Update homepage ticker for 1.12

_news/news-item-1.md

@@ -1,5 +1,5 @@
 ---
 order: 1
-link: https://pytorch.org/blog/pytorch-1.11-released
-summary: NEW! PyTorch 1.11, TorchData, and functorch are now available
+link: https://pytorch.org/blog/pytorch-1.12-released/
+summary: "New release! PyTorch 1.12: TorchArrow, Functional API for Modules and nvFuser are now available!"
 ---

_news/news-item-2.md

@@ -1,5 +1,5 @@
 ---
 order: 2
-link: https://pytorch.org/blog/pytorch-1.11-new-library-releases
-summary: NEW! Introducing TorchRec, and other domain library updates in PyTorch 1.11
+link: https://pytorch.org/blog/pytorch-1.12-new-library-releases/
+summary: New libraries updates in PyTorch 1.12
 ---

docs/master/_sources/generated/torch.cuda.stream.rst.txt

@@ -1,6 +1,13 @@
-torch.cuda.stream
-=================
-
+.. role:: hidden
+    :class: hidden-section
 .. currentmodule:: torch.cuda
 
-.. autofunction:: stream
+
+Stream
+======
+
+.. autoclass:: Stream
+    :inherited-members:
+    :members:
+
+.. autogenerated from source/_templates/autosummary/class.rst

docs/master/_sources/generated/torch.nn.utils.prune.identity.rst.txt

@@ -1,6 +1,13 @@
-torch.nn.utils.prune.identity
-=============================
-
+.. role:: hidden
+    :class: hidden-section
 .. currentmodule:: torch.nn.utils.prune
 
-.. autofunction:: identity
+
+Identity
+========
+
+.. autoclass:: Identity
+    :inherited-members:
+    :members:
+
+.. autogenerated from source/_templates/autosummary/class.rst

docs/master/generated/torch.cuda.stream.html

@@ -10,14 +10,14 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
 
-  <title>torch.cuda.stream &mdash; PyTorch master documentation</title>
+  <title>Stream &mdash; PyTorch master documentation</title>
 
 
 
 
 
 
-    <link rel="canonical" href="https://pytorch.org/docs/stable/generated/torch.cuda.stream.html"/>
+    <link rel="canonical" href="https://pytorch.org/docs/stable/generated/torch.cuda.Stream.html"/>
 
 
 
@@ -41,8 +41,8 @@
   <link rel="stylesheet" href="../_static/css/jit.css" type="text/css" />
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+    <link rel="next" title="ExternalStream" href="torch.cuda.ExternalStream.html" />
+    <link rel="prev" title="torch.cuda.comm.gather" href="torch.cuda.comm.gather.html" />
 
 <!--
   Search engines should not index the master version of documentation.
@@ -242,7 +242,7 @@
 
 
 <div>
-  <a style="color:#F05732" href="https://pytorch.org/docs/stable/generated/torch.cuda.stream.html">
+  <a style="color:#F05732" href="https://pytorch.org/docs/stable/generated/torch.cuda.Stream.html">
     You are viewing unstable developer preview docs.
     Click here to view docs for latest stable release.
   </a>
@@ -397,13 +397,13 @@
 
           <li><a href="../cuda.html">torch.cuda</a> &gt;</li>
 
-      <li>torch.cuda.stream</li>
+      <li>Stream</li>
 
 
       <li class="pytorch-breadcrumbs-aside">
 
 
-            <a href="../_sources/generated/torch.cuda.stream.rst.txt" rel="nofollow"><img src="../_static/images/view-page-source-icon.svg"></a>
+            <a href="../_sources/generated/torch.cuda.Stream.rst.txt" rel="nofollow"><img src="../_static/images/view-page-source-icon.svg"></a>
 
 
       </li>
@@ -429,21 +429,105 @@
             <div role="main" class="main-content" itemscope="itemscope" itemtype="http://schema.org/Article">
              <article itemprop="articleBody" id="pytorch-article" class="pytorch-article">
 
