Generate Python docs from pytorch/pytorch@35991df

Author: pytorchbot

docs/main/_dynamo.html

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     <div class="version">
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docs/main/_images/RReLU.png

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docs/main/_modules/torch.html

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docs/main/_modules/torch/__config__.html

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docs/main/_modules/torch/_dynamo.html

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     <div class="version">
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docs/main/_modules/torch/_dynamo/backends/registry.html

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@@ -478,6 +478,7 @@ <h1>Source code for torch._dynamo.eval_frame</h1><div class="highlight"><pre>
 <span class="kn">import</span> <span class="nn">inspect</span>
 <span class="kn">import</span> <span class="nn">logging</span>
 <span class="kn">import</span> <span class="nn">os</span>
+<span class="kn">import</span> <span class="nn">re</span>
 <span class="kn">import</span> <span class="nn">sys</span>
 <span class="kn">import</span> <span class="nn">textwrap</span>
 <span class="kn">import</span> <span class="nn">threading</span>
@@ -1143,6 +1144,22 @@ <h1>Source code for torch._dynamo.eval_frame</h1><div class="highlight"><pre>
             <span class="s2">&quot;you can specify them separately instead.&quot;</span>
         <span class="p">)</span>
 
+    <span class="nd">@property</span>
+    <span class="k">def</span> <span class="nf">serializable_spec</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
+        <span class="c1"># We need a serialization compatible format of the constraint so that it</span>
+        <span class="c1"># can be savedin the graph module w/o breaking the module serialization.</span>
+        <span class="c1"># The saved constraints will be used directly for the post-exporting pass</span>
+        <span class="c1"># that converts constraints to runtime assertion. The saved constraints</span>
+        <span class="c1"># will not be saved in the serialized module.</span>
+        <span class="c1"># TODO: A better way is needed. Currently we use &#39;t_id&#39; to map the constraint,</span>
+        <span class="c1"># which is not reliable</span>
+        <span class="k">return</span> <span class="p">{</span>
+            <span class="s2">&quot;t_id&quot;</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">t_id</span><span class="p">,</span>
+            <span class="s2">&quot;dim&quot;</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">dim</span><span class="p">,</span>
+            <span class="s2">&quot;min&quot;</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">constraint_range</span><span class="o">.</span><span class="n">vr</span><span class="o">.</span><span class="n">lower</span><span class="p">,</span>
+            <span class="s2">&quot;max&quot;</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">constraint_range</span><span class="o">.</span><span class="n">vr</span><span class="o">.</span><span class="n">upper</span><span class="p">,</span>
+        <span class="p">}</span>
+
 
 <div class="viewcode-block" id="export"><a class="viewcode-back" href="../../../_dynamo.html#torch._dynamo.export">[docs]</a><span class="k">def</span> <span class="nf">export</span><span class="p">(</span>
     <span class="n">f</span><span class="p">:</span> <span class="n">Callable</span><span class="p">[</span><span class="o">...</span><span class="p">,</span> <span class="n">Any</span><span class="p">],</span>
@@ -1246,6 +1263,7 @@ <h1>Source code for torch._dynamo.eval_frame</h1><div class="highlight"><pre>
 
     <span class="n">fake_mode</span> <span class="o">=</span> <span class="kc">None</span>
     <span class="n">example_inputs</span> <span class="o">=</span> <span class="p">[]</span>
+    <span class="n">var_to_range_map</span> <span class="o">=</span> <span class="p">{}</span>
 
     <span class="k">def</span> <span class="nf">dynamo_normalization_capturing_compiler</span><span class="p">(</span>
         <span class="n">gm</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">fx</span><span class="o">.</span><span class="n">GraphModule</span><span class="p">,</span> <span class="n">inner_example_inputs</span>
@@ -1256,9 +1274,11 @@ <h1>Source code for torch._dynamo.eval_frame</h1><div class="highlight"><pre>
         <span class="p">),</span> <span class="s2">&quot;Tried to emit a second graph during export. Tracing through &#39;f&#39; must produce a single graph.&quot;</span>
         <span class="n">graph</span> <span class="o">=</span> <span class="n">gm</span>
 
