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<!DOCTYPE html>
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<title>torch.Storage — PyTorch 0.1.12_2 documentation</title>
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<li class="toctree-l1"><a class="reference internal" href="notes/autograd.html">Autograd mechanics</a><ul>
<li class="toctree-l2"><a class="reference internal" href="notes/autograd.html#excluding-subgraphs-from-backward">Excluding subgraphs from backward</a><ul>
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<p class="caption"><span class="caption-text">Package Reference</span></p>
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<li class="toctree-l2"><a class="reference internal" href="nn.html#linear-layers">Linear layers</a><ul>
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</ul>
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<li class="toctree-l2"><a class="reference internal" href="nn.html#dropout-layers">Dropout layers</a><ul>
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<li class="toctree-l3"><a class="reference internal" href="nn.html#dropout2d"><span class="hidden-section">Dropout2d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="nn.html#dropout3d"><span class="hidden-section">Dropout3d</span></a></li>
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<li class="toctree-l2"><a class="reference internal" href="nn.html#loss-functions">Loss functions</a><ul>
<li class="toctree-l3"><a class="reference internal" href="nn.html#l1loss"><span class="hidden-section">L1Loss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="nn.html#mseloss"><span class="hidden-section">MSELoss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="nn.html#crossentropyloss"><span class="hidden-section">CrossEntropyLoss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="nn.html#nllloss"><span class="hidden-section">NLLLoss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="nn.html#nllloss2d"><span class="hidden-section">NLLLoss2d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="nn.html#kldivloss"><span class="hidden-section">KLDivLoss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="nn.html#bceloss"><span class="hidden-section">BCELoss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="nn.html#marginrankingloss"><span class="hidden-section">MarginRankingLoss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="nn.html#hingeembeddingloss"><span class="hidden-section">HingeEmbeddingLoss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="nn.html#multilabelmarginloss"><span class="hidden-section">MultiLabelMarginLoss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="nn.html#smoothl1loss"><span class="hidden-section">SmoothL1Loss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="nn.html#softmarginloss"><span class="hidden-section">SoftMarginLoss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="nn.html#multilabelsoftmarginloss"><span class="hidden-section">MultiLabelSoftMarginLoss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="nn.html#cosineembeddingloss"><span class="hidden-section">CosineEmbeddingLoss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="nn.html#multimarginloss"><span class="hidden-section">MultiMarginLoss</span></a></li>
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<li class="toctree-l2"><a class="reference internal" href="nn.html#vision-layers">Vision layers</a><ul>
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<li class="toctree-l3"><a class="reference internal" href="nn.html#pad-packed-sequence"><span class="hidden-section">pad_packed_sequence</span></a></li>
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<li class="toctree-l3"><a class="reference internal" href="nn.html#conv-transpose2d"><span class="hidden-section">conv_transpose2d</span></a></li>
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<li class="toctree-l3"><a class="reference internal" href="nn.html#avg-pool2d"><span class="hidden-section">avg_pool2d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="nn.html#avg-pool3d"><span class="hidden-section">avg_pool3d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="nn.html#max-pool1d"><span class="hidden-section">max_pool1d</span></a></li>
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<li class="toctree-l3"><a class="reference internal" href="nn.html#max-pool3d"><span class="hidden-section">max_pool3d</span></a></li>
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<li class="toctree-l3"><a class="reference internal" href="nn.html#id17"><span class="hidden-section">relu</span></a></li>
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<li class="toctree-l3"><a class="reference internal" href="nn.html#id25"><span class="hidden-section">softplus</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="nn.html#id26"><span class="hidden-section">softmin</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="nn.html#id27"><span class="hidden-section">softmax</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="nn.html#id28"><span class="hidden-section">softshrink</span></a></li>
