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Expand Down Expand Up @@ -493,7 +493,7 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
<span class="s1">&#39;is_deterministic_algorithms_warn_only_enabled&#39;</span><span class="p">,</span>
<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>
<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>
<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;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>
<span class="p">]</span>

<span class="c1">################################################################################</span>
Expand Down Expand Up @@ -642,6 +642,67 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
<span class="k">if</span> <span class="n">TYPE_CHECKING</span><span class="p">:</span>
<span class="kn">import</span> <span class="nn">torch._C</span> <span class="k">as</span> <span class="nn">_C</span>

<span class="k">class</span> <span class="nc">SymInt</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Like an int (including magic methods), but redirects all operations on the</span>
<span class="sd"> wrapped node. This is used in particular to symbolically record operations</span>
<span class="sd"> in the symbolic shape workflow.</span>
<span class="sd"> &quot;&quot;&quot;</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">node</span><span class="p">):</span>
<span class="kn">from</span> <span class="nn">torch.fx.experimental.symbolic_shapes</span> <span class="kn">import</span> <span class="n">SymNode</span>
<span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">node</span><span class="p">,</span> <span class="n">SymNode</span><span class="p">)</span>
<span class="c1"># This field MUST be named node; C++ binding code assumes that this</span>
<span class="c1"># class has a field named node that stores SymNode</span>
<span class="bp">self</span><span class="o">.</span><span class="n">node</span> <span class="o">=</span> <span class="n">node</span>

<span class="c1"># Magic methods installed later</span>

<span class="k">def</span> <span class="fm">__bool__</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">node</span><span class="o">.</span><span class="n">bool_</span><span class="p">()</span>

<span class="k">def</span> <span class="fm">__int__</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">node</span><span class="o">.</span><span class="n">int_</span><span class="p">()</span>

<span class="k">def</span> <span class="nf">__sym_float__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">SymFloat</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">node</span><span class="o">.</span><span class="n">sym_float</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="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">node</span><span class="o">.</span><span class="n">str</span><span class="p">()</span>

<span class="c1"># For BC; direct access of node is OK too</span>
<span class="k">def</span> <span class="nf">get_pyobj</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">node</span>

<span class="k">class</span> <span class="nc">SymFloat</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Like an float (including magic methods), but redirects all operations on the</span>
<span class="sd"> wrapped node. This is used in particular to symbolically record operations</span>
<span class="sd"> in the symbolic shape workflow.</span>
<span class="sd"> &quot;&quot;&quot;</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">node</span><span class="p">):</span>
<span class="kn">from</span> <span class="nn">torch.fx.experimental.symbolic_shapes</span> <span class="kn">import</span> <span class="n">SymNode</span>
<span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">node</span><span class="p">,</span> <span class="n">SymNode</span><span class="p">)</span>
<span class="c1"># This field MUST be named node; C++ binding code assumes that this</span>
<span class="c1"># class has a field named node that stores SymNode</span>
<span class="bp">self</span><span class="o">.</span><span class="n">node</span> <span class="o">=</span> <span class="n">node</span>

<span class="c1"># Magic methods installed later</span>

<span class="k">def</span> <span class="fm">__bool__</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">node</span><span class="o">.</span><span class="n">bool_</span><span class="p">()</span>

<span class="k">def</span> <span class="nf">__sym_int__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">SymInt</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">node</span><span class="o">.</span><span class="n">sym_int</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="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">node</span><span class="o">.</span><span class="n">str</span><span class="p">()</span>

<span class="c1"># For BC; direct access of node is OK too</span>
<span class="k">def</span> <span class="nf">get_pyobj</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">node</span>

<span class="c1"># Check to see if we can load C extensions, and if not provide some guidance</span>
<span class="c1"># on what the problem might be.</span>
<span class="k">try</span><span class="p">:</span>
Expand Down Expand Up @@ -1387,7 +1448,6 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
<span class="n">lstsq</span><span class="p">,</span>
<span class="p">)</span>


<span class="k">def</span> <span class="nf">_register_device_module</span><span class="p">(</span><span class="n">device_type</span><span class="p">,</span> <span class="n">module</span><span class="p">):</span>
<span class="sa">r</span><span class="sd">&quot;&quot;&quot;Register an external runtime module of the specific :attr:`device_type`</span>
<span class="sd"> supported by torch.</span>
Expand Down Expand Up @@ -1417,6 +1477,9 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
<span class="kn">import</span> <span class="nn">torch.cuda._sanitizer</span> <span class="k">as</span> <span class="nn">csan</span>

<span class="n">csan</span><span class="o">.</span><span class="n">enable_cuda_sanitizer</span><span class="p">()</span>

<span class="c1"># Populate magic methods on SymInt and SymFloat</span>
<span class="kn">import</span> <span class="nn">torch.fx.experimental.symbolic_shapes</span>
</pre></div>

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