># Check to see if we can load C extensions, and if not provide some guidance</span>
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@@ -1429,6 +1463,11 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
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<span class="kn">from</span> <span class="nn">torch.amp</span> <span class="kn">import</span> <span class="n">autocast</span>
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<span class="c1"># Initializing the extension shadows the built-in python float / int classes;</span>
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<div class="viewcode-block" id="Tensor.storage"><a class="viewcode-back" href="../../generated/torch.Tensor.storage.html#torch.Tensor.storage">[docs]</a> <span class="k">def</span> <span class="nf">storage</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
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<span class="sd"> storage() -&gt; torch.TypedStorage</span>
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<span class="sd"> Returns the underlying storage.</span>
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<span class="sd"> Returns the underlying :class:`TypedStorage`.</span>
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<span class="sd"> :class:`TypedStorage` is deprecated. It will be removed in the future, and</span>
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<span class="k">def</span> <span class="nf">_typed_storage</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
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<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">_storage</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">TypedStorage</span><span class="p">):</span>
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<span class="n">wrap_storage</span><span class="o">=</span><span class="n">untyped_storage</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span> <span class="n">_internal</span><span class="o">=</span><span class="kc">True</span>
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<span class="k">def</span> <span class="nf">_reduce_ex_internal</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">proto</span><span class="p">):</span>

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