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<div class="section" id="torch-tensor">
<span id="tensor-doc"></span><h1>torch.Tensor<a class="headerlink" href="#torch-tensor" title="Permalink to this heading">¶</a></h1>
<p>A <a class="reference internal" href="#torch.Tensor" title="torch.Tensor"><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.Tensor</span></code></a> is a multi-dimensional matrix containing elements of
a single data type.</p>
<div class="section" id="data-types">
<h2>Data types<a class="headerlink" href="#data-types" title="Permalink to this heading">¶</a></h2>
<p>Torch defines 10 tensor types with CPU and GPU variants which are as follows:</p>
<table class="docutils colwidths-auto align-default">
<thead>
<tr class="row-odd"><th class="head"><p>Data type</p></th>
<th class="head"><p>dtype</p></th>
<th class="head"><p>CPU tensor</p></th>
<th class="head"><p>GPU tensor</p></th>
</tr>
</thead>
<tbody>
<tr class="row-even"><td><p>32-bit floating point</p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">torch.float32</span></code> or <code class="docutils literal notranslate"><span class="pre">torch.float</span></code></p></td>
<td><p><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.FloatTensor</span></code></p></td>
<td><p><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.cuda.FloatTensor</span></code></p></td>
</tr>
<tr class="row-odd"><td><p>64-bit floating point</p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">torch.float64</span></code> or <code class="docutils literal notranslate"><span class="pre">torch.double</span></code></p></td>
<td><p><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.DoubleTensor</span></code></p></td>
<td><p><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.cuda.DoubleTensor</span></code></p></td>
</tr>
<tr class="row-even"><td><p>16-bit floating point <a class="footnote-reference brackets" href="#id4" id="id1">1</a></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">torch.float16</span></code> or <code class="docutils literal notranslate"><span class="pre">torch.half</span></code></p></td>
<td><p><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.HalfTensor</span></code></p></td>
<td><p><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.cuda.HalfTensor</span></code></p></td>
</tr>
<tr class="row-odd"><td><p>16-bit floating point <a class="footnote-reference brackets" href="#id5" id="id2">2</a></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">torch.bfloat16</span></code></p></td>
<td><p><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.BFloat16Tensor</span></code></p></td>
<td><p><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.cuda.BFloat16Tensor</span></code></p></td>
</tr>
<tr class="row-even"><td><p>32-bit complex</p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">torch.complex32</span></code> or <code class="docutils literal notranslate"><span class="pre">torch.chalf</span></code></p></td>
<td></td>
<td></td>
</tr>
<tr class="row-odd"><td><p>64-bit complex</p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">torch.complex64</span></code> or <code class="docutils literal notranslate"><span class="pre">torch.cfloat</span></code></p></td>
<td></td>
<td></td>
</tr>
<tr class="row-even"><td><p>128-bit complex</p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">torch.complex128</span></code> or <code class="docutils literal notranslate"><span class="pre">torch.cdouble</span></code></p></td>
<td></td>
<td></td>
</tr>
<tr class="row-odd"><td><p>8-bit integer (unsigned)</p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">torch.uint8</span></code></p></td>
<td><p><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.ByteTensor</span></code></p></td>
<td><p><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.cuda.ByteTensor</span></code></p></td>
</tr>
<tr class="row-even"><td><p>8-bit integer (signed)</p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">torch.int8</span></code></p></td>
<td><p><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.CharTensor</span></code></p></td>
<td><p><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.cuda.CharTensor</span></code></p></td>
</tr>
<tr class="row-odd"><td><p>16-bit integer (signed)</p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">torch.int16</span></code> or <code class="docutils literal notranslate"><span class="pre">torch.short</span></code></p></td>
<td><p><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.ShortTensor</span></code></p></td>
<td><p><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.cuda.ShortTensor</span></code></p></td>
</tr>
<tr class="row-even"><td><p>32-bit integer (signed)</p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">torch.int32</span></code> or <code class="docutils literal notranslate"><span class="pre">torch.int</span></code></p></td>
<td><p><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.IntTensor</span></code></p></td>
<td><p><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.cuda.IntTensor</span></code></p></td>
</tr>
<tr class="row-odd"><td><p>64-bit integer (signed)</p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">torch.int64</span></code> or <code class="docutils literal notranslate"><span class="pre">torch.long</span></code></p></td>
<td><p><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.LongTensor</span></code></p></td>
<td><p><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.cuda.LongTensor</span></code></p></td>
</tr>
<tr class="row-even"><td><p>Boolean</p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">torch.bool</span></code></p></td>
<td><p><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.BoolTensor</span></code></p></td>
<td><p><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.cuda.BoolTensor</span></code></p></td>
</tr>
<tr class="row-odd"><td><p>quantized 8-bit integer (unsigned)</p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">torch.quint8</span></code></p></td>
<td><p><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.ByteTensor</span></code></p></td>
<td><p>/</p></td>
</tr>
<tr class="row-even"><td><p>quantized 8-bit integer (signed)</p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">torch.qint8</span></code></p></td>
<td><p><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.CharTensor</span></code></p></td>
<td><p>/</p></td>
</tr>
