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<div class="section" id="torch-dynamic-value">
<h1>torch.dynamic-value<a class="headerlink" href="#torch-dynamic-value" title="Permalink to this heading">¶</a></h1>
<div class="section" id="constrain-as-size-example">
<h2>constrain_as_size_example<a class="headerlink" href="#constrain-as-size-example" 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.escape-hatch.html"><span class="doc">torch.escape-hatch</span></a>, <a class="reference internal" href="#"><span class="doc">torch.dynamic-value</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="kn">import</span> <span class="nn">torch</span>
<span class="k">def</span> <span class="nf">constrain_as_size_example</span><span class="p">(</span><span class="n">x</span><span class="p">):</span>
<span class="w"> </span><span class="sd">"""</span>
<span class="sd"> If the value is not known at tracing time, you can provide hint so that we</span>
<span class="sd"> can trace further. Please look at constrain_as_value and constrain_as_size APIs</span>
<span class="sd"> constrain_as_size is used for values that NEED to be used for constructing</span>
<span class="sd"> tensor.</span>
<span class="sd"> """</span>
<span class="n">a</span> <span class="o">=</span> <span class="n">x</span><span class="o">.</span><span class="n">item</span><span class="p">()</span>
<span class="n">torch</span><span class="o">.</span><span class="n">_constrain_as_size</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="nb">min</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="nb">max</span><span class="o">=</span><span class="mi">5</span><span class="p">)</span>
<span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">ones</span><span class="p">((</span><span class="n">a</span><span class="p">,</span> <span class="mi">5</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">l_x_</span><span class="p">:</span> <span class="s2">"i64[]"</span><span class="p">):</span>
<span class="n">_local_scalar_dense</span><span class="p">:</span> <span class="s2">"Sym(i4)"</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">_local_scalar_dense</span><span class="o">.</span><span class="n">default</span><span class="p">(</span><span class="n">l_x_</span><span class="p">);</span> <span class="n">l_x_</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">ge</span><span class="p">:</span> <span class="s2">"Sym(i4 >= 0)"</span> <span class="o">=</span> <span class="n">_local_scalar_dense</span> <span class="o">>=</span> <span class="mi">0</span>
<span class="n">scalar_tensor</span><span class="p">:</span> <span class="s2">"f32[]"</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">scalar_tensor</span><span class="o">.</span><span class="n">default</span><span class="p">(</span><span class="n">ge</span><span class="p">);</span> <span class="n">ge</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">_assert_async</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">_assert_async</span><span class="o">.</span><span class="n">msg</span><span class="p">(</span><span class="n">scalar_tensor</span><span class="p">,</span> <span class="s1">'_local_scalar_dense is outside of inline constraint [0, 5].'</span><span class="p">);</span> <span class="n">scalar_tensor</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">le</span><span class="p">:</span> <span class="s2">"Sym(i4 <= 5)"</span> <span class="o">=</span> <span class="n">_local_scalar_dense</span> <span class="o"><=</span> <span class="mi">5</span>
<span class="n">scalar_tensor_1</span><span class="p">:</span> <span class="s2">"f32[]"</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">scalar_tensor</span><span class="o">.</span><span class="n">default</span><span class="p">(</span><span class="n">le</span><span class="p">);</span> <span class="n">le</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">_assert_async_1</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">_assert_async</span><span class="o">.</span><span class="n">msg</span><span class="p">(</span><span class="n">scalar_tensor_1</span><span class="p">,</span> <span class="s1">'_local_scalar_dense is outside of inline constraint [0, 5].'</span><span class="p">);</span> <span class="n">scalar_tensor_1</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">sym_constrain_range_for_size</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">sym_constrain_range_for_size</span><span class="o">.</span><span class="n">default</span><span class="p">(</span><span class="n">_local_scalar_dense</span><span class="p">,</span> <span class="nb">min</span> <span class="o">=</span> <span class="mi">0</span><span class="p">,</span> <span class="nb">max</span> <span class="o">=</span> <span class="mi">5</span><span class="p">)</span>
<span class="n">ones</span><span class="p">:</span> <span class="s2">"f32[i4, 5]"</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">ones</span><span class="o">.</span><span class="n">default</span><span class="p">([</span><span class="n">_local_scalar_dense</span><span class="p">,</span> <span class="mi">5</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">_local_scalar_dense</span> <span class="o">=</span> <span class="kc">None</span>