-  <section id="torch-cuda-stream">
-<h1>torch.cuda.stream<a class="headerlink" href="#torch-cuda-stream" title="Permalink to this heading">¶</a></h1>
-<dl class="py function">
-<dt class="sig sig-object py" id="torch.cuda.stream">
-<span class="sig-prename descclassname"><span class="pre">torch.cuda.</span></span><span class="sig-name descname"><span class="pre">stream</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">stream</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/torch/cuda.html#stream"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torch.cuda.stream" title="Permalink to this definition">¶</a></dt>
-<dd><p>Wrapper around the Context-manager StreamContext that
-selects a given stream.</p>
+  <section id="stream">
+<h1>Stream<a class="headerlink" href="#stream" title="Permalink to this heading">¶</a></h1>
+<dl class="py class">
+<dt class="sig sig-object py" id="torch.cuda.Stream">
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">torch.cuda.</span></span><span class="sig-name descname"><span class="pre">Stream</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">device</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">priority</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/torch/cuda/streams.html#Stream"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torch.cuda.Stream" title="Permalink to this definition">¶</a></dt>
+<dd><p>Wrapper around a CUDA stream.</p>
+<p>A CUDA stream is a linear sequence of execution that belongs to a specific
+device, independent from other streams.  See <a class="reference internal" href="../notes/cuda.html#cuda-semantics"><span class="std std-ref">CUDA semantics</span></a> for
+details.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
-<dd class="field-odd"><p><strong>stream</strong> (<a class="reference internal" href="torch.cuda.Stream.html#torch.cuda.Stream" title="torch.cuda.Stream"><em>Stream</em></a>) – selected stream. This manager is a no-op if it’s
-<code class="docutils literal notranslate"><span class="pre">None</span></code>.</p>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>device</strong> (<a class="reference internal" href="../tensor_attributes.html#torch.device" title="torch.device"><em>torch.device</em></a><em> or </em><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><em>int</em></a><em>, </em><em>optional</em>) – a device on which to allocate
+the stream. If <a class="reference internal" href="torch.cuda.device.html#torch.cuda.device" title="torch.cuda.device"><code class="xref py py-attr docutils literal notranslate"><span class="pre">device</span></code></a> is <code class="docutils literal notranslate"><span class="pre">None</span></code> (default) or a negative
+integer, this will use the current device.</p></li>
+<li><p><strong>priority</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><em>int</em></a><em>, </em><em>optional</em>) – priority of the stream. Can be either
+-1 (high priority) or 0 (low priority). By default, streams have
+priority 0.</p></li>
+</ul>
+</dd>
+</dl>
+<div class="admonition note">
+<p class="admonition-title">Note</p>
+<p>Although CUDA versions &gt;= 11 support more than two levels of
+priorities, in PyTorch, we only support two levels of priorities.</p>
+</div>
+<dl class="py method">
+<dt class="sig sig-object py" id="torch.cuda.Stream.query">
+<span class="sig-name descname"><span class="pre">query</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../_modules/torch/cuda/streams.html#Stream.query"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torch.cuda.Stream.query" title="Permalink to this definition">¶</a></dt>
+<dd><p>Checks if all the work submitted has been completed.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Returns<span class="colon">:</span></dt>
+<dd class="field-odd"><p>A boolean indicating if all kernels in this stream are completed.</p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="torch.cuda.Stream.record_event">
+<span class="sig-name descname"><span class="pre">record_event</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">event</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/torch/cuda/streams.html#Stream.record_event"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torch.cuda.Stream.record_event" title="Permalink to this definition">¶</a></dt>
+<dd><p>Records an event.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><p><strong>event</strong> (<a class="reference internal" href="torch.cuda.Event.html#torch.cuda.Event" title="torch.cuda.Event"><em>torch.cuda.Event</em></a><em>, </em><em>optional</em>) – event to record. If not given, a new one
