Generate Python docs from pytorch/pytorch@cc88ac8

Author: pytorchbot

docs/master/__config__.html

@@ -189,7 +189,7 @@
 
 
                 <div class="version">
-                  master (1.9.0a0+git715835c )
+                  master (1.9.0a0+gitcc88ac8 )
                 </div>
 
 

docs/master/_modules/index.html

@@ -188,7 +188,7 @@
 
 
                 <div class="version">
-                  master (1.9.0a0+git715835c )
+                  master (1.9.0a0+gitcc88ac8 )
                 </div>
 
 

docs/master/_modules/torch.html

@@ -188,7 +188,7 @@
 
 
                 <div class="version">
-                  master (1.9.0a0+git715835c )
+                  master (1.9.0a0+gitcc88ac8 )
                 </div>
 
 
@@ -407,7 +407,7 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
 <span class="k">if</span> <span class="n">sys</span><span class="o">.</span><span class="n">executable</span> <span class="o">==</span> <span class="s1">&#39;torch_deploy&#39;</span><span class="p">:</span>
     <span class="n">__version__</span> <span class="o">=</span> <span class="s2">&quot;torch-deploy-1.8&quot;</span>
 <span class="k">else</span><span class="p">:</span>
-    <span class="kn">from</span> <span class="nn">.version</span> <span class="kn">import</span> <span class="n">__version__</span>
+    <span class="kn">from</span> <span class="nn">.version</span> <span class="kn">import</span> <span class="n">__version__</span> <span class="k">as</span> <span class="n">__version__</span>
 <span class="kn">from</span> <span class="nn">._six</span> <span class="kn">import</span> <span class="n">string_classes</span> <span class="k">as</span> <span class="n">_string_classes</span>
 
 <span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Set</span><span class="p">,</span> <span class="n">Type</span><span class="p">,</span> <span class="n">TYPE_CHECKING</span>
@@ -611,6 +611,19 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
             <span class="k">if</span> <span class="n">name</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">!=</span> <span class="s1">&#39;_&#39;</span> <span class="ow">and</span>
             <span class="ow">not</span> <span class="n">name</span><span class="o">.</span><span class="n">endswith</span><span class="p">(</span><span class="s1">&#39;Base&#39;</span><span class="p">)]</span>
 
+<span class="k">if</span> <span class="ow">not</span> <span class="n">TYPE_CHECKING</span><span class="p">:</span>
+    <span class="c1"># issue 38137 and python issue 43367. Submodules of a C extension are</span>
+    <span class="c1"># non-standard, and attributes of those submodules cannot be pickled since</span>
+    <span class="c1"># pickle expect to be able to import them as &quot;from _C.sub import attr&quot;</span>
+    <span class="c1"># which fails with &quot;_C is not a package</span>
+    <span class="k">for</span> <span class="n">attr</span> <span class="ow">in</span> <span class="nb">dir</span><span class="p">(</span><span class="n">_C</span><span class="p">):</span>
+        <span class="n">candidate</span> <span class="o">=</span> <span class="nb">getattr</span><span class="p">(</span><span class="n">_C</span><span class="p">,</span> <span class="n">attr</span><span class="p">)</span>
+        <span class="k">if</span> <span class="nb">type</span><span class="p">(</span><span class="n">candidate</span><span class="p">)</span> <span class="ow">is</span> <span class="nb">type</span><span class="p">(</span><span class="n">_C</span><span class="p">):</span>
+            <span class="c1"># submodule</span>
+            <span class="k">if</span> <span class="sa">f</span><span class="s1">&#39;torch._C.</span><span class="si">{</span><span class="n">attr</span><span class="si">}</span><span class="s1">&#39;</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">sys</span><span class="o">.</span><span class="n">modules</span><span class="p">:</span>
+                <span class="n">sys</span><span class="o">.</span><span class="n">modules</span><span class="p">[</span><span class="sa">f</span><span class="s1">&#39;torch._C.</span><span class="si">{</span><span class="n">attr</span><span class="si">}</span><span class="s1">&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">candidate</span>
+
+
 <span class="c1">################################################################################</span>
 <span class="c1"># Define basic utilities</span>
 <span class="c1">################################################################################</span>
@@ -997,37 +1010,45 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
 <span class="c1"># Import most common subpackages</span>
 <span class="c1">################################################################################</span>
 