<tr class="row-odd"><td><p>quantized 32-bit integer (signed)</p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">torch.qint32</span></code></p></td>
<td><p><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.IntTensor</span></code></p></td>
<td><p>/</p></td>
</tr>
<tr class="row-even"><td><p>quantized 4-bit integer (unsigned) <a class="footnote-reference brackets" href="#id6" id="id3">3</a></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">torch.quint4x2</span></code></p></td>
<td><p><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.ByteTensor</span></code></p></td>
<td><p>/</p></td>
</tr>
</tbody>
</table>
<dl class="footnote brackets">
<dt class="label" id="id4"><span class="brackets"><a class="fn-backref" href="#id1">1</a></span></dt>
<dd><p>Sometimes referred to as binary16: uses 1 sign, 5 exponent, and 10
significand bits. Useful when precision is important at the expense of range.</p>
</dd>
<dt class="label" id="id5"><span class="brackets"><a class="fn-backref" href="#id2">2</a></span></dt>
<dd><p>Sometimes referred to as Brain Floating Point: uses 1 sign, 8 exponent, and 7
significand bits. Useful when range is important, since it has the same
number of exponent bits as <code class="docutils literal notranslate"><span class="pre">float32</span></code></p>
</dd>
<dt class="label" id="id6"><span class="brackets"><a class="fn-backref" href="#id3">3</a></span></dt>
<dd><p>quantized 4-bit integer is stored as a 8-bit signed integer. Currently it’s only supported in EmbeddingBag operator.</p>
</dd>
</dl>
<p><a class="reference internal" href="#torch.Tensor" title="torch.Tensor"><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.Tensor</span></code></a> is an alias for the default tensor type (<code class="xref py py-class docutils literal notranslate"><span class="pre">torch.FloatTensor</span></code>).</p>
</div>
<div class="section" id="initializing-and-basic-operations">
<h2>Initializing and basic operations<a class="headerlink" href="#initializing-and-basic-operations" title="Permalink to this heading">¶</a></h2>
<p>A tensor can be constructed from a Python <a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.12)"><code class="xref py py-class docutils literal notranslate"><span class="pre">list</span></code></a> or sequence using the
<a class="reference internal" href="generated/torch.tensor.html#torch.tensor" title="torch.tensor"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.tensor()</span></code></a> constructor:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">([[</span><span class="mf">1.</span><span class="p">,</span> <span class="o">-</span><span class="mf">1.</span><span class="p">],</span> <span class="p">[</span><span class="mf">1.</span><span class="p">,</span> <span class="o">-</span><span class="mf">1.</span><span class="p">]])</span>
<span class="go">tensor([[ 1.0000, -1.0000],</span>
<span class="go"> [ 1.0000, -1.0000]])</span>
<span class="gp">>>> </span><span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">],</span> <span class="p">[</span><span class="mi">4</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">6</span><span class="p">]]))</span>
<span class="go">tensor([[ 1, 2, 3],</span>
<span class="go"> [ 4, 5, 6]])</span>
</pre></div>
</div>
<div class="admonition warning">
<p class="admonition-title">Warning</p>
<p><a class="reference internal" href="generated/torch.tensor.html#torch.tensor" title="torch.tensor"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.tensor()</span></code></a> always copies <code class="xref py py-attr docutils literal notranslate"><span class="pre">data</span></code>. If you have a Tensor
<code class="xref py py-attr docutils literal notranslate"><span class="pre">data</span></code> and just want to change its <code class="docutils literal notranslate"><span class="pre">requires_grad</span></code> flag, use
<a class="reference internal" href="generated/torch.Tensor.requires_grad_.html#torch.Tensor.requires_grad_" title="torch.Tensor.requires_grad_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">requires_grad_()</span></code></a> or
<a class="reference internal" href="generated/torch.Tensor.detach.html#torch.Tensor.detach" title="torch.Tensor.detach"><code class="xref py py-meth docutils literal notranslate"><span class="pre">detach()</span></code></a> to avoid a copy.
If you have a numpy array and want to avoid a copy, use
<a class="reference internal" href="generated/torch.as_tensor.html#torch.as_tensor" title="torch.as_tensor"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.as_tensor()</span></code></a>.</p>
</div>
<p>A tensor of specific data type can be constructed by passing a
<a class="reference internal" href="tensor_attributes.html#torch.dtype" title="torch.dtype"><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.dtype</span></code></a> and/or a <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> to a
constructor or tensor creation op:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">torch</span><span class="o">.</span><span class="n">zeros</span><span class="p">([</span><span class="mi">2</span><span class="p">,</span> <span class="mi">4</span><span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">int32</span><span class="p">)</span>
<span class="go">tensor([[ 0, 0, 0, 0],</span>
<span class="go"> [ 0, 0, 0, 0]], dtype=torch.int32)</span>
<span class="gp">>>> </span><span class="n">cuda0</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">device</span><span class="p">(</span><span class="s1">'cuda:0'</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">torch</span><span class="o">.</span><span class="n">ones</span><span class="p">([</span><span class="mi">2</span><span class="p">,</span> <span class="mi">4</span><span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">float64</span><span class="p">,</span> <span class="n">device</span><span class="o">=</span><span class="n">cuda0</span><span class="p">)</span>
<span class="go">tensor([[ 1.0000, 1.0000, 1.0000, 1.0000],</span>
<span class="go"> [ 1.0000, 1.0000, 1.0000, 1.0000]], dtype=torch.float64, device='cuda:0')</span>
</pre></div>
</div>
<p>For more information about building Tensors, see <a class="reference internal" href="torch.html#tensor-creation-ops"><span class="std std-ref">Creation Ops</span></a></p>
<p>The contents of a tensor can be accessed and modified using Python’s indexing