+will be allocated.</p>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Recorded event.</p>
 </dd>
 </dl>
-<p>..Note:: In eager mode stream is of type Stream class while in JIT it is
-an object of the custom class <code class="docutils literal notranslate"><span class="pre">torch.classes.cuda.Stream</span></code>.</p>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="torch.cuda.Stream.synchronize">
+<span class="sig-name descname"><span class="pre">synchronize</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../_modules/torch/cuda/streams.html#Stream.synchronize"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torch.cuda.Stream.synchronize" title="Permalink to this definition">¶</a></dt>
+<dd><p>Wait for all the kernels in this stream to complete.</p>
+<div class="admonition note">
+<p class="admonition-title">Note</p>
+<p>This is a wrapper around <code class="docutils literal notranslate"><span class="pre">cudaStreamSynchronize()</span></code>: see
+<a class="reference external" href="https://docs.nvidia.com/cuda/cuda-runtime-api/group__CUDART__STREAM.html">CUDA Stream documentation</a> for more info.</p>
+</div>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="torch.cuda.Stream.wait_event">
+<span class="sig-name descname"><span class="pre">wait_event</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">event</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/torch/cuda/streams.html#Stream.wait_event"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torch.cuda.Stream.wait_event" title="Permalink to this definition">¶</a></dt>
+<dd><p>Makes all future work submitted to the stream wait for an event.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><p><strong>event</strong> (<a class="reference internal" href="torch.cuda.Event.html#torch.cuda.Event" title="torch.cuda.Event"><em>torch.cuda.Event</em></a>) – an event to wait for.</p>
+</dd>
+</dl>
+<div class="admonition note">
+<p class="admonition-title">Note</p>
+<p>This is a wrapper around <code class="docutils literal notranslate"><span class="pre">cudaStreamWaitEvent()</span></code>: see
+<a class="reference external" href="https://docs.nvidia.com/cuda/cuda-runtime-api/group__CUDART__STREAM.html">CUDA Stream documentation</a> for more info.</p>
+<p>This function returns without waiting for <code class="xref py py-attr docutils literal notranslate"><span class="pre">event</span></code>: only future
+operations are affected.</p>
+</div>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="torch.cuda.Stream.wait_stream">
+<span class="sig-name descname"><span class="pre">wait_stream</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">stream</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/torch/cuda/streams.html#Stream.wait_stream"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torch.cuda.Stream.wait_stream" title="Permalink to this definition">¶</a></dt>
+<dd><p>Synchronizes with another stream.</p>
+<p>All future work submitted to this stream will wait until all kernels
+submitted to a given stream at the time of call complete.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><p><strong>stream</strong> (<a class="reference internal" href="#torch.cuda.Stream" title="torch.cuda.Stream"><em>Stream</em></a>) – a stream to synchronize.</p>
+</dd>
+</dl>
+<div class="admonition note">
+<p class="admonition-title">Note</p>
+<p>This function returns without waiting for currently enqueued
+kernels in <a class="reference internal" href="torch.cuda.stream.html#torch.cuda.stream" title="torch.cuda.stream"><code class="xref py py-attr docutils literal notranslate"><span class="pre">stream</span></code></a>: only future operations are affected.</p>
+</div>
+</dd></dl>
+
 </dd></dl>
 
 </section>
@@ -456,10 +540,10 @@ <h1>torch.cuda.stream<a class="headerlink" href="#torch-cuda-stream" title="Perm
 
     <div class="rst-footer-buttons" role="navigation" aria-label="footer navigation">
 
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@@ -491,7 +575,7 @@ <h1>torch.cuda.stream<a class="headerlink" href="#torch-cuda-stream" title="Perm
           <div class="pytorch-right-menu" id="pytorch-right-menu">
             <div class="pytorch-side-scroll" id="pytorch-side-scroll-right">
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-<li><a class="reference internal" href="#">torch.cuda.stream</a></li>
+<li><a class="reference internal" href="#">Stream</a></li>
 </ul>
 
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