Generate Python docs from pytorch/pytorch@a21f2ab

Author: pytorchbot

docs/master/__config__.html

@@ -194,7 +194,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+git125a559 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+gita21f2ab ) &#x25BC</a>
     </div>
 
 

docs/master/_images/RReLU.png

@@ -193,7 +193,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+git125a559 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+gita21f2ab ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/index.html

@@ -193,7 +193,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+git125a559 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+gita21f2ab ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/torch.html

@@ -193,7 +193,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+git125a559 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+gita21f2ab ) &#x25BC</a>
     </div>
 
 
@@ -900,7 +900,7 @@ <h1>Source code for torch._jit_internal</h1><div class="highlight"><pre>
     <span class="k">return</span> <span class="n">fn</span></div>
 
 
-<div class="viewcode-block" id="unused"><a class="viewcode-back" href="../../generated/torch.jit.unused.html#torch.jit.unused">[docs]</a><span class="k">def</span> <span class="nf">unused</span><span class="p">(</span><span class="n">fn</span><span class="p">):</span>
+<span class="k">def</span> <span class="nf">unused</span><span class="p">(</span><span class="n">fn</span><span class="p">):</span>
     <span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    This decorator indicates to the compiler that a function or method should</span>
 <span class="sd">    be ignored and replaced with the raising of an exception. This allows you</span>
@@ -947,7 +947,7 @@ <h1>Source code for torch._jit_internal</h1><div class="highlight"><pre>
         <span class="k">return</span> <span class="n">prop</span>
 
     <span class="n">fn</span><span class="o">.</span><span class="n">_torchscript_modifier</span> <span class="o">=</span> <span class="n">FunctionModifiers</span><span class="o">.</span><span class="n">UNUSED</span>
-    <span class="k">return</span> <span class="n">fn</span></div>
+    <span class="k">return</span> <span class="n">fn</span>
 
 <span class="c1"># No op context manager from python side</span>
 <span class="k">class</span> <span class="nc">_IgnoreContextManager</span><span class="p">(</span><span class="n">contextlib</span><span class="o">.</span><span class="n">AbstractContextManager</span><span class="p">):</span>

docs/master/_modules/torch/__config__.html

@@ -193,7 +193,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+git125a559 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+gita21f2ab ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/torch/_jit_internal.html

@@ -193,7 +193,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+git125a559 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+gita21f2ab ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/torch/_lobpcg.html

@@ -193,7 +193,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+git125a559 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+gita21f2ab ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/torch/_lowrank.html

@@ -193,7 +193,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+git125a559 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+gita21f2ab ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/torch/_tensor.html

@@ -193,7 +193,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+git125a559 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+gita21f2ab ) &#x25BC</a>
     </div>
 
