Generate Python docs from pytorch/pytorch@145a20b

Author: pytorchbot

docs/master/__config__.html

@@ -193,7 +193,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.10.0a0+git7fce0bb ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.10.0a0+git145a20b ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/index.html

@@ -192,7 +192,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.10.0a0+git7fce0bb ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.10.0a0+git145a20b ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/torch.html

@@ -192,7 +192,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.10.0a0+git7fce0bb ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.10.0a0+git145a20b ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/torch/__config__.html

@@ -192,7 +192,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.10.0a0+git7fce0bb ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.10.0a0+git145a20b ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/torch/_jit_internal.html

@@ -192,7 +192,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.10.0a0+git7fce0bb ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.10.0a0+git145a20b ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/torch/_lobpcg.html

@@ -192,7 +192,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.10.0a0+git7fce0bb ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.10.0a0+git145a20b ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/torch/_lowrank.html

@@ -192,7 +192,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.10.0a0+git7fce0bb ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.10.0a0+git145a20b ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/torch/_tensor.html

@@ -192,7 +192,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.10.0a0+git7fce0bb ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.10.0a0+git145a20b ) &#x25BC</a>
     </div>
 
 
@@ -526,6 +526,16 @@ <h1>Source code for torch._tensor</h1><div class="highlight"><pre>
                        <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">device</span><span class="p">),</span>
                        <span class="bp">self</span><span class="o">.</span><span class="n">requires_grad</span><span class="p">)</span>
             <span class="k">return</span> <span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">_utils</span><span class="o">.</span><span class="n">_rebuild_mlc_tensor</span><span class="p">,</span> <span class="n">arg_mlc</span><span class="p">)</span>
+        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">device</span><span class="o">.</span><span class="n">type</span> <span class="o">==</span> <span class="s1">&#39;meta&#39;</span><span class="p">:</span>
+            <span class="c1"># NB: This implementation BREAKS storage sharing.  Current</span>
+            <span class="c1"># hypothesis is that no one cares for meta tensors.</span>
+            <span class="n">arg_meta</span> <span class="o">=</span> <span class="p">(</span>
+                <span class="bp">self</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span>
+                <span class="nb">tuple</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">size</span><span class="p">()),</span>
+                <span class="bp">self</span><span class="o">.</span><span class="n">stride</span><span class="p">(),</span>
+                <span class="bp">self</span><span class="o">.</span><span class="n">requires_grad</span><span class="p">,</span>
+            <span class="p">)</span>
+            <span class="k">return</span> <span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">_utils</span><span class="o">.</span><span class="n">_rebuild_meta_tensor_no_storage</span><span class="p">,</span> <span class="n">arg_meta</span><span class="p">)</span>
         <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">is_quantized</span><span class="p">:</span>
             <span class="c1"># quantizer_params can be different type based on torch attribute</span>
             <span class="n">quantizer_params</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="n">Tuple</span><span class="p">[</span><span class="n">torch</span><span class="o">.</span><span class="n">qscheme</span><span class="p">,</span> <span class="nb">float</span><span class="p">,</span> <span class="nb">int</span><span class="p">],</span> <span class="n">Tuple</span><span class="p">[</span><span class="n">Any</span><span class="p">,</span> <span class="n">Tensor</span><span class="p">,</span> <span class="n">Tensor</span><span class="p">,</span> <span class="nb">int</span><span class="p">]]</span>
@@ -595,7 +605,7 @@ <h1>Source code for torch._tensor</h1><div class="highlight"><pre>
         <span class="c1"># All strings are unicode in Python 3.</span>
         <span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">_tensor_str</span><span class="o">.</span><span class="n">_str</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span>
 
