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<div class="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.Stream">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">torch.</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></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">priority</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#torch.Stream" title="Permalink to this definition">¶</a></dt>
<dd><p>An in-order queue of executing the respective tasks asynchronously in first in first out (FIFO) order.
It can control or synchronize the execution of other Stream or block the current host thread to ensure
the correct task sequencing. It supports with statement as a context manager to ensure the operators
within the with block are running on the corresponding stream.</p>
<p>See in-depth description of the CUDA behavior at <a class="reference internal" href="../notes/cuda.html#cuda-semantics"><span class="std std-ref">CUDA semantics</span></a> for details
on the exact semantic that applies to all devices.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<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"><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.device</span></code></a>, optional) – the desired device for the Stream.
If not given, the current <a class="reference internal" href="../torch.html#accelerators"><span class="std std-ref">accelerator</span></a> type will be used.</p></li>
<li><p><strong>priority</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.13)"><em>int</em></a><em>, </em><em>optional</em>) – priority of the stream, should be 0 or negative, where negative
numbers indicate higher priority. By default, streams have priority 0.</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>An torch.Stream object.</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p><a class="reference internal" href="#torch.Stream" title="torch.Stream">Stream</a></p>
</dd>
</dl>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="k">with</span> <span class="n">torch</span><span class="o">.</span><span class="n">Stream</span><span class="p">(</span><span class="n">device</span><span class="o">=</span><span class="s1">'cuda'</span><span class="p">)</span> <span class="k">as</span> <span class="n">s_cuda</span><span class="p">:</span>
<span class="gp">>>> </span> <span class="n">a</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="n">device</span><span class="o">=</span><span class="s1">'cuda'</span><span class="p">)</span>
<span class="gp">>>> </span> <span class="n">b</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">5</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="n">device</span><span class="o">=</span><span class="s1">'cuda'</span><span class="p">)</span>
<span class="gp">>>> </span> <span class="n">c</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">mm</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">)</span>
</pre></div>
</div>
<dl class="py method">
<dt class="sig sig-object py" id="torch.Stream.query">
<span class="sig-name descname"><span class="pre">query</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.13)"><span class="pre">bool</span></a></span></span><a class="headerlink" href="#torch.Stream.query" title="Permalink to this definition">¶</a></dt>
<dd><p>Check if all the work submitted has been completed.</p>
<dl class="field-list simple">
<dt class="field-odd">Returns</dt>
<dd class="field-odd"><p>A boolean indicating if all kernels in this stream are completed.</p>
</dd>
<dt class="field-even">Return type</dt>
<dd class="field-even"><p><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.13)">bool</a></p>
</dd>
</dl>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">s_cuda</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">Stream</span><span class="p">(</span><span class="n">device</span><span class="o">=</span><span class="s1">'cuda'</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">s_cuda</span><span class="o">.</span><span class="n">query</span><span class="p">()</span>
<span class="go">True</span>
</pre></div>
</div>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="torch.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></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="torch.Event.html#torch.Event" title="torch.Event"><span class="pre">Event</span></a></span></span><a class="headerlink" href="#torch.Stream.record_event" title="Permalink to this definition">¶</a></dt>
<dd><p>Record an event. En-queuing it into the Stream to allow further synchronization from the current point in the FIFO queue.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>event</strong> (<a class="reference internal" href="torch.Event.html#torch.Event" title="torch.Event"><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.Event</span></code></a>, optional) – event to record. If not given, a new one will be allocated.</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>Recorded event.</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p><a class="reference internal" href="torch.Event.html#torch.Event" title="torch.Event">Event</a></p>
</dd>
</dl>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">s_cuda</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">Stream</span><span class="p">(</span><span class="n">device</span><span class="o">=</span><span class="s1">'cuda'</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">e_cuda</span> <span class="o">=</span> <span class="n">s_cuda</span><span class="o">.</span><span class="n">record_event</span><span class="p">()</span>
</pre></div>
</div>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="torch.Stream.synchronize">
<span class="sig-name descname"><span class="pre">synchronize</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.13)"><span class="pre">None</span></a></span></span><a class="headerlink" href="#torch.Stream.synchronize" title="Permalink to this definition">¶</a></dt>
<dd><p>Wait for all the kernels in this stream to complete.</p>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">s_cuda</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">Stream</span><span class="p">(</span><span class="n">device</span><span class="o">=</span><span class="s1">'cuda'</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">s_cuda</span><span class="o">.</span><span class="n">synchronize</span><span class="p">()</span>
</pre></div>
</div>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="torch.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> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.13)"><span class="pre">None</span></a></span></span><a class="headerlink" href="#torch.Stream.wait_event" title="Permalink to this definition">¶</a></dt>
<dd><p>Make all future work submitted to the stream wait for an event.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>event</strong> (<a class="reference internal" href="torch.Event.html#torch.Event" title="torch.Event"><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.Event</span></code></a>) – an event to wait for.</p>
</dd>
</dl>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">s1_cuda</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">Stream</span><span class="p">(</span><span class="n">device</span><span class="o">=</span><span class="s1">'cuda'</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">s2_cuda</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">Stream</span><span class="p">(</span><span class="n">device</span><span class="o">=</span><span class="s1">'cuda'</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">e_cuda</span> <span class="o">=</span> <span class="n">s1_cuda</span><span class="o">.</span><span class="n">record_event</span><span class="p">()</span>
<span class="gp">>>> </span><span class="n">s2_cuda</span><span class="o">.</span><span class="n">wait_event</span><span class="p">(</span><span class="n">e_cuda</span><span class="p">)</span>
</pre></div>
</div>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="torch.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> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.13)"><span class="pre">None</span></a></span></span><a class="headerlink" href="#torch.Stream.wait_stream" title="Permalink to this definition">¶</a></dt>
<dd><p>Synchronize with another stream. All future work submitted to this stream will wait until all kernels
already submitted to the given stream are completed.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>stream</strong> (<a class="reference internal" href="#torch.Stream" title="torch.Stream"><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.Stream</span></code></a>) – a stream to synchronize.</p>
</dd>
</dl>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">s1_cuda</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">Stream</span><span class="p">(</span><span class="n">device</span><span class="o">=</span><span class="s1">'cuda'</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">s2_cuda</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">Stream</span><span class="p">(</span><span class="n">device</span><span class="o">=</span><span class="s1">'cuda'</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">s2_cuda</span><span class="o">.</span><span class="n">wait_stream</span><span class="p">(</span><span class="n">s1_cuda</span><span class="p">)</span>
</pre></div>
</div>
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