-<span class="kn">import</span> <span class="nn">torch.cuda</span>
-<span class="kn">import</span> <span class="nn">torch.autograd</span>
-<span class="kn">from</span> <span class="nn">torch.autograd</span> <span class="kn">import</span> <span class="n">no_grad</span><span class="p">,</span> <span class="n">enable_grad</span><span class="p">,</span> <span class="n">set_grad_enabled</span>
-<span class="kn">import</span> <span class="nn">torch.fft</span>
-<span class="kn">import</span> <span class="nn">torch.futures</span>
-<span class="kn">import</span> <span class="nn">torch.nn</span>
+<span class="c1"># Use the redundant form so that type checkers know that these are a part of</span>
+<span class="c1"># the public API. The &quot;regular&quot; import lines are there solely for the runtime</span>
+<span class="c1"># side effect of adding to the imported module&#39;s members for other users.</span>
+
+<span class="kn">from</span> <span class="nn">torch</span> <span class="kn">import</span> <span class="n">cuda</span> <span class="k">as</span> <span class="n">cuda</span>
+<span class="kn">from</span> <span class="nn">torch</span> <span class="kn">import</span> <span class="n">autograd</span> <span class="k">as</span> <span class="n">autograd</span>
+<span class="kn">from</span> <span class="nn">torch.autograd</span> <span class="kn">import</span> <span class="p">(</span>
+    <span class="n">no_grad</span> <span class="k">as</span> <span class="n">no_grad</span><span class="p">,</span>
+    <span class="n">enable_grad</span> <span class="k">as</span> <span class="n">enable_grad</span><span class="p">,</span>
+    <span class="n">set_grad_enabled</span> <span class="k">as</span> <span class="n">set_grad_enabled</span><span class="p">,</span>
+<span class="p">)</span>
+<span class="kn">from</span> <span class="nn">torch</span> <span class="kn">import</span> <span class="n">fft</span> <span class="k">as</span> <span class="n">fft</span>
+<span class="kn">from</span> <span class="nn">torch</span> <span class="kn">import</span> <span class="n">futures</span> <span class="k">as</span> <span class="n">futures</span>
+<span class="kn">from</span> <span class="nn">torch</span> <span class="kn">import</span> <span class="n">nn</span> <span class="k">as</span> <span class="n">nn</span>
 <span class="kn">import</span> <span class="nn">torch.nn.intrinsic</span>
 <span class="kn">import</span> <span class="nn">torch.nn.quantizable</span>
 <span class="kn">import</span> <span class="nn">torch.nn.quantized</span>
-<span class="kn">import</span> <span class="nn">torch.optim</span>
+<span class="kn">from</span> <span class="nn">torch</span> <span class="kn">import</span> <span class="n">optim</span> <span class="k">as</span> <span class="n">optim</span>
 <span class="kn">import</span> <span class="nn">torch.optim._multi_tensor</span>
-<span class="kn">import</span> <span class="nn">torch.multiprocessing</span>
-<span class="kn">import</span> <span class="nn">torch.sparse</span>
+<span class="kn">from</span> <span class="nn">torch</span> <span class="kn">import</span> <span class="n">multiprocessing</span> <span class="k">as</span> <span class="n">multiprocessing</span>
+<span class="kn">from</span> <span class="nn">torch</span> <span class="kn">import</span> <span class="n">sparse</span> <span class="k">as</span> <span class="n">sparse</span>
 <span class="kn">import</span> <span class="nn">torch.utils.backcompat</span>
-<span class="kn">import</span> <span class="nn">torch.onnx</span>
-<span class="kn">import</span> <span class="nn">torch.jit</span>
-<span class="kn">import</span> <span class="nn">torch.linalg</span>
-<span class="kn">import</span> <span class="nn">torch.hub</span>
-<span class="kn">import</span> <span class="nn">torch.random</span>
-<span class="kn">import</span> <span class="nn">torch.distributions</span>
-<span class="kn">import</span> <span class="nn">torch.testing</span>
+<span class="kn">from</span> <span class="nn">torch</span> <span class="kn">import</span> <span class="n">onnx</span> <span class="k">as</span> <span class="n">onnx</span>
+<span class="kn">from</span> <span class="nn">torch</span> <span class="kn">import</span> <span class="n">jit</span> <span class="k">as</span> <span class="n">jit</span>
+<span class="kn">from</span> <span class="nn">torch</span> <span class="kn">import</span> <span class="n">linalg</span> <span class="k">as</span> <span class="n">linalg</span>
+<span class="kn">from</span> <span class="nn">torch</span> <span class="kn">import</span> <span class="n">hub</span> <span class="k">as</span> <span class="n">hub</span>
+<span class="kn">from</span> <span class="nn">torch</span> <span class="kn">import</span> <span class="n">random</span> <span class="k">as</span> <span class="n">random</span>
+<span class="kn">from</span> <span class="nn">torch</span> <span class="kn">import</span> <span class="n">distributions</span> <span class="k">as</span> <span class="n">distributions</span>
+<span class="kn">from</span> <span class="nn">torch</span> <span class="kn">import</span> <span class="n">testing</span> <span class="k">as</span> <span class="n">testing</span>
 <span class="kn">import</span> <span class="nn">torch.backends.cuda</span>
 <span class="kn">import</span> <span class="nn">torch.backends.mkl</span>
 <span class="kn">import</span> <span class="nn">torch.backends.mkldnn</span>
 <span class="kn">import</span> <span class="nn">torch.backends.openmp</span>
 <span class="kn">import</span> <span class="nn">torch.backends.quantized</span>
-<span class="kn">import</span> <span class="nn">torch.quantization</span>
+<span class="kn">from</span> <span class="nn">torch</span> <span class="kn">import</span> <span class="n">quantization</span> <span class="k">as</span> <span class="n">quantization</span>
 <span class="kn">import</span> <span class="nn">torch.utils.data</span>
-<span class="kn">import</span> <span class="nn">torch.__config__</span>
-<span class="kn">import</span> <span class="nn">torch.__future__</span>
-<span class="kn">import</span> <span class="nn">torch.profiler</span>
+<span class="kn">from</span> <span class="nn">torch</span> <span class="kn">import</span> <span class="n">__config__</span> <span class="k">as</span> <span class="n">__config__</span>
+<span class="kn">from</span> <span class="nn">torch</span> <span class="kn">import</span> <span class="n">__future__</span> <span class="k">as</span> <span class="n">__future__</span>
+<span class="kn">from</span> <span class="nn">torch</span> <span class="kn">import</span> <span class="n">profiler</span> <span class="k">as</span> <span class="n">profiler</span>
 