and slicing notation:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">x</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">([[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">],</span> <span class="p">[</span><span class="mi">4</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">6</span><span class="p">]])</span>
<span class="gp">>>> </span><span class="nb">print</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">1</span><span class="p">][</span><span class="mi">2</span><span class="p">])</span>
<span class="go">tensor(6)</span>
<span class="gp">>>> </span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">][</span><span class="mi">1</span><span class="p">]</span> <span class="o">=</span> <span class="mi">8</span>
<span class="gp">>>> </span><span class="nb">print</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
<span class="go">tensor([[ 1, 8, 3],</span>
<span class="go"> [ 4, 5, 6]])</span>
</pre></div>
</div>
<p>Use <a class="reference internal" href="generated/torch.Tensor.item.html#torch.Tensor.item" title="torch.Tensor.item"><code class="xref py py-meth docutils literal notranslate"><span class="pre">torch.Tensor.item()</span></code></a> to get a Python number from a tensor containing a
single value:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">x</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">([[</span><span class="mi">1</span><span class="p">]])</span>
<span class="gp">>>> </span><span class="n">x</span>
<span class="go">tensor([[ 1]])</span>
<span class="gp">>>> </span><span class="n">x</span><span class="o">.</span><span class="n">item</span><span class="p">()</span>
<span class="go">1</span>
<span class="gp">>>> </span><span class="n">x</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">(</span><span class="mf">2.5</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">x</span>
<span class="go">tensor(2.5000)</span>
<span class="gp">>>> </span><span class="n">x</span><span class="o">.</span><span class="n">item</span><span class="p">()</span>
<span class="go">2.5</span>
</pre></div>
</div>
<p>For more information about indexing, see <a class="reference internal" href="torch.html#indexing-slicing-joining"><span class="std std-ref">Indexing, Slicing, Joining, Mutating Ops</span></a></p>
<p>A tensor can be created with <code class="xref py py-attr docutils literal notranslate"><span class="pre">requires_grad=True</span></code> so that
<a class="reference internal" href="autograd.html#module-torch.autograd" title="torch.autograd"><code class="xref py py-mod docutils literal notranslate"><span class="pre">torch.autograd</span></code></a> records operations on them for automatic differentiation.</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">x</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">([[</span><span class="mf">1.</span><span class="p">,</span> <span class="o">-</span><span class="mf">1.</span><span class="p">],</span> <span class="p">[</span><span class="mf">1.</span><span class="p">,</span> <span class="mf">1.</span><span class="p">]],</span> <span class="n">requires_grad</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">out</span> <span class="o">=</span> <span class="n">x</span><span class="o">.</span><span class="n">pow</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span>
<span class="gp">>>> </span><span class="n">out</span><span class="o">.</span><span class="n">backward</span><span class="p">()</span>
<span class="gp">>>> </span><span class="n">x</span><span class="o">.</span><span class="n">grad</span>
<span class="go">tensor([[ 2.0000, -2.0000],</span>
<span class="go"> [ 2.0000, 2.0000]])</span>
</pre></div>
</div>
<p>Each tensor has an associated <code class="xref py py-class docutils literal notranslate"><span class="pre">torch.Storage</span></code>, which holds its data.
The tensor class also provides multi-dimensional, <a class="reference external" href="https://en.wikipedia.org/wiki/Stride_of_an_array">strided</a>
view of a storage and defines numeric operations on it.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>For more information on tensor views, see <a class="reference internal" href="tensor_view.html#tensor-view-doc"><span class="std std-ref">Tensor Views</span></a>.</p>
</div>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>For more information on the <a class="reference internal" href="tensor_attributes.html#torch.dtype" title="torch.dtype"><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.dtype</span></code></a>, <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>, and
<a class="reference internal" href="tensor_attributes.html#torch.layout" title="torch.layout"><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.layout</span></code></a> attributes of a <a class="reference internal" href="#torch.Tensor" title="torch.Tensor"><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.Tensor</span></code></a>, see
<a class="reference internal" href="tensor_attributes.html#tensor-attributes-doc"><span class="std std-ref">Tensor Attributes</span></a>.</p>
</div>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>Methods which mutate a tensor are marked with an underscore suffix.
For example, <code class="xref py py-func docutils literal notranslate"><span class="pre">torch.FloatTensor.abs_()</span></code> computes the absolute value
in-place and returns the modified tensor, while <code class="xref py py-func docutils literal notranslate"><span class="pre">torch.FloatTensor.abs()</span></code>
computes the result in a new tensor.</p>
</div>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>To change an existing tensor’s <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> and/or <a class="reference internal" href="tensor_attributes.html#torch.dtype" title="torch.dtype"><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.dtype</span></code></a>, consider using
<a class="reference internal" href="generated/torch.Tensor.to.html#torch.Tensor.to" title="torch.Tensor.to"><code class="xref py py-meth docutils literal notranslate"><span class="pre">to()</span></code></a> method on the tensor.</p>
</div>
<div class="admonition warning">
<p class="admonition-title">Warning</p>
<p>Current implementation of <a class="reference internal" href="#torch.Tensor" title="torch.Tensor"><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.Tensor</span></code></a> introduces memory overhead,
thus it might lead to unexpectedly high memory usage in the applications with many tiny tensors.
