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<div class="section" id="python-builtin">
<h1>python.builtin<a class="headerlink" href="#python-builtin" title="Permalink to this heading">¶</a></h1>
<div class="section" id="dynamic-shape-round">
<h2>dynamic_shape_round<a class="headerlink" href="#dynamic-shape-round" title="Permalink to this heading">¶</a></h2>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>Tags: <a class="reference internal" href="torch.dynamic-shape.html"><span class="doc">torch.dynamic-shape</span></a>, <a class="reference internal" href="#"><span class="doc">python.builtin</span></a></p>
<p>Support Level: NOT_SUPPORTED_YET</p>
</div>
<p>Original source code:</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># mypy: allow-untyped-defs</span>
<span class="kn">import</span> <span class="nn">torch</span>
<span class="kn">from</span> <span class="nn">torch._export.db.case</span> <span class="kn">import</span> <span class="n">SupportLevel</span>
<span class="kn">from</span> <span class="nn">torch.export</span> <span class="kn">import</span> <span class="n">Dim</span>
<span class="k">class</span> <span class="nc">DynamicShapeRound</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">Module</span><span class="p">):</span>
<span class="w"> </span><span class="sd">"""</span>
<span class="sd"> Calling round on dynamic shapes is not supported.</span>
<span class="sd"> """</span>
<span class="k">def</span> <span class="nf">forward</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="k">return</span> <span class="n">x</span><span class="p">[:</span> <span class="nb">round</span><span class="p">(</span><span class="n">x</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">/</span> <span class="mi">2</span><span class="p">)]</span>
<span class="n">x</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span>
<span class="n">dim0_x</span> <span class="o">=</span> <span class="n">Dim</span><span class="p">(</span><span class="s2">"dim0_x"</span><span class="p">)</span>
<span class="n">example_args</span> <span class="o">=</span> <span class="p">(</span><span class="n">x</span><span class="p">,)</span>
<span class="n">tags</span> <span class="o">=</span> <span class="p">{</span><span class="s2">"torch.dynamic-shape"</span><span class="p">,</span> <span class="s2">"python.builtin"</span><span class="p">}</span>
<span class="n">support_level</span> <span class="o">=</span> <span class="n">SupportLevel</span><span class="o">.</span><span class="n">NOT_SUPPORTED_YET</span>
<span class="n">dynamic_shapes</span> <span class="o">=</span> <span class="p">{</span><span class="s2">"x"</span><span class="p">:</span> <span class="p">{</span><span class="mi">0</span><span class="p">:</span> <span class="n">dim0_x</span><span class="p">}}</span>
<span class="n">model</span> <span class="o">=</span> <span class="n">DynamicShapeRound</span><span class="p">()</span>
<span class="n">torch</span><span class="o">.</span><span class="n">export</span><span class="o">.</span><span class="n">export</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">example_args</span><span class="p">,</span> <span class="n">dynamic_shapes</span><span class="o">=</span><span class="n">dynamic_shapes</span><span class="p">)</span>
</pre></div>
</div>
<p>Result:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>Unsupported: Constraints violated (dim0_x)! For more information, run with TORCH_LOGS="+dynamic".