 <span class="n">_C</span><span class="o">.</span><span class="n">_init_names</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">_storage_classes</span><span class="p">))</span>
 
@@ -1042,11 +1063,11 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
 
 
 <span class="c1"># Import the ops &quot;namespace&quot;</span>
-<span class="kn">from</span> <span class="nn">torch._ops</span> <span class="kn">import</span> <span class="n">ops</span>
-<span class="kn">from</span> <span class="nn">torch._classes</span> <span class="kn">import</span> <span class="n">classes</span>
+<span class="kn">from</span> <span class="nn">torch._ops</span> <span class="kn">import</span> <span class="n">ops</span> <span class="k">as</span> <span class="n">ops</span>
+<span class="kn">from</span> <span class="nn">torch._classes</span> <span class="kn">import</span> <span class="n">classes</span> <span class="k">as</span> <span class="n">classes</span>
 
 <span class="c1"># Import the quasi random sampler</span>
-<span class="kn">import</span> <span class="nn">torch.quasirandom</span>
+<span class="kn">from</span> <span class="nn">torch</span> <span class="kn">import</span> <span class="n">quasirandom</span> <span class="k">as</span> <span class="n">quasirandom</span>
 
 <span class="c1"># If you are seeing this, it means that this call site was not checked if</span>
 <span class="c1"># the memory format could be preserved, and it was switched to old default</span>
@@ -1060,9 +1081,9 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
 
 <span class="c1"># Import tools that require fully imported torch (for applying</span>
 <span class="c1"># torch.jit.script as a decorator, for instance):</span>
-<span class="kn">from</span> <span class="nn">._lobpcg</span> <span class="kn">import</span> <span class="n">lobpcg</span>
+<span class="kn">from</span> <span class="nn">._lobpcg</span> <span class="kn">import</span> <span class="n">lobpcg</span> <span class="k">as</span> <span class="n">lobpcg</span>
 
-<span class="kn">from</span> <span class="nn">._vmap_internals</span> <span class="kn">import</span> <span class="n">vmap</span>
+<span class="kn">from</span> <span class="nn">._vmap_internals</span> <span class="kn">import</span> <span class="n">vmap</span> <span class="k">as</span> <span class="n">vmap</span>
 
 <span class="c1"># These were previously defined in native_functions.yaml and appeared on the</span>
 <span class="c1"># `torch` namespace, but we moved them to c10 dispatch to facilitate custom</span>

docs/master/_modules/torch/__config__.html

@@ -188,7 +188,7 @@
 
 
                 <div class="version">
-                  master (1.9.0a0+git715835c )
+                  master (1.9.0a0+gitcc88ac8 )
                 </div>
 
 

docs/master/_modules/torch/_jit_internal.html

@@ -188,7 +188,7 @@
 
 
                 <div class="version">
-                  master (1.9.0a0+git715835c )
+                  master (1.9.0a0+gitcc88ac8 )
                 </div>
 
 

docs/master/_modules/torch/_lobpcg.html

@@ -188,7 +188,7 @@
 
 
                 <div class="version">
-                  master (1.9.0a0+git715835c )
+                  master (1.9.0a0+gitcc88ac8 )
                 </div>
 
 

docs/master/_modules/torch/_lowrank.html

@@ -188,7 +188,7 @@
 
 
                 <div class="version">
-                  master (1.9.0a0+git715835c )
+                  master (1.9.0a0+gitcc88ac8 )
                 </div>
 
 

docs/master/_modules/torch/_tensor_str.html

@@ -188,7 +188,7 @@
 
 
                 <div class="version">
-                  master (1.9.0a0+git715835c )
+                  master (1.9.0a0+gitcc88ac8 )
                 </div>
 
 

docs/master/_modules/torch/_utils.html

@@ -188,7 +188,7 @@
 
 
                 <div class="version">
-                  master (1.9.0a0+git715835c )
+                  master (1.9.0a0+gitcc88ac8 )
                 </div>
 
 

docs/master/_modules/torch/_vmap_internals.html

@@ -188,7 +188,7 @@
 
 
                 <div class="version">
-                  master (1.9.0a0+git715835c )
+                  master (1.9.0a0+gitcc88ac8 )
                 </div>