If this is your case, consider using one large structure.</p>
</div>
</div>
<div class="section" id="tensor-class-reference">
<h2>Tensor class reference<a class="headerlink" href="#tensor-class-reference" title="Permalink to this heading">¶</a></h2>
<dl class="py class">
<dt class="sig sig-object py" id="torch.Tensor">
<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">Tensor</span></span><a class="headerlink" href="#torch.Tensor" title="Permalink to this definition">¶</a></dt>
<dd><p>There are a few main ways to create a tensor, depending on your use case.</p>
<ul class="simple">
<li><p>To create a tensor with pre-existing data, use <a class="reference internal" href="generated/torch.tensor.html#torch.tensor" title="torch.tensor"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.tensor()</span></code></a>.</p></li>
<li><p>To create a tensor with specific size, use <code class="docutils literal notranslate"><span class="pre">torch.*</span></code> tensor creation
ops (see <a class="reference internal" href="torch.html#tensor-creation-ops"><span class="std std-ref">Creation Ops</span></a>).</p></li>
<li><p>To create a tensor with the same size (and similar types) as another tensor,
use <code class="docutils literal notranslate"><span class="pre">torch.*_like</span></code> tensor creation ops
(see <a class="reference internal" href="torch.html#tensor-creation-ops"><span class="std std-ref">Creation Ops</span></a>).</p></li>
<li><p>To create a tensor with similar type but different size as another tensor,
use <code class="docutils literal notranslate"><span class="pre">tensor.new_*</span></code> creation ops.</p></li>
</ul>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="torch.Tensor.T">
<span class="sig-prename descclassname"><span class="pre">Tensor.</span></span><span class="sig-name descname"><span class="pre">T</span></span><a class="headerlink" href="#torch.Tensor.T" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns a view of this tensor with its dimensions reversed.</p>
<p>If <code class="docutils literal notranslate"><span class="pre">n</span></code> is the number of dimensions in <code class="docutils literal notranslate"><span class="pre">x</span></code>,
<code class="docutils literal notranslate"><span class="pre">x.T</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">x.permute(n-1,</span> <span class="pre">n-2,</span> <span class="pre">...,</span> <span class="pre">0)</span></code>.</p>
<div class="admonition warning">
<p class="admonition-title">Warning</p>
<p>The use of <a class="reference internal" href="#torch.Tensor.T" title="torch.Tensor.T"><code class="xref py py-func docutils literal notranslate"><span class="pre">Tensor.T()</span></code></a> on tensors of dimension other than 2 to reverse their shape
is deprecated and it will throw an error in a future release. Consider <a class="reference internal" href="#torch.Tensor.mT" title="torch.Tensor.mT"><code class="xref py py-attr docutils literal notranslate"><span class="pre">mT</span></code></a>
to transpose batches of matrices or <cite>x.permute(*torch.arange(x.ndim - 1, -1, -1))</cite> to reverse
the dimensions of a tensor.</p>
</div>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="torch.Tensor.H">
<span class="sig-prename descclassname"><span class="pre">Tensor.</span></span><span class="sig-name descname"><span class="pre">H</span></span><a class="headerlink" href="#torch.Tensor.H" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns a view of a matrix (2-D tensor) conjugated and transposed.</p>
<p><code class="docutils literal notranslate"><span class="pre">x.H</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">x.transpose(0,</span> <span class="pre">1).conj()</span></code> for complex matrices and
<code class="docutils literal notranslate"><span class="pre">x.transpose(0,</span> <span class="pre">1)</span></code> for real matrices.</p>
<div class="admonition seealso">
<p class="admonition-title">See also</p>
<p><a class="reference internal" href="#torch.Tensor.mH" title="torch.Tensor.mH"><code class="xref py py-attr docutils literal notranslate"><span class="pre">mH</span></code></a>: An attribute that also works on batches of matrices.</p>
</div>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="torch.Tensor.mT">
<span class="sig-prename descclassname"><span class="pre">Tensor.</span></span><span class="sig-name descname"><span class="pre">mT</span></span><a class="headerlink" href="#torch.Tensor.mT" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns a view of this tensor with the last two dimensions transposed.</p>
<p><code class="docutils literal notranslate"><span class="pre">x.mT</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">x.transpose(-2,</span> <span class="pre">-1)</span></code>.</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="torch.Tensor.mH">
<span class="sig-prename descclassname"><span class="pre">Tensor.</span></span><span class="sig-name descname"><span class="pre">mH</span></span><a class="headerlink" href="#torch.Tensor.mH" title="Permalink to this definition">¶</a></dt>
<dd><p>Accessing this property is equivalent to calling <a class="reference internal" href="generated/torch.adjoint.html#torch.adjoint" title="torch.adjoint"><code class="xref py py-func docutils literal notranslate"><span class="pre">adjoint()</span></code></a>.</p>
</dd></dl>
<table class="autosummary longtable docutils colwidths-auto align-default">
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.new_tensor.html#torch.Tensor.new_tensor" title="torch.Tensor.new_tensor"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.new_tensor</span></code></a></p></td>
<td><p>Returns a new Tensor with <code class="xref py py-attr docutils literal notranslate"><span class="pre">data</span></code> as the tensor data.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.new_full.html#torch.Tensor.new_full" title="torch.Tensor.new_full"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.new_full</span></code></a></p></td>
<td><p>Returns a Tensor of size <code class="xref py py-attr docutils literal notranslate"><span class="pre">size</span></code> filled with <code class="xref py py-attr docutils literal notranslate"><span class="pre">fill_value</span></code>.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.new_empty.html#torch.Tensor.new_empty" title="torch.Tensor.new_empty"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.new_empty</span></code></a></p></td>
<td><p>Returns a Tensor of size <code class="xref py py-attr docutils literal notranslate"><span class="pre">size</span></code> filled with uninitialized data.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.new_ones.html#torch.Tensor.new_ones" title="torch.Tensor.new_ones"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.new_ones</span></code></a></p></td>