-        <span class="k">nonlocal</span> <span class="n">fake_mode</span><span class="p">,</span> <span class="n">example_inputs</span>
+        <span class="k">nonlocal</span> <span class="n">fake_mode</span><span class="p">,</span> <span class="n">example_inputs</span><span class="p">,</span> <span class="n">var_to_range_map</span>
         <span class="n">fake_mode</span> <span class="o">=</span> <span class="n">_guards</span><span class="o">.</span><span class="n">detect_fake_mode</span><span class="p">(</span><span class="n">inner_example_inputs</span><span class="p">)</span>
         <span class="n">example_inputs</span> <span class="o">=</span> <span class="n">inner_example_inputs</span>
+        <span class="k">if</span> <span class="n">fake_mode</span> <span class="ow">and</span> <span class="n">fake_mode</span><span class="o">.</span><span class="n">shape_env</span><span class="p">:</span>
+            <span class="n">var_to_range_map</span> <span class="o">=</span> <span class="n">fake_mode</span><span class="o">.</span><span class="n">shape_env</span><span class="o">.</span><span class="n">var_to_range</span>
 
         <span class="k">def</span> <span class="nf">result_capturing_wrapper</span><span class="p">(</span><span class="o">*</span><span class="n">graph_inputs</span><span class="p">):</span>
             <span class="k">nonlocal</span> <span class="n">graph_captured_result</span>
@@ -1378,6 +1398,21 @@ <h1>Source code for torch._dynamo.eval_frame</h1><div class="highlight"><pre>
         <span class="n">graph</span><span class="p">,</span>
     <span class="p">)</span><span class="o">.</span><span class="n">transform</span><span class="p">()</span>
 
+    <span class="c1"># Store constraints and inputs as metadata for user passes, e.g. turn constraints to runtime check</span>
+    <span class="n">new_graph</span><span class="o">.</span><span class="n">meta</span><span class="p">[</span><span class="s2">&quot;example_inputs&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">example_inputs</span>
+    <span class="n">new_graph</span><span class="o">.</span><span class="n">meta</span><span class="p">[</span><span class="s2">&quot;input_shape_constraints&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span>
+        <span class="p">[</span><span class="n">constraint</span><span class="o">.</span><span class="n">serializable_spec</span> <span class="k">for</span> <span class="n">constraint</span> <span class="ow">in</span> <span class="n">constraints</span><span class="p">]</span>
+        <span class="k">if</span> <span class="n">constraints</span>
+        <span class="k">else</span> <span class="kc">None</span>
+    <span class="p">)</span>
+    <span class="n">new_graph</span><span class="o">.</span><span class="n">meta</span><span class="p">[</span><span class="s2">&quot;inline_constraints&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="p">{</span>
+        <span class="n">node</span><span class="o">.</span><span class="n">meta</span><span class="p">[</span><span class="s2">&quot;val&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">node</span><span class="o">.</span><span class="n">expr</span><span class="p">:</span> <span class="n">var_to_range_map</span><span class="p">[</span><span class="n">node</span><span class="o">.</span><span class="n">meta</span><span class="p">[</span><span class="s2">&quot;val&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">node</span><span class="o">.</span><span class="n">expr</span><span class="p">]</span>
+        <span class="k">for</span> <span class="n">node</span> <span class="ow">in</span> <span class="n">new_graph</span><span class="o">.</span><span class="n">graph</span><span class="o">.</span><span class="n">nodes</span>
+        <span class="k">if</span> <span class="n">node</span><span class="o">.</span><span class="n">op</span> <span class="o">!=</span> <span class="s2">&quot;placeholder&quot;</span> <span class="ow">and</span> <span class="s2">&quot;val&quot;</span> <span class="ow">in</span> <span class="n">node</span><span class="o">.</span><span class="n">meta</span>
+        <span class="c1"># Find constraints frome unbacked symints</span>
+        <span class="ow">and</span> <span class="n">re</span><span class="o">.</span><span class="n">match</span><span class="p">(</span><span class="sa">r</span><span class="s2">&quot;^i\d+$&quot;</span><span class="p">,</span> <span class="nb">str</span><span class="p">(</span><span class="n">node</span><span class="o">.</span><span class="n">meta</span><span class="p">[</span><span class="s2">&quot;val&quot;</span><span class="p">]))</span>
+    <span class="p">}</span>
+
     <span class="k">def</span> <span class="nf">signature_to_fullargspec</span><span class="p">(</span><span class="n">sig</span><span class="p">:</span> <span class="n">inspect</span><span class="o">.</span><span class="n">Signature</span><span class="p">):</span>
         <span class="c1"># Get a list of Parameter objects from the Signature object</span>
         <span class="n">params</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">sig</span><span class="o">.</span><span class="n">parameters</span><span class="o">.</span><span class="n">values</span><span class="p">())</span>

docs/main/_modules/torch/_dynamo/eval_frame.html

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