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<div class="section" id="packedsequence">
<h1>PackedSequence<a class="headerlink" href="#packedsequence" title="Permalink to this headline">¶</a></h1>
<dl class="class">
<dt id="torch.nn.utils.rnn.PackedSequence">
<em class="property">class </em><code class="sig-prename descclassname">torch.nn.utils.rnn.</code><code class="sig-name descname">PackedSequence</code><a class="reference internal" href="../_modules/torch/nn/utils/rnn.html#PackedSequence"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#torch.nn.utils.rnn.PackedSequence" title="Permalink to this definition">¶</a></dt>
<dd><p>Holds the data and list of <a class="reference internal" href="#torch.nn.utils.rnn.PackedSequence.batch_sizes" title="torch.nn.utils.rnn.PackedSequence.batch_sizes"><code class="xref py py-attr docutils literal notranslate"><span class="pre">batch_sizes</span></code></a> of a packed sequence.</p>
<p>All RNN modules accept packed sequences as inputs.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>Instances of this class should never be created manually. They are meant
to be instantiated by functions like <a class="reference internal" href="torch.nn.utils.rnn.pack_padded_sequence.html#torch.nn.utils.rnn.pack_padded_sequence" title="torch.nn.utils.rnn.pack_padded_sequence"><code class="xref py py-func docutils literal notranslate"><span class="pre">pack_padded_sequence()</span></code></a>.</p>
<p>Batch sizes represent the number elements at each sequence step in
the batch, not the varying sequence lengths passed to
<a class="reference internal" href="torch.nn.utils.rnn.pack_padded_sequence.html#torch.nn.utils.rnn.pack_padded_sequence" title="torch.nn.utils.rnn.pack_padded_sequence"><code class="xref py py-func docutils literal notranslate"><span class="pre">pack_padded_sequence()</span></code></a>. For instance, given data <code class="docutils literal notranslate"><span class="pre">abc</span></code> and <code class="docutils literal notranslate"><span class="pre">x</span></code>
the <a class="reference internal" href="#torch.nn.utils.rnn.PackedSequence" title="torch.nn.utils.rnn.PackedSequence"><code class="xref py py-class docutils literal notranslate"><span class="pre">PackedSequence</span></code></a> would contain data <code class="docutils literal notranslate"><span class="pre">axbc</span></code> with
<code class="docutils literal notranslate"><span class="pre">batch_sizes=[2,1,1]</span></code>.</p>
</div>
<dl class="field-list simple">
<dt class="field-odd">Variables</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>~PackedSequence.data</strong> (<a class="reference internal" href="../tensors.html#torch.Tensor" title="torch.Tensor"><em>Tensor</em></a>) – Tensor containing packed sequence</p></li>
<li><p><strong>~PackedSequence.batch_sizes</strong> (<a class="reference internal" href="../tensors.html#torch.Tensor" title="torch.Tensor"><em>Tensor</em></a>) – Tensor of integers holding
information about the batch size at each sequence step</p></li>
<li><p><strong>~PackedSequence.sorted_indices</strong> (<a class="reference internal" href="../tensors.html#torch.Tensor" title="torch.Tensor"><em>Tensor</em></a><em>, </em><em>optional</em>) – Tensor of integers holding how this
<a class="reference internal" href="#torch.nn.utils.rnn.PackedSequence" title="torch.nn.utils.rnn.PackedSequence"><code class="xref py py-class docutils literal notranslate"><span class="pre">PackedSequence</span></code></a> is constructed from sequences.</p></li>
<li><p><strong>~PackedSequence.unsorted_indices</strong> (<a class="reference internal" href="../tensors.html#torch.Tensor" title="torch.Tensor"><em>Tensor</em></a><em>, </em><em>optional</em>) – Tensor of integers holding how this
to recover the original sequences with correct order.</p></li>
</ul>
</dd>
</dl>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p><a class="reference internal" href="#torch.nn.utils.rnn.PackedSequence.data" title="torch.nn.utils.rnn.PackedSequence.data"><code class="xref py py-attr docutils literal notranslate"><span class="pre">data</span></code></a> can be on arbitrary device and of arbitrary dtype.