<td><p>Returns a Tensor of size <code class="xref py py-attr docutils literal notranslate"><span class="pre">size</span></code> filled with <code class="docutils literal notranslate"><span class="pre">1</span></code>.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.new_zeros.html#torch.Tensor.new_zeros" title="torch.Tensor.new_zeros"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.new_zeros</span></code></a></p></td>
<td><p>Returns a Tensor of size <code class="xref py py-attr docutils literal notranslate"><span class="pre">size</span></code> filled with <code class="docutils literal notranslate"><span class="pre">0</span></code>.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.is_cuda.html#torch.Tensor.is_cuda" title="torch.Tensor.is_cuda"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.is_cuda</span></code></a></p></td>
<td><p>Is <code class="docutils literal notranslate"><span class="pre">True</span></code> if the Tensor is stored on the GPU, <code class="docutils literal notranslate"><span class="pre">False</span></code> otherwise.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.is_quantized.html#torch.Tensor.is_quantized" title="torch.Tensor.is_quantized"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.is_quantized</span></code></a></p></td>
<td><p>Is <code class="docutils literal notranslate"><span class="pre">True</span></code> if the Tensor is quantized, <code class="docutils literal notranslate"><span class="pre">False</span></code> otherwise.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.is_meta.html#torch.Tensor.is_meta" title="torch.Tensor.is_meta"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.is_meta</span></code></a></p></td>
<td><p>Is <code class="docutils literal notranslate"><span class="pre">True</span></code> if the Tensor is a meta tensor, <code class="docutils literal notranslate"><span class="pre">False</span></code> otherwise.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.device.html#torch.Tensor.device" title="torch.Tensor.device"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.device</span></code></a></p></td>
<td><p>Is the <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> where this Tensor is.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.grad.html#torch.Tensor.grad" title="torch.Tensor.grad"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.grad</span></code></a></p></td>
<td><p>This attribute is <code class="docutils literal notranslate"><span class="pre">None</span></code> by default and becomes a Tensor the first time a call to <code class="xref py py-func docutils literal notranslate"><span class="pre">backward()</span></code> computes gradients for <code class="docutils literal notranslate"><span class="pre">self</span></code>.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.ndim.html#torch.Tensor.ndim" title="torch.Tensor.ndim"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.ndim</span></code></a></p></td>
<td><p>Alias for <a class="reference internal" href="generated/torch.Tensor.dim.html#torch.Tensor.dim" title="torch.Tensor.dim"><code class="xref py py-meth docutils literal notranslate"><span class="pre">dim()</span></code></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.real.html#torch.Tensor.real" title="torch.Tensor.real"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.real</span></code></a></p></td>
<td><p>Returns a new tensor containing real values of the <code class="xref py py-attr docutils literal notranslate"><span class="pre">self</span></code> tensor for a complex-valued input tensor.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.imag.html#torch.Tensor.imag" title="torch.Tensor.imag"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.imag</span></code></a></p></td>
<td><p>Returns a new tensor containing imaginary values of the <code class="xref py py-attr docutils literal notranslate"><span class="pre">self</span></code> tensor.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.nbytes.html#torch.Tensor.nbytes" title="torch.Tensor.nbytes"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.nbytes</span></code></a></p></td>
<td><p>Returns the number of bytes consumed by the "view" of elements of the Tensor if the Tensor does not use sparse storage layout.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.itemsize.html#torch.Tensor.itemsize" title="torch.Tensor.itemsize"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.itemsize</span></code></a></p></td>
<td><p>Alias for <a class="reference internal" href="generated/torch.Tensor.element_size.html#torch.Tensor.element_size" title="torch.Tensor.element_size"><code class="xref py py-meth docutils literal notranslate"><span class="pre">element_size()</span></code></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.abs.html#torch.Tensor.abs" title="torch.Tensor.abs"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.abs</span></code></a></p></td>
<td><p>See <a class="reference internal" href="generated/torch.abs.html#torch.abs" title="torch.abs"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.abs()</span></code></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.abs_.html#torch.Tensor.abs_" title="torch.Tensor.abs_"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.abs_</span></code></a></p></td>
<td><p>In-place version of <a class="reference internal" href="generated/torch.Tensor.abs.html#torch.Tensor.abs" title="torch.Tensor.abs"><code class="xref py py-meth docutils literal notranslate"><span class="pre">abs()</span></code></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.absolute.html#torch.Tensor.absolute" title="torch.Tensor.absolute"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.absolute</span></code></a></p></td>
<td><p>Alias for <a class="reference internal" href="generated/torch.abs.html#torch.abs" title="torch.abs"><code class="xref py py-func docutils literal notranslate"><span class="pre">abs()</span></code></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.absolute_.html#torch.Tensor.absolute_" title="torch.Tensor.absolute_"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.absolute_</span></code></a></p></td>
<td><p>In-place version of <a class="reference internal" href="generated/torch.Tensor.absolute.html#torch.Tensor.absolute" title="torch.Tensor.absolute"><code class="xref py py-meth docutils literal notranslate"><span class="pre">absolute()</span></code></a> Alias for <code class="xref py py-func docutils literal notranslate"><span class="pre">abs_()</span></code></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.acos.html#torch.Tensor.acos" title="torch.Tensor.acos"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.acos</span></code></a></p></td>
<td><p>See <a class="reference internal" href="generated/torch.acos.html#torch.acos" title="torch.acos"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.acos()</span></code></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.acos_.html#torch.Tensor.acos_" title="torch.Tensor.acos_"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.acos_</span></code></a></p></td>