</pre></div>
</div>
</div>
<div class="section" id="tensor-setattr">
<h2>tensor_setattr<a class="headerlink" href="#tensor-setattr" title="Permalink to this heading">¶</a></h2>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>Tags: <a class="reference internal" href="#"><span class="doc">python.builtin</span></a></p>
<p>Support Level: SUPPORTED</p>
</div>
<p>Original source code:</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># mypy: allow-untyped-defs</span>
<span class="kn">import</span> <span class="nn">torch</span>
<span class="k">class</span> <span class="nc">TensorSetattr</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">Module</span><span class="p">):</span>
<span class="w"> </span><span class="sd">"""</span>
<span class="sd"> setattr() call onto tensors is not supported.</span>
<span class="sd"> """</span>
<span class="k">def</span> <span class="nf">forward</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="n">attr</span><span class="p">):</span>
<span class="nb">setattr</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">attr</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">))</span>
<span class="k">return</span> <span class="n">x</span> <span class="o">+</span> <span class="mi">4</span>
<span class="n">example_args</span> <span class="o">=</span> <span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">),</span> <span class="s2">"attr"</span><span class="p">)</span>
<span class="n">tags</span> <span class="o">=</span> <span class="p">{</span><span class="s2">"python.builtin"</span><span class="p">}</span>
<span class="n">model</span> <span class="o">=</span> <span class="n">TensorSetattr</span><span class="p">()</span>
<span class="n">torch</span><span class="o">.</span><span class="n">export</span><span class="o">.</span><span class="n">export</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">example_args</span><span class="p">)</span>
</pre></div>
</div>
<p>Result:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">ExportedProgram</span><span class="p">:</span>
<span class="k">class</span> <span class="nc">GraphModule</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">Module</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">forward</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="s2">"f32[3, 2]"</span><span class="p">,</span> <span class="n">attr</span><span class="p">):</span>
<span class="n">randn</span><span class="p">:</span> <span class="s2">"f32[3, 2]"</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">ops</span><span class="o">.</span><span class="n">aten</span><span class="o">.</span><span class="n">randn</span><span class="o">.</span><span class="n">default</span><span class="p">([</span><span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">],</span> <span class="n">device</span> <span class="o">=</span> <span class="n">device</span><span class="p">(</span><span class="nb">type</span><span class="o">=</span><span class="s1">'cpu'</span><span class="p">),</span> <span class="n">pin_memory</span> <span class="o">=</span> <span class="kc">False</span><span class="p">);</span> <span class="n">randn</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">add</span><span class="p">:</span> <span class="s2">"f32[3, 2]"</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">ops</span><span class="o">.</span><span class="n">aten</span><span class="o">.</span><span class="n">add</span><span class="o">.</span><span class="n">Tensor</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="mi">4</span><span class="p">);</span> <span class="n">x</span> <span class="o">=</span> <span class="kc">None</span>
<span class="k">return</span> <span class="p">(</span><span class="n">add</span><span class="p">,)</span>
<span class="n">Graph</span> <span class="n">signature</span><span class="p">:</span> <span class="n">ExportGraphSignature</span><span class="p">(</span><span class="n">input_specs</span><span class="o">=</span><span class="p">[</span><span class="n">InputSpec</span><span class="p">(</span><span class="n">kind</span><span class="o">=<</span><span class="n">InputKind</span><span class="o">.</span><span class="n">USER_INPUT</span><span class="p">:</span> <span class="mi">1</span><span class="o">></span><span class="p">,</span> <span class="n">arg</span><span class="o">=</span><span class="n">TensorArgument</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s1">'x'</span><span class="p">),</span> <span class="n">target</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">persistent</span><span class="o">=</span><span class="kc">None</span><span class="p">),</span> <span class="n">InputSpec</span><span class="p">(</span><span class="n">kind</span><span class="o">=<</span><span class="n">InputKind</span><span class="o">.</span><span class="n">USER_INPUT</span><span class="p">:</span> <span class="mi">1</span><span class="o">></span><span class="p">,</span> <span class="n">arg</span><span class="o">=</span><span class="n">ConstantArgument</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s1">'attr'</span><span class="p">,</span> <span class="n">value</span><span class="o">=</span><span class="s1">'attr'</span><span class="p">),</span> <span class="n">target</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">persistent</span><span class="o">=</span><span class="kc">None</span><span class="p">)],</span> <span class="n">output_specs</span><span class="o">=</span><span class="p">[</span><span class="n">OutputSpec</span><span class="p">(</span><span class="n">kind</span><span class="o">=<</span><span class="n">OutputKind</span><span class="o">.</span><span class="n">USER_OUTPUT</span><span class="p">:</span> <span class="mi">1</span><span class="o">></span><span class="p">,</span> <span class="n">arg</span><span class="o">=</span><span class="n">TensorArgument</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s1">'add'</span><span class="p">),</span> <span class="n">target</span><span class="o">=</span><span class="kc">None</span><span class="p">)])</span>