 
@@ -479,8 +479,8 @@ <h1>Source code for torch._vmap_internals</h1><div class="highlight"><pre>
 <span class="c1"># Undos the batching (and any batch dimensions) associated with the `vmap_level`.</span>
 <span class="k">def</span> <span class="nf">_unwrap_batched</span><span class="p">(</span>
         <span class="n">batched_outputs</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="n">Tensor</span><span class="p">,</span> <span class="n">Tuple</span><span class="p">[</span><span class="n">Tensor</span><span class="p">,</span> <span class="o">...</span><span class="p">]],</span>
-        <span class="n">out_dims</span><span class="p">:</span> <span class="n">out_dims_t</span><span class="p">,</span>
-        <span class="n">vmap_level</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">func</span><span class="p">:</span> <span class="n">Callable</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Tuple</span><span class="p">:</span>
+        <span class="n">out_dims</span><span class="p">:</span> <span class="n">out_dims_t</span><span class="p">,</span> <span class="n">vmap_level</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">func</span><span class="p">:</span> <span class="n">Callable</span><span class="p">,</span>
+        <span class="n">allow_none_pass_through</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Tuple</span><span class="p">:</span>
     <span class="n">num_outputs</span> <span class="o">=</span> <span class="n">_num_outputs</span><span class="p">(</span><span class="n">batched_outputs</span><span class="p">)</span>
     <span class="n">out_dims_as_tuple</span> <span class="o">=</span> <span class="n">_as_tuple</span><span class="p">(</span>
         <span class="n">out_dims</span><span class="p">,</span> <span class="n">num_outputs</span><span class="p">,</span>
@@ -493,8 +493,12 @@ <h1>Source code for torch._vmap_internals</h1><div class="highlight"><pre>
     <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">batched_outputs</span><span class="p">,</span> <span class="n">Tensor</span><span class="p">):</span>
         <span class="n">out_dim</span> <span class="o">=</span> <span class="n">out_dims_as_tuple</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
         <span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">_remove_batch_dim</span><span class="p">(</span><span class="n">batched_outputs</span><span class="p">,</span> <span class="n">vmap_level</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">,</span> <span class="n">out_dim</span><span class="p">)</span>  <span class="c1"># type: ignore[return-value]</span>
-    <span class="k">return</span> <span class="nb">tuple</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">_remove_batch_dim</span><span class="p">(</span><span class="n">out</span><span class="p">,</span> <span class="n">vmap_level</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">,</span> <span class="n">out_dim</span><span class="p">)</span>
-                 <span class="k">for</span> <span class="n">out</span><span class="p">,</span> <span class="n">out_dim</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">batched_outputs</span><span class="p">,</span> <span class="n">out_dims_as_tuple</span><span class="p">))</span>
+    <span class="k">if</span> <span class="n">allow_none_pass_through</span><span class="p">:</span>
+        <span class="k">return</span> <span class="nb">tuple</span><span class="p">((</span><span class="n">torch</span><span class="o">.</span><span class="n">_remove_batch_dim</span><span class="p">(</span><span class="n">out</span><span class="p">,</span> <span class="n">vmap_level</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">,</span> <span class="n">out_dim</span><span class="p">)</span> <span class="k">if</span> <span class="n">out</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span> <span class="k">else</span> <span class="kc">None</span><span class="p">)</span>
+                     <span class="k">for</span> <span class="n">out</span><span class="p">,</span> <span class="n">out_dim</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">batched_outputs</span><span class="p">,</span> <span class="n">out_dims_as_tuple</span><span class="p">))</span>
+    <span class="k">else</span><span class="p">:</span>
+        <span class="k">return</span> <span class="nb">tuple</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">_remove_batch_dim</span><span class="p">(</span><span class="n">out</span><span class="p">,</span> <span class="n">vmap_level</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">,</span> <span class="n">out_dim</span><span class="p">)</span>
+                     <span class="k">for</span> <span class="n">out</span><span class="p">,</span> <span class="n">out_dim</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">batched_outputs</span><span class="p">,</span> <span class="n">out_dims_as_tuple</span><span class="p">))</span>
 
 <span class="c1"># Checks that `fn` returned one or more Tensors and nothing else.</span>
 <span class="c1"># NB: A python function that return multiple arguments returns a single tuple,</span>
@@ -645,16 +649,22 @@ <h1>Source code for torch._vmap_internals</h1><div class="highlight"><pre>
     <span class="k">return</span> <span class="n">_vmap</span><span class="p">(</span><span class="n">func</span><span class="p">,</span> <span class="n">in_dims</span><span class="p">,</span> <span class="n">out_dims</span><span class="p">)</span></div>
 