<td><p>In-place version of <a class="reference internal" href="generated/torch.Tensor.acos.html#torch.Tensor.acos" title="torch.Tensor.acos"><code class="xref py py-meth docutils literal notranslate"><span class="pre">acos()</span></code></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.arccos.html#torch.Tensor.arccos" title="torch.Tensor.arccos"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.arccos</span></code></a></p></td>
<td><p>See <a class="reference internal" href="generated/torch.arccos.html#torch.arccos" title="torch.arccos"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.arccos()</span></code></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.arccos_.html#torch.Tensor.arccos_" title="torch.Tensor.arccos_"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.arccos_</span></code></a></p></td>
<td><p>In-place version of <a class="reference internal" href="generated/torch.Tensor.arccos.html#torch.Tensor.arccos" title="torch.Tensor.arccos"><code class="xref py py-meth docutils literal notranslate"><span class="pre">arccos()</span></code></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.add.html#torch.Tensor.add" title="torch.Tensor.add"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.add</span></code></a></p></td>
<td><p>Add a scalar or tensor to <code class="xref py py-attr docutils literal notranslate"><span class="pre">self</span></code> tensor.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.add_.html#torch.Tensor.add_" title="torch.Tensor.add_"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.add_</span></code></a></p></td>
<td><p>In-place version of <a class="reference internal" href="generated/torch.Tensor.add.html#torch.Tensor.add" title="torch.Tensor.add"><code class="xref py py-meth docutils literal notranslate"><span class="pre">add()</span></code></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.addbmm.html#torch.Tensor.addbmm" title="torch.Tensor.addbmm"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.addbmm</span></code></a></p></td>
<td><p>See <a class="reference internal" href="generated/torch.addbmm.html#torch.addbmm" title="torch.addbmm"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.addbmm()</span></code></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.addbmm_.html#torch.Tensor.addbmm_" title="torch.Tensor.addbmm_"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.addbmm_</span></code></a></p></td>
<td><p>In-place version of <a class="reference internal" href="generated/torch.Tensor.addbmm.html#torch.Tensor.addbmm" title="torch.Tensor.addbmm"><code class="xref py py-meth docutils literal notranslate"><span class="pre">addbmm()</span></code></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.addcdiv.html#torch.Tensor.addcdiv" title="torch.Tensor.addcdiv"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.addcdiv</span></code></a></p></td>
<td><p>See <a class="reference internal" href="generated/torch.addcdiv.html#torch.addcdiv" title="torch.addcdiv"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.addcdiv()</span></code></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.addcdiv_.html#torch.Tensor.addcdiv_" title="torch.Tensor.addcdiv_"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.addcdiv_</span></code></a></p></td>
<td><p>In-place version of <a class="reference internal" href="generated/torch.Tensor.addcdiv.html#torch.Tensor.addcdiv" title="torch.Tensor.addcdiv"><code class="xref py py-meth docutils literal notranslate"><span class="pre">addcdiv()</span></code></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.addcmul.html#torch.Tensor.addcmul" title="torch.Tensor.addcmul"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.addcmul</span></code></a></p></td>
<td><p>See <a class="reference internal" href="generated/torch.addcmul.html#torch.addcmul" title="torch.addcmul"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.addcmul()</span></code></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.addcmul_.html#torch.Tensor.addcmul_" title="torch.Tensor.addcmul_"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.addcmul_</span></code></a></p></td>
<td><p>In-place version of <a class="reference internal" href="generated/torch.Tensor.addcmul.html#torch.Tensor.addcmul" title="torch.Tensor.addcmul"><code class="xref py py-meth docutils literal notranslate"><span class="pre">addcmul()</span></code></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.addmm.html#torch.Tensor.addmm" title="torch.Tensor.addmm"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.addmm</span></code></a></p></td>
<td><p>See <a class="reference internal" href="generated/torch.addmm.html#torch.addmm" title="torch.addmm"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.addmm()</span></code></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.addmm_.html#torch.Tensor.addmm_" title="torch.Tensor.addmm_"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.addmm_</span></code></a></p></td>
<td><p>In-place version of <a class="reference internal" href="generated/torch.Tensor.addmm.html#torch.Tensor.addmm" title="torch.Tensor.addmm"><code class="xref py py-meth docutils literal notranslate"><span class="pre">addmm()</span></code></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.sspaddmm.html#torch.Tensor.sspaddmm" title="torch.Tensor.sspaddmm"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.sspaddmm</span></code></a></p></td>
<td><p>See <a class="reference internal" href="generated/torch.sspaddmm.html#torch.sspaddmm" title="torch.sspaddmm"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.sspaddmm()</span></code></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.addmv.html#torch.Tensor.addmv" title="torch.Tensor.addmv"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.addmv</span></code></a></p></td>
<td><p>See <a class="reference internal" href="generated/torch.addmv.html#torch.addmv" title="torch.addmv"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.addmv()</span></code></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.addmv_.html#torch.Tensor.addmv_" title="torch.Tensor.addmv_"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.addmv_</span></code></a></p></td>
<td><p>In-place version of <a class="reference internal" href="generated/torch.Tensor.addmv.html#torch.Tensor.addmv" title="torch.Tensor.addmv"><code class="xref py py-meth docutils literal notranslate"><span class="pre">addmv()</span></code></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.addr.html#torch.Tensor.addr" title="torch.Tensor.addr"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.addr</span></code></a></p></td>
<td><p>See <a class="reference internal" href="generated/torch.addr.html#torch.addr" title="torch.addr"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.addr()</span></code></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.addr_.html#torch.Tensor.addr_" title="torch.Tensor.addr_"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.addr_</span></code></a></p></td>
