Generate Python docs from pytorch/pytorch@0553b46

Author: pytorchbot

docs/2.0/_images/RReLU.png

@@ -1927,6 +1927,15 @@ <h1>Source code for torch.onnx.utils</h1><div class="highlight"><pre>
     <span class="k">if</span> <span class="n">export_type</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
         <span class="n">export_type</span> <span class="o">=</span> <span class="n">_exporter_states</span><span class="o">.</span><span class="n">ExportTypes</span><span class="o">.</span><span class="n">PROTOBUF_FILE</span>
 
+    <span class="c1"># Discussed deprecation with Nikita Shulga and Sergii Dymchenko from Meta</span>
+    <span class="k">if</span> <span class="n">_C_onnx</span><span class="o">.</span><span class="n">_CAFFE2_ATEN_FALLBACK</span><span class="p">:</span>
+        <span class="n">warnings</span><span class="o">.</span><span class="n">warn</span><span class="p">(</span>
+            <span class="s2">&quot;Caffe2 ONNX exporter is deprecated in version 2.0 and will be &quot;</span>
+            <span class="s2">&quot;removed in 2.2. Please use PyTorch 2.1 or older for this capability.&quot;</span><span class="p">,</span>
+            <span class="n">category</span><span class="o">=</span><span class="ne">FutureWarning</span><span class="p">,</span>
+            <span class="n">stacklevel</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span>
+        <span class="p">)</span>
+
     <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">model</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">DataParallel</span><span class="p">):</span>
         <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span>
             <span class="s2">&quot;torch.nn.DataParallel is not supported by ONNX &quot;</span>

docs/2.0/_modules/torch/onnx/utils.html

@@ -846,7 +846,7 @@ <h1>Source code for torch.profiler.profiler</h1><div class="highlight"><pre>
 <span class="sd">                torch.profiler.ProfilerActivity.CUDA,</span>
 <span class="sd">            ],</span>
 
-<span class="sd">            # In this example with wait=1, warmup=1, active=2,</span>
+<span class="sd">            # In this example with wait=1, warmup=1, active=2, repeat=1,</span>
 <span class="sd">            # profiler will skip the first step/iteration,</span>
 <span class="sd">            # start warming up on the second, record</span>
 <span class="sd">            # the third and the forth iterations,</span>
@@ -857,7 +857,8 @@ <h1>Source code for torch.profiler.profiler</h1><div class="highlight"><pre>
 <span class="sd">            schedule=torch.profiler.schedule(</span>
 <span class="sd">                wait=1,</span>
 <span class="sd">                warmup=1,</span>
-<span class="sd">                active=2),</span>
+<span class="sd">                active=2,</span>
+<span class="sd">                repeat=1),</span>
 <span class="sd">            on_trace_ready=trace_handler</span>
 <span class="sd">            # on_trace_ready=torch.profiler.tensorboard_trace_handler(&#39;./log&#39;)</span>
 <span class="sd">            # used when outputting for tensorboard</span>

docs/2.0/_modules/torch/profiler/profiler.html

@@ -661,7 +661,7 @@ <h2>API Reference<a class="headerlink" href="#api-reference" title="Permalink to
         <span class="n">torch</span><span class="o">.</span><span class="n">profiler</span><span class="o">.</span><span class="n">ProfilerActivity</span><span class="o">.</span><span class="n">CUDA</span><span class="p">,</span>
     <span class="p">],</span>
 
-    <span class="c1"># In this example with wait=1, warmup=1, active=2,</span>
+    <span class="c1"># In this example with wait=1, warmup=1, active=2, repeat=1,</span>
     <span class="c1"># profiler will skip the first step/iteration,</span>
     <span class="c1"># start warming up on the second, record</span>
     <span class="c1"># the third and the forth iterations,</span>
@@ -672,7 +672,8 @@ <h2>API Reference<a class="headerlink" href="#api-reference" title="Permalink to
     <span class="n">schedule</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">profiler</span><span class="o">.</span><span class="n">schedule</span><span class="p">(</span>
         <span class="n">wait</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span>
         <span class="n">warmup</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span>
-        <span class="n">active</span><span class="o">=</span><span class="mi">2</span><span class="p">),</span>
+        <span class="n">active</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span>
+        <span class="n">repeat</span><span class="o">=</span><span class="mi">1</span><span class="p">),</span>
     <span class="n">on_trace_ready</span><span class="o">=</span><span class="n">trace_handler</span>
     <span class="c1"># on_trace_ready=torch.profiler.tensorboard_trace_handler(&#39;./log&#39;)</span>
     <span class="c1"># used when outputting for tensorboard</span>