 <span class="c1"># A version of vmap but without the initial &quot;experimental prototype&quot; warning</span>
-<span class="k">def</span> <span class="nf">_vmap</span><span class="p">(</span><span class="n">func</span><span class="p">:</span> <span class="n">Callable</span><span class="p">,</span> <span class="n">in_dims</span><span class="p">:</span> <span class="n">in_dims_t</span> <span class="o">=</span> <span class="mi">0</span><span class="p">,</span> <span class="n">out_dims</span><span class="p">:</span> <span class="n">out_dims_t</span> <span class="o">=</span> <span class="mi">0</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Callable</span><span class="p">:</span>
+<span class="k">def</span> <span class="nf">_vmap</span><span class="p">(</span><span class="n">func</span><span class="p">:</span> <span class="n">Callable</span><span class="p">,</span> <span class="n">in_dims</span><span class="p">:</span> <span class="n">in_dims_t</span> <span class="o">=</span> <span class="mi">0</span><span class="p">,</span> <span class="n">out_dims</span><span class="p">:</span> <span class="n">out_dims_t</span> <span class="o">=</span> <span class="mi">0</span><span class="p">,</span> <span class="n">allow_none_pass_through</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Callable</span><span class="p">:</span>
+    <span class="c1"># The `allow_none_pass_through` argument is a temporary workaround may be removed.</span>
+    <span class="c1"># Currently it enables us to wrap the call in `autograd.grad` to the autograd engine,</span>
+    <span class="c1"># which may return None if any of the inputs are unused. See the issue discussing this:</span>
+    <span class="c1"># https://github.com/facebookresearch/functorch/issues/159.</span>
     <span class="nd">@functools</span><span class="o">.</span><span class="n">wraps</span><span class="p">(</span><span class="n">func</span><span class="p">)</span>
     <span class="k">def</span> <span class="nf">wrapped</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">):</span>
         <span class="n">_check_out_dims_is_int_or_int_tuple</span><span class="p">(</span><span class="n">out_dims</span><span class="p">,</span> <span class="n">func</span><span class="p">)</span>
         <span class="n">vmap_level</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">_C</span><span class="o">.</span><span class="n">_vmapmode_increment_nesting</span><span class="p">()</span>
         <span class="k">try</span><span class="p">:</span>
             <span class="n">batched_inputs</span><span class="p">,</span> <span class="n">batch_size</span> <span class="o">=</span> <span class="n">_create_batched_inputs</span><span class="p">(</span><span class="n">in_dims</span><span class="p">,</span> <span class="n">args</span><span class="p">,</span> <span class="n">vmap_level</span><span class="p">,</span> <span class="n">func</span><span class="p">)</span>
             <span class="n">batched_outputs</span> <span class="o">=</span> <span class="n">func</span><span class="p">(</span><span class="o">*</span><span class="n">batched_inputs</span><span class="p">)</span>
-            <span class="n">_validate_outputs</span><span class="p">(</span><span class="n">batched_outputs</span><span class="p">,</span> <span class="n">func</span><span class="p">)</span>
-            <span class="k">return</span> <span class="n">_unwrap_batched</span><span class="p">(</span><span class="n">batched_outputs</span><span class="p">,</span> <span class="n">out_dims</span><span class="p">,</span> <span class="n">vmap_level</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">,</span> <span class="n">func</span><span class="p">)</span>
+            <span class="k">if</span> <span class="ow">not</span> <span class="n">allow_none_pass_through</span><span class="p">:</span>
+                <span class="n">_validate_outputs</span><span class="p">(</span><span class="n">batched_outputs</span><span class="p">,</span> <span class="n">func</span><span class="p">)</span>
+            <span class="k">return</span> <span class="n">_unwrap_batched</span><span class="p">(</span><span class="n">batched_outputs</span><span class="p">,</span> <span class="n">out_dims</span><span class="p">,</span> <span class="n">vmap_level</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">,</span> <span class="n">func</span><span class="p">,</span>
+                                   <span class="n">allow_none_pass_through</span><span class="o">=</span><span class="n">allow_none_pass_through</span><span class="p">)</span>
         <span class="k">finally</span><span class="p">:</span>
             <span class="n">torch</span><span class="o">.</span><span class="n">_C</span><span class="o">.</span><span class="n">_vmapmode_decrement_nesting</span><span class="p">()</span>
     <span class="k">return</span> <span class="n">wrapped</span>

docs/master/_modules/torch/_tensor_str.html

@@ -193,7 +193,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+git125a559 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+gita21f2ab ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/torch/_utils.html

@@ -193,7 +193,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+git125a559 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+gita21f2ab ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/torch/_vmap_internals.html

@@ -193,7 +193,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+git125a559 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+gita21f2ab ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/torch/ao/quantization/fake_quantize.html

@@ -193,7 +193,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+git125a559 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+gita21f2ab ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/torch/ao/quantization/fuse_modules.html

@@ -193,7 +193,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+git125a559 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+gita21f2ab ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/torch/ao/quantization/observer.html

@@ -193,7 +193,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+git125a559 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+gita21f2ab ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/torch/ao/quantization/qconfig.html

@@ -193,7 +193,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+git125a559 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+gita21f2ab ) &#x25BC</a>
     </div>