<td><p>In-place version of <a class="reference internal" href="generated/torch.Tensor.addr.html#torch.Tensor.addr" title="torch.Tensor.addr"><code class="xref py py-meth docutils literal notranslate"><span class="pre">addr()</span></code></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.adjoint.html#torch.Tensor.adjoint" title="torch.Tensor.adjoint"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.adjoint</span></code></a></p></td>
<td><p>Alias for <a class="reference internal" href="generated/torch.adjoint.html#torch.adjoint" title="torch.adjoint"><code class="xref py py-func docutils literal notranslate"><span class="pre">adjoint()</span></code></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.allclose.html#torch.Tensor.allclose" title="torch.Tensor.allclose"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.allclose</span></code></a></p></td>
<td><p>See <a class="reference internal" href="generated/torch.allclose.html#torch.allclose" title="torch.allclose"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.allclose()</span></code></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.amax.html#torch.Tensor.amax" title="torch.Tensor.amax"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.amax</span></code></a></p></td>
<td><p>See <a class="reference internal" href="generated/torch.amax.html#torch.amax" title="torch.amax"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.amax()</span></code></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.amin.html#torch.Tensor.amin" title="torch.Tensor.amin"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.amin</span></code></a></p></td>
<td><p>See <a class="reference internal" href="generated/torch.amin.html#torch.amin" title="torch.amin"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.amin()</span></code></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.aminmax.html#torch.Tensor.aminmax" title="torch.Tensor.aminmax"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.aminmax</span></code></a></p></td>
<td><p>See <a class="reference internal" href="generated/torch.aminmax.html#torch.aminmax" title="torch.aminmax"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.aminmax()</span></code></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.angle.html#torch.Tensor.angle" title="torch.Tensor.angle"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.angle</span></code></a></p></td>
<td><p>See <a class="reference internal" href="generated/torch.angle.html#torch.angle" title="torch.angle"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.angle()</span></code></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.apply_.html#torch.Tensor.apply_" title="torch.Tensor.apply_"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.apply_</span></code></a></p></td>
<td><p>Applies the function <code class="xref py py-attr docutils literal notranslate"><span class="pre">callable</span></code> to each element in the tensor, replacing each element with the value returned by <code class="xref py py-attr docutils literal notranslate"><span class="pre">callable</span></code>.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.argmax.html#torch.Tensor.argmax" title="torch.Tensor.argmax"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.argmax</span></code></a></p></td>
<td><p>See <a class="reference internal" href="generated/torch.argmax.html#torch.argmax" title="torch.argmax"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.argmax()</span></code></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.argmin.html#torch.Tensor.argmin" title="torch.Tensor.argmin"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.argmin</span></code></a></p></td>
<td><p>See <a class="reference internal" href="generated/torch.argmin.html#torch.argmin" title="torch.argmin"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.argmin()</span></code></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.argsort.html#torch.Tensor.argsort" title="torch.Tensor.argsort"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.argsort</span></code></a></p></td>
<td><p>See <a class="reference internal" href="generated/torch.argsort.html#torch.argsort" title="torch.argsort"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.argsort()</span></code></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.argwhere.html#torch.Tensor.argwhere" title="torch.Tensor.argwhere"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.argwhere</span></code></a></p></td>
<td><p>See <a class="reference internal" href="generated/torch.argwhere.html#torch.argwhere" title="torch.argwhere"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.argwhere()</span></code></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.asin.html#torch.Tensor.asin" title="torch.Tensor.asin"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.asin</span></code></a></p></td>
<td><p>See <a class="reference internal" href="generated/torch.asin.html#torch.asin" title="torch.asin"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.asin()</span></code></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.asin_.html#torch.Tensor.asin_" title="torch.Tensor.asin_"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.asin_</span></code></a></p></td>
<td><p>In-place version of <a class="reference internal" href="generated/torch.Tensor.asin.html#torch.Tensor.asin" title="torch.Tensor.asin"><code class="xref py py-meth docutils literal notranslate"><span class="pre">asin()</span></code></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.arcsin.html#torch.Tensor.arcsin" title="torch.Tensor.arcsin"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.arcsin</span></code></a></p></td>
<td><p>See <a class="reference internal" href="generated/torch.arcsin.html#torch.arcsin" title="torch.arcsin"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.arcsin()</span></code></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.arcsin_.html#torch.Tensor.arcsin_" title="torch.Tensor.arcsin_"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.arcsin_</span></code></a></p></td>
<td><p>In-place version of <a class="reference internal" href="generated/torch.Tensor.arcsin.html#torch.Tensor.arcsin" title="torch.Tensor.arcsin"><code class="xref py py-meth docutils literal notranslate"><span class="pre">arcsin()</span></code></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.as_strided.html#torch.Tensor.as_strided" title="torch.Tensor.as_strided"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.as_strided</span></code></a></p></td>
<td><p>See <a class="reference internal" href="generated/torch.as_strided.html#torch.as_strided" title="torch.as_strided"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.as_strided()</span></code></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.atan.html#torch.Tensor.atan" title="torch.Tensor.atan"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.atan</span></code></a></p></td>
<td><p>See <a class="reference internal" href="generated/torch.atan.html#torch.atan" title="torch.atan"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.atan()</span></code></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.atan_.html#torch.Tensor.atan_" title="torch.Tensor.atan_"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.atan_</span></code></a></p></td>