<a class="reference internal" href="#torch.nn.utils.rnn.PackedSequence.sorted_indices" title="torch.nn.utils.rnn.PackedSequence.sorted_indices"><code class="xref py py-attr docutils literal notranslate"><span class="pre">sorted_indices</span></code></a> and <a class="reference internal" href="#torch.nn.utils.rnn.PackedSequence.unsorted_indices" title="torch.nn.utils.rnn.PackedSequence.unsorted_indices"><code class="xref py py-attr docutils literal notranslate"><span class="pre">unsorted_indices</span></code></a> must be <code class="docutils literal notranslate"><span class="pre">torch.int64</span></code>
tensors on the same device as <a class="reference internal" href="#torch.nn.utils.rnn.PackedSequence.data" title="torch.nn.utils.rnn.PackedSequence.data"><code class="xref py py-attr docutils literal notranslate"><span class="pre">data</span></code></a>.</p>
<p>However, <a class="reference internal" href="#torch.nn.utils.rnn.PackedSequence.batch_sizes" title="torch.nn.utils.rnn.PackedSequence.batch_sizes"><code class="xref py py-attr docutils literal notranslate"><span class="pre">batch_sizes</span></code></a> should always be a CPU <code class="docutils literal notranslate"><span class="pre">torch.int64</span></code> tensor.</p>
<p>This invariant is maintained throughout <a class="reference internal" href="#torch.nn.utils.rnn.PackedSequence" title="torch.nn.utils.rnn.PackedSequence"><code class="xref py py-class docutils literal notranslate"><span class="pre">PackedSequence</span></code></a> class,
and all functions that construct a <cite>:class:PackedSequence</cite> in PyTorch
(i.e., they only pass in tensors conforming to this constraint).</p>
</div>
<dl class="method">
<dt id="torch.nn.utils.rnn.PackedSequence.batch_sizes">
<em class="property">property </em><code class="sig-name descname">batch_sizes</code><a class="headerlink" href="#torch.nn.utils.rnn.PackedSequence.batch_sizes" title="Permalink to this definition">¶</a></dt>
<dd><p>Alias for field number 1</p>
</dd></dl>
<dl class="method">
<dt id="torch.nn.utils.rnn.PackedSequence.count">
<code class="sig-name descname">count</code><span class="sig-paren">(</span><em class="sig-param">value</em><span class="sig-paren">)</span> → integer -- return number of occurrences of value<a class="headerlink" href="#torch.nn.utils.rnn.PackedSequence.count" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="method">
<dt id="torch.nn.utils.rnn.PackedSequence.data">
<em class="property">property </em><code class="sig-name descname">data</code><a class="headerlink" href="#torch.nn.utils.rnn.PackedSequence.data" title="Permalink to this definition">¶</a></dt>
<dd><p>Alias for field number 0</p>
</dd></dl>
<dl class="method">
<dt id="torch.nn.utils.rnn.PackedSequence.index">
<code class="sig-name descname">index</code><span class="sig-paren">(</span><em class="sig-param">value</em><span class="optional">[</span>, <em class="sig-param">start</em><span class="optional">[</span>, <em class="sig-param">stop</em><span class="optional">]</span><span class="optional">]</span><span class="sig-paren">)</span> → integer -- return first index of value.<a class="headerlink" href="#torch.nn.utils.rnn.PackedSequence.index" title="Permalink to this definition">¶</a></dt>
<dd><p>Raises ValueError if the value is not present.</p>
</dd></dl>
<dl class="method">
<dt id="torch.nn.utils.rnn.PackedSequence.is_cuda">
<em class="property">property </em><code class="sig-name descname">is_cuda</code><a class="headerlink" href="#torch.nn.utils.rnn.PackedSequence.is_cuda" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns true if <cite>self.data</cite> stored on a gpu</p>
</dd></dl>
<dl class="method">
<dt id="torch.nn.utils.rnn.PackedSequence.is_pinned">
<code class="sig-name descname">is_pinned</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../_modules/torch/nn/utils/rnn.html#PackedSequence.is_pinned"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#torch.nn.utils.rnn.PackedSequence.is_pinned" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns true if <cite>self.data</cite> stored on in pinned memory</p>
</dd></dl>
<dl class="method">
<dt id="torch.nn.utils.rnn.PackedSequence.sorted_indices">
<em class="property">property </em><code class="sig-name descname">sorted_indices</code><a class="headerlink" href="#torch.nn.utils.rnn.PackedSequence.sorted_indices" title="Permalink to this definition">¶</a></dt>
<dd><p>Alias for field number 2</p>
</dd></dl>
<dl class="method">
<dt id="torch.nn.utils.rnn.PackedSequence.to">
<code class="sig-name descname">to</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/torch/nn/utils/rnn.html#PackedSequence.to"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#torch.nn.utils.rnn.PackedSequence.to" title="Permalink to this definition">¶</a></dt>
<dd><p>Performs dtype and/or device conversion on <cite>self.data</cite>.</p>
<p>It has similar signature as <a class="reference internal" href="../tensors.html#torch.Tensor.to" title="torch.Tensor.to"><code class="xref py py-meth docutils literal notranslate"><span class="pre">torch.Tensor.to()</span></code></a>, except optional
arguments like <cite>non_blocking</cite> and <cite>copy</cite> should be passed as kwargs,
not args, or they will not apply to the index tensors.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>If the <code class="docutils literal notranslate"><span class="pre">self.data</span></code> Tensor already has the correct <code class="xref py py-class docutils literal notranslate"><span class="pre">torch.dtype</span></code>
and <code class="xref py py-class docutils literal notranslate"><span class="pre">torch.device</span></code>, then <code class="docutils literal notranslate"><span class="pre">self</span></code> is returned.
Otherwise, returns a copy with the desired configuration.</p>
</div>
</dd></dl>
<dl class="method">
<dt id="torch.nn.utils.rnn.PackedSequence.unsorted_indices">
<em class="property">property </em><code class="sig-name descname">unsorted_indices</code><a class="headerlink" href="#torch.nn.utils.rnn.PackedSequence.unsorted_indices" title="Permalink to this definition">¶</a></dt>
<dd><p>Alias for field number 3</p>
</dd></dl>
</dd></dl>
</div>
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