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<p class="caption"><span class="caption-text">torchvision Reference</span></p>
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<li class="toctree-l3"><a class="reference internal" href="torchvision/datasets.html#captions">Captions:</a></li>
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<div class="section" id="torch-storage">
<h1>torch.Storage<a class="headerlink" href="#torch-storage" title="Permalink to this headline">¶</a></h1>
<p>A <code class="xref py py-class docutils literal"><span class="pre">torch.Storage</span></code> is a contiguous, one-dimensional array of a single
data type.</p>
<p>Every <a class="reference internal" href="tensors.html#torch.Tensor" title="torch.Tensor"><code class="xref py py-class docutils literal"><span class="pre">torch.Tensor</span></code></a> has a corresponding storage of the same data type.</p>
<dl class="class">
<dt id="torch.FloatStorage">
<em class="property">class </em><code class="descclassname">torch.</code><code class="descname">FloatStorage</code><a class="reference internal" href="_modules/torch.html#FloatStorage"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#torch.FloatStorage" title="Permalink to this definition">¶</a></dt>
<dd><dl class="method">
<dt id="torch.FloatStorage.byte">
<code class="descname">byte</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#torch.FloatStorage.byte" title="Permalink to this definition">¶</a></dt>
<dd><p>Casts this storage to byte type</p>
</dd></dl>
<dl class="method">
<dt id="torch.FloatStorage.char">
<code class="descname">char</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#torch.FloatStorage.char" title="Permalink to this definition">¶</a></dt>
<dd><p>Casts this storage to char type</p>
</dd></dl>
<dl class="method">
<dt id="torch.FloatStorage.clone">
<code class="descname">clone</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#torch.FloatStorage.clone" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns a copy of this storage</p>
</dd></dl>
<dl class="method">
<dt id="torch.FloatStorage.copy_">
<code class="descname">copy_</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#torch.FloatStorage.copy_" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="method">
<dt id="torch.FloatStorage.cpu">
<code class="descname">cpu</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#torch.FloatStorage.cpu" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns a CPU copy of this storage if it’s not already on the CPU</p>
</dd></dl>
<dl class="method">
<dt id="torch.FloatStorage.cuda">
<code class="descname">cuda</code><span class="sig-paren">(</span><em>device=None</em>, <em>async=False</em><span class="sig-paren">)</span><a class="headerlink" href="#torch.FloatStorage.cuda" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns a copy of this object in CUDA memory.</p>
<p>If this object is already in CUDA memory and on the correct device, then
no copy is performed and the original object is returned.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>device</strong> (<a class="reference external" href="https://docs.python.org/2/library/functions.html#int" title="(in Python v2.7)"><em>int</em></a>) – The destination GPU id. Defaults to the current device.</li>
<li><strong>async</strong> (<a class="reference external" href="https://docs.python.org/2/library/functions.html#bool" title="(in Python v2.7)"><em>bool</em></a>) – If True and the source is in pinned memory, the copy will
be asynchronous with respect to the host. Otherwise, the
argument has no effect.</li>
</ul>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="torch.FloatStorage.data_ptr">
<code class="descname">data_ptr</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#torch.FloatStorage.data_ptr" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="method">
<dt id="torch.FloatStorage.double">
<code class="descname">double</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#torch.FloatStorage.double" title="Permalink to this definition">¶</a></dt>
<dd><p>Casts this storage to double type</p>
</dd></dl>
<dl class="method">
<dt id="torch.FloatStorage.element_size">
<code class="descname">element_size</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#torch.FloatStorage.element_size" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="method">
<dt id="torch.FloatStorage.fill_">
<code class="descname">fill_</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#torch.FloatStorage.fill_" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="method">
<dt id="torch.FloatStorage.float">
<code class="descname">float</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#torch.FloatStorage.float" title="Permalink to this definition">¶</a></dt>
<dd><p>Casts this storage to float type</p>
</dd></dl>
<dl class="method">
<dt id="torch.FloatStorage.from_buffer">
<code class="descname">from_buffer</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#torch.FloatStorage.from_buffer" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="method">