<span class="k">return</span> <span class="p">(</span><span class="n">ones</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">'l_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">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">'ones'</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><span class="n">i0</span><span class="p">:</span> <span class="n">ValueRanges</span><span class="p">(</span><span class="n">lower</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">upper</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span> <span class="n">is_bool</span><span class="o">=</span><span class="kc">False</span><span class="p">),</span> <span class="n">i1</span><span class="p">:</span> <span class="n">ValueRanges</span><span class="p">(</span><span class="n">lower</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">upper</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span> <span class="n">is_bool</span><span class="o">=</span><span class="kc">False</span><span class="p">),</span> <span class="n">i2</span><span class="p">:</span> <span class="n">ValueRanges</span><span class="p">(</span><span class="n">lower</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">upper</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span> <span class="n">is_bool</span><span class="o">=</span><span class="kc">False</span><span class="p">),</span> <span class="n">i3</span><span class="p">:</span> <span class="n">ValueRanges</span><span class="p">(</span><span class="n">lower</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">upper</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span> <span class="n">is_bool</span><span class="o">=</span><span class="kc">False</span><span class="p">),</span> <span class="n">i4</span><span class="p">:</span> <span class="n">ValueRanges</span><span class="p">(</span><span class="n">lower</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">upper</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span> <span class="n">is_bool</span><span class="o">=</span><span class="kc">False</span><span class="p">)}</span>
<span class="n">Equality</span> <span class="n">constraints</span><span class="p">:</span> <span class="p">[]</span>
</pre></div>
</div>
</div>
<div class="section" id="constrain-as-value-example">
<h2>constrain_as_value_example<a class="headerlink" href="#constrain-as-value-example" 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.escape-hatch.html"><span class="doc">torch.escape-hatch</span></a>, <a class="reference internal" href="#"><span class="doc">torch.dynamic-value</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="kn">import</span> <span class="nn">torch</span>
<span class="k">def</span> <span class="nf">constrain_as_value_example</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">):</span>
<span class="w"> </span><span class="sd">"""</span>
<span class="sd"> If the value is not known at tracing time, you can provide hint so that we</span>
<span class="sd"> can trace further. Please look at constrain_as_value and constrain_as_size APIs.</span>
<span class="sd"> constrain_as_value is used for values that don't need to be used for constructing</span>
<span class="sd"> tensor.</span>
<span class="sd"> """</span>
<span class="n">a</span> <span class="o">=</span> <span class="n">x</span><span class="o">.</span><span class="n">item</span><span class="p">()</span>
<span class="n">torch</span><span class="o">.</span><span class="n">_constrain_as_value</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="nb">min</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="nb">max</span><span class="o">=</span><span class="mi">5</span><span class="p">)</span>
<span class="k">if</span> <span class="n">a</span> <span class="o"><</span> <span class="mi">6</span><span class="p">:</span>
<span class="k">return</span> <span class="n">y</span><span class="o">.</span><span class="n">sin</span><span class="p">()</span>
<span class="k">return</span> <span class="n">y</span><span class="o">.</span><span class="n">cos</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">l_x_</span><span class="p">:</span> <span class="s2">"i64[]"</span><span class="p">,</span> <span class="n">l_y_</span><span class="p">:</span> <span class="s2">"f32[5, 5]"</span><span class="p">):</span>
<span class="n">_local_scalar_dense</span><span class="p">:</span> <span class="s2">"Sym(i4)"</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">_local_scalar_dense</span><span class="o">.</span><span class="n">default</span><span class="p">(</span><span class="n">l_x_</span><span class="p">);</span> <span class="n">l_x_</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">ge</span><span class="p">:</span> <span class="s2">"Sym(i4 >= 0)"</span> <span class="o">=</span> <span class="n">_local_scalar_dense</span> <span class="o">>=</span> <span class="mi">0</span>