<span class="n">Range</span> <span class="n">constraints</span><span class="p">:</span> <span class="p">{}</span>
</pre></div>
</div>
</div>
<div class="section" id="type-reflection-method">
<h2>type_reflection_method<a class="headerlink" href="#type-reflection-method" title="Permalink to this heading">¶</a></h2>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>Tags: <a class="reference internal" href="#"><span class="doc">python.builtin</span></a></p>
<p>Support Level: SUPPORTED</p>
</div>
<p>Original source code:</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># mypy: allow-untyped-defs</span>
<span class="kn">import</span> <span class="nn">torch</span>
<span class="k">class</span> <span class="nc">A</span><span class="p">:</span>
<span class="nd">@classmethod</span>
<span class="k">def</span> <span class="nf">func</span><span class="p">(</span><span class="bp">cls</span><span class="p">,</span> <span class="n">x</span><span class="p">):</span>
<span class="k">return</span> <span class="mi">1</span> <span class="o">+</span> <span class="n">x</span>
<span class="k">class</span> <span class="nc">TypeReflectionMethod</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">Module</span><span class="p">):</span>
<span class="w"> </span><span class="sd">"""</span>
<span class="sd"> type() calls on custom objects followed by attribute accesses are not allowed</span>
<span class="sd"> due to its overly dynamic nature.</span>
<span class="sd"> """</span>
<span class="k">def</span> <span class="nf">forward</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="n">a</span> <span class="o">=</span> <span class="n">A</span><span class="p">()</span>
<span class="k">return</span> <span class="nb">type</span><span class="p">(</span><span class="n">a</span><span class="p">)</span><span class="o">.</span><span class="n">func</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
<span class="n">example_args</span> <span class="o">=</span> <span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">),)</span>
<span class="n">tags</span> <span class="o">=</span> <span class="p">{</span><span class="s2">"python.builtin"</span><span class="p">}</span>
<span class="n">model</span> <span class="o">=</span> <span class="n">TypeReflectionMethod</span><span class="p">()</span>
<span class="n">torch</span><span class="o">.</span><span class="n">export</span><span class="o">.</span><span class="n">export</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">example_args</span><span class="p">)</span>
</pre></div>
</div>
<p>Result:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">ExportedProgram</span><span class="p">:</span>
<span class="k">class</span> <span class="nc">GraphModule</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">Module</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">forward</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="s2">"f32[3, 4]"</span><span class="p">):</span>
<span class="n">add</span><span class="p">:</span> <span class="s2">"f32[3, 4]"</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">ops</span><span class="o">.</span><span class="n">aten</span><span class="o">.</span><span class="n">add</span><span class="o">.</span><span class="n">Tensor</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="mi">1</span><span class="p">);</span> <span class="n">x</span> <span class="o">=</span> <span class="kc">None</span>
<span class="k">return</span> <span class="p">(</span><span class="n">add</span><span class="p">,)</span>
<span class="n">Graph</span> <span class="n">signature</span><span class="p">:</span> <span class="n">ExportGraphSignature</span><span class="p">(</span><span class="n">input_specs</span><span class="o">=</span><span class="p">[</span><span class="n">InputSpec</span><span class="p">(</span><span class="n">kind</span><span class="o">=<</span><span class="n">InputKind</span><span class="o">.</span><span class="n">USER_INPUT</span><span class="p">:</span> <span class="mi">1</span><span class="o">></span><span class="p">,</span> <span class="n">arg</span><span class="o">=</span><span class="n">TensorArgument</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s1">'x'</span><span class="p">),</span> <span class="n">target</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">persistent</span><span class="o">=</span><span class="kc">None</span><span class="p">)],</span> <span class="n">output_specs</span><span class="o">=</span><span class="p">[</span><span class="n">OutputSpec</span><span class="p">(</span><span class="n">kind</span><span class="o">=<</span><span class="n">OutputKind</span><span class="o">.</span><span class="n">USER_OUTPUT</span><span class="p">:</span> <span class="mi">1</span><span class="o">></span><span class="p">,</span> <span class="n">arg</span><span class="o">=</span><span class="n">TensorArgument</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s1">'add'</span><span class="p">),</span> <span class="n">target</span><span class="o">=</span><span class="kc">None</span><span class="p">)])</span>
<span class="n">Range</span> <span class="n">constraints</span><span class="p">:</span> <span class="p">{}</span>
</pre></div>
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<a href="https://pytorch.org/tutorials/beginner/introyt.html">Introduction to PyTorch - YouTube Series</a>
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