<dt id="torch.FloatStorage.half">
<code class="descname">half</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#torch.FloatStorage.half" title="Permalink to this definition">¶</a></dt>
<dd><p>Casts this storage to half type</p>
</dd></dl>
<dl class="method">
<dt id="torch.FloatStorage.int">
<code class="descname">int</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#torch.FloatStorage.int" title="Permalink to this definition">¶</a></dt>
<dd><p>Casts this storage to int type</p>
</dd></dl>
<dl class="attribute">
<dt id="torch.FloatStorage.is_cuda">
<code class="descname">is_cuda</code><em class="property"> = False</em><a class="headerlink" href="#torch.FloatStorage.is_cuda" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="method">
<dt id="torch.FloatStorage.is_pinned">
<code class="descname">is_pinned</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#torch.FloatStorage.is_pinned" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="method">
<dt id="torch.FloatStorage.is_shared">
<code class="descname">is_shared</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#torch.FloatStorage.is_shared" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="attribute">
<dt id="torch.FloatStorage.is_sparse">
<code class="descname">is_sparse</code><em class="property"> = False</em><a class="headerlink" href="#torch.FloatStorage.is_sparse" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="method">
<dt id="torch.FloatStorage.long">
<code class="descname">long</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#torch.FloatStorage.long" title="Permalink to this definition">¶</a></dt>
<dd><p>Casts this storage to long type</p>
</dd></dl>
<dl class="method">
<dt id="torch.FloatStorage.new">
<code class="descname">new</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#torch.FloatStorage.new" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="method">
<dt id="torch.FloatStorage.pin_memory">
<code class="descname">pin_memory</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#torch.FloatStorage.pin_memory" title="Permalink to this definition">¶</a></dt>
<dd><p>Copies the storage to pinned memory, if it’s not already pinned.</p>
</dd></dl>
<dl class="method">
<dt id="torch.FloatStorage.resize_">
<code class="descname">resize_</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#torch.FloatStorage.resize_" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="method">
<dt id="torch.FloatStorage.share_memory_">
<code class="descname">share_memory_</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#torch.FloatStorage.share_memory_" title="Permalink to this definition">¶</a></dt>
<dd><p>Moves the storage to shared memory.</p>
<p>This is a no-op for storages already in shared memory and for CUDA
storages, which do not need to be moved for sharing across processes.
Storages in shared memory cannot be resized.</p>
<p>Returns: self</p>
</dd></dl>
<dl class="method">
<dt id="torch.FloatStorage.short">
<code class="descname">short</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#torch.FloatStorage.short" title="Permalink to this definition">¶</a></dt>
<dd><p>Casts this storage to short type</p>
</dd></dl>
<dl class="method">
<dt id="torch.FloatStorage.size">
<code class="descname">size</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#torch.FloatStorage.size" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="method">
<dt id="torch.FloatStorage.tolist">
<code class="descname">tolist</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#torch.FloatStorage.tolist" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns a list containing the elements of this storage</p>
</dd></dl>
<dl class="method">
<dt id="torch.FloatStorage.type">
<code class="descname">type</code><span class="sig-paren">(</span><em>new_type=None</em>, <em>async=False</em><span class="sig-paren">)</span><a class="headerlink" href="#torch.FloatStorage.type" title="Permalink to this definition">¶</a></dt>
<dd><p>Casts this object to the specified type.</p>
<p>If this is already of the correct type, no copy is performed and the
original object is returned.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>new_type</strong> (<a class="reference external" href="https://docs.python.org/2/library/functions.html#type" title="(in Python v2.7)"><em>type</em></a><em> or </em><a class="reference external" href="https://docs.python.org/2/library/string.html#module-string" title="(in Python v2.7)"><em>string</em></a>) – The desired type</li>
<li><strong>async</strong> (<a class="reference external" href="https://docs.python.org/2/library/functions.html#bool" title="(in Python v2.7)"><em>bool</em></a>) – If True, and the source is in pinned memory and
destination is on the GPU or vice versa, the copy is
performed asynchronously with respect to the host.
Otherwise, the argument has no effect.</li>
</ul>
</td>
</tr>
</tbody>
</table>
</dd></dl>
</dd></dl>
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