-<div class="viewcode-block" id="Tensor.backward"><a class="viewcode-back" href="../../generated/torch.Tensor.backward.html#torch.Tensor.backward">[docs]</a>    <span class="k">def</span> <span class="nf">backward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">gradient</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">retain_graph</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">create_graph</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">inputs</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
+    <span class="k">def</span> <span class="nf">backward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">gradient</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">retain_graph</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">create_graph</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">inputs</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
         <span class="sa">r</span><span class="sd">&quot;&quot;&quot;Computes the gradient of current tensor w.r.t. graph leaves.</span>
 
 <span class="sd">        The graph is differentiated using the chain rule. If the tensor is</span>
@@ -651,7 +661,7 @@ <h1>Source code for torch._tensor</h1><div class="highlight"><pre>
                 <span class="n">retain_graph</span><span class="o">=</span><span class="n">retain_graph</span><span class="p">,</span>
                 <span class="n">create_graph</span><span class="o">=</span><span class="n">create_graph</span><span class="p">,</span>
                 <span class="n">inputs</span><span class="o">=</span><span class="n">inputs</span><span class="p">)</span>
-        <span class="n">torch</span><span class="o">.</span><span class="n">autograd</span><span class="o">.</span><span class="n">backward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">gradient</span><span class="p">,</span> <span class="n">retain_graph</span><span class="p">,</span> <span class="n">create_graph</span><span class="p">,</span> <span class="n">inputs</span><span class="o">=</span><span class="n">inputs</span><span class="p">)</span></div>
+        <span class="n">torch</span><span class="o">.</span><span class="n">autograd</span><span class="o">.</span><span class="n">backward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">gradient</span><span class="p">,</span> <span class="n">retain_graph</span><span class="p">,</span> <span class="n">create_graph</span><span class="p">,</span> <span class="n">inputs</span><span class="o">=</span><span class="n">inputs</span><span class="p">)</span>
 
     <span class="k">def</span> <span class="nf">register_hook</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">hook</span><span class="p">):</span>
         <span class="sa">r</span><span class="sd">&quot;&quot;&quot;Registers a backward hook.</span>

docs/master/_modules/torch/_tensor_str.html

@@ -192,7 +192,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.10.0a0+git7fce0bb ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.10.0a0+git145a20b ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/torch/_utils.html

@@ -192,7 +192,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.10.0a0+git7fce0bb ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.10.0a0+git145a20b ) &#x25BC</a>
     </div>
 
 
@@ -575,6 +575,10 @@ <h1>Source code for torch._utils</h1><div class="highlight"><pre>
     <span class="k">return</span> <span class="n">tensor</span>
 
 
+<span class="k">def</span> <span class="nf">_rebuild_meta_tensor_no_storage</span><span class="p">(</span><span class="n">dtype</span><span class="p">,</span> <span class="n">size</span><span class="p">,</span> <span class="n">stride</span><span class="p">,</span> <span class="n">requires_grad</span><span class="p">):</span>
+    <span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">empty_strided</span><span class="p">(</span><span class="n">size</span><span class="p">,</span> <span class="n">stride</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">,</span> <span class="n">device</span><span class="o">=</span><span class="s1">&#39;meta&#39;</span><span class="p">,</span> <span class="n">requires_grad</span><span class="o">=</span><span class="n">requires_grad</span><span class="p">)</span>
+
+
 <span class="k">def</span> <span class="nf">_rebuild_qtensor</span><span class="p">(</span><span class="n">storage</span><span class="p">,</span> <span class="n">storage_offset</span><span class="p">,</span> <span class="n">size</span><span class="p">,</span> <span class="n">stride</span><span class="p">,</span> <span class="n">quantizer_params</span><span class="p">,</span> <span class="n">requires_grad</span><span class="p">,</span> <span class="n">backward_hooks</span><span class="p">):</span>
     <span class="n">qscheme</span> <span class="o">=</span> <span class="n">quantizer_params</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
     <span class="k">if</span> <span class="n">qscheme</span> <span class="o">==</span> <span class="n">torch</span><span class="o">.</span><span class="n">per_tensor_affine</span><span class="p">:</span>