<span class="n">scalar_tensor</span><span class="p">:</span> <span class="s2">"f32[]"</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">scalar_tensor</span><span class="o">.</span><span class="n">default</span><span class="p">(</span><span class="n">ge</span><span class="p">);</span> <span class="n">ge</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">_assert_async</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">_assert_async</span><span class="o">.</span><span class="n">msg</span><span class="p">(</span><span class="n">scalar_tensor</span><span class="p">,</span> <span class="s1">'_local_scalar_dense is outside of inline constraint [0, 5].'</span><span class="p">);</span> <span class="n">scalar_tensor</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">le</span><span class="p">:</span> <span class="s2">"Sym(i4 <= 5)"</span> <span class="o">=</span> <span class="n">_local_scalar_dense</span> <span class="o"><=</span> <span class="mi">5</span>
<span class="n">scalar_tensor_1</span><span class="p">:</span> <span class="s2">"f32[]"</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">scalar_tensor</span><span class="o">.</span><span class="n">default</span><span class="p">(</span><span class="n">le</span><span class="p">);</span> <span class="n">le</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">_assert_async_1</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">_assert_async</span><span class="o">.</span><span class="n">msg</span><span class="p">(</span><span class="n">scalar_tensor_1</span><span class="p">,</span> <span class="s1">'_local_scalar_dense is outside of inline constraint [0, 5].'</span><span class="p">);</span> <span class="n">scalar_tensor_1</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">sym_constrain_range</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">sym_constrain_range</span><span class="o">.</span><span class="n">default</span><span class="p">(</span><span class="n">_local_scalar_dense</span><span class="p">,</span> <span class="nb">min</span> <span class="o">=</span> <span class="mi">0</span><span class="p">,</span> <span class="nb">max</span> <span class="o">=</span> <span class="mi">5</span><span class="p">);</span> <span class="n">_local_scalar_dense</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">sin</span><span class="p">:</span> <span class="s2">"f32[5, 5]"</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">sin</span><span class="o">.</span><span class="n">default</span><span class="p">(</span><span class="n">l_y_</span><span class="p">);</span> <span class="n">l_y_</span> <span class="o">=</span> <span class="kc">None</span>
<span class="k">return</span> <span class="p">(</span><span class="n">sin</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">'l_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">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">'l_y_'</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">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">'sin'</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><span class="n">i0</span><span class="p">:</span> <span class="n">ValueRanges</span><span class="p">(</span><span class="n">lower</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">upper</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span> <span class="n">is_bool</span><span class="o">=</span><span class="kc">False</span><span class="p">),</span> <span class="n">i1</span><span class="p">:</span> <span class="n">ValueRanges</span><span class="p">(</span><span class="n">lower</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">upper</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span> <span class="n">is_bool</span><span class="o">=</span><span class="kc">False</span><span class="p">),</span> <span class="n">i2</span><span class="p">:</span> <span class="n">ValueRanges</span><span class="p">(</span><span class="n">lower</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">upper</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span> <span class="n">is_bool</span><span class="o">=</span><span class="kc">False</span><span class="p">),</span> <span class="n">i3</span><span class="p">:</span> <span class="n">ValueRanges</span><span class="p">(</span><span class="n">lower</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">upper</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span> <span class="n">is_bool</span><span class="o">=</span><span class="kc">False</span><span class="p">),</span> <span class="n">i4</span><span class="p">:</span> <span class="n">ValueRanges</span><span class="p">(</span><span class="n">lower</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">upper</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span> <span class="n">is_bool</span><span class="o">=</span><span class="kc">False</span><span class="p">)}</span>
<span class="n">Equality</span> <span class="n">constraints</span><span class="p">:</span> <span class="p">[]</span>
</pre></div>
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