<td><p>In-place version of <a class="reference internal" href="generated/torch.Tensor.atan.html#torch.Tensor.atan" title="torch.Tensor.atan"><code class="xref py py-meth docutils literal notranslate"><span class="pre">atan()</span></code></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.arctan.html#torch.Tensor.arctan" title="torch.Tensor.arctan"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.arctan</span></code></a></p></td>
<td><p>See <a class="reference internal" href="generated/torch.arctan.html#torch.arctan" title="torch.arctan"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.arctan()</span></code></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.arctan_.html#torch.Tensor.arctan_" title="torch.Tensor.arctan_"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.arctan_</span></code></a></p></td>
<td><p>In-place version of <a class="reference internal" href="generated/torch.Tensor.arctan.html#torch.Tensor.arctan" title="torch.Tensor.arctan"><code class="xref py py-meth docutils literal notranslate"><span class="pre">arctan()</span></code></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.atan2.html#torch.Tensor.atan2" title="torch.Tensor.atan2"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.atan2</span></code></a></p></td>
<td><p>See <a class="reference internal" href="generated/torch.atan2.html#torch.atan2" title="torch.atan2"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.atan2()</span></code></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.atan2_.html#torch.Tensor.atan2_" title="torch.Tensor.atan2_"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.atan2_</span></code></a></p></td>
<td><p>In-place version of <a class="reference internal" href="generated/torch.Tensor.atan2.html#torch.Tensor.atan2" title="torch.Tensor.atan2"><code class="xref py py-meth docutils literal notranslate"><span class="pre">atan2()</span></code></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.arctan2.html#torch.Tensor.arctan2" title="torch.Tensor.arctan2"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.arctan2</span></code></a></p></td>
<td><p>See <a class="reference internal" href="generated/torch.arctan2.html#torch.arctan2" title="torch.arctan2"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.arctan2()</span></code></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.arctan2_.html#torch.Tensor.arctan2_" title="torch.Tensor.arctan2_"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.arctan2_</span></code></a></p></td>
<td><p>atan2_(other) -> Tensor</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.all.html#torch.Tensor.all" title="torch.Tensor.all"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.all</span></code></a></p></td>
<td><p>See <a class="reference internal" href="generated/torch.all.html#torch.all" title="torch.all"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.all()</span></code></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.any.html#torch.Tensor.any" title="torch.Tensor.any"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.any</span></code></a></p></td>
<td><p>See <a class="reference internal" href="generated/torch.any.html#torch.any" title="torch.any"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.any()</span></code></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.backward.html#torch.Tensor.backward" title="torch.Tensor.backward"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.backward</span></code></a></p></td>
<td><p>Computes the gradient of current tensor wrt graph leaves.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.baddbmm.html#torch.Tensor.baddbmm" title="torch.Tensor.baddbmm"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.baddbmm</span></code></a></p></td>
<td><p>See <a class="reference internal" href="generated/torch.baddbmm.html#torch.baddbmm" title="torch.baddbmm"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.baddbmm()</span></code></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.baddbmm_.html#torch.Tensor.baddbmm_" title="torch.Tensor.baddbmm_"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.baddbmm_</span></code></a></p></td>
<td><p>In-place version of <a class="reference internal" href="generated/torch.Tensor.baddbmm.html#torch.Tensor.baddbmm" title="torch.Tensor.baddbmm"><code class="xref py py-meth docutils literal notranslate"><span class="pre">baddbmm()</span></code></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.bernoulli.html#torch.Tensor.bernoulli" title="torch.Tensor.bernoulli"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.bernoulli</span></code></a></p></td>
<td><p>Returns a result tensor where each <span class="math"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mtext mathvariant="monospace">result[i]</mtext></mrow><annotation encoding="application/x-tex">\texttt{result[i]}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.7778em;vertical-align:-0.0833em;"></span><span class="mord text"><span class="mord texttt">result[i]</span></span></span></span></span></span> is independently sampled from <span class="math"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mtext>Bernoulli</mtext><mo stretchy="false">(</mo><mtext mathvariant="monospace">self[i]</mtext><mo stretchy="false">)</mo></mrow><annotation encoding="application/x-tex">\text{Bernoulli}(\texttt{self[i]})</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord text"><span class="mord">Bernoulli</span></span><span class="mopen">(</span><span class="mord text"><span class="mord texttt">self[i]</span></span><span class="mclose">)</span></span></span></span></span>.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.bernoulli_.html#torch.Tensor.bernoulli_" title="torch.Tensor.bernoulli_"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.bernoulli_</span></code></a></p></td>
<td><p>Fills each location of <code class="xref py py-attr docutils literal notranslate"><span class="pre">self</span></code> with an independent sample from <span class="math"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mtext>Bernoulli</mtext><mo stretchy="false">(</mo><mtext mathvariant="monospace">p</mtext><mo stretchy="false">)</mo></mrow><annotation encoding="application/x-tex">\text{Bernoulli}(\texttt{p})</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord text"><span class="mord">Bernoulli</span></span><span class="mopen">(</span><span class="mord text"><span class="mord texttt">p</span></span><span class="mclose">)</span></span></span></span></span>.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.bfloat16.html#torch.Tensor.bfloat16" title="torch.Tensor.bfloat16"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.bfloat16</span></code></a></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">self.bfloat16()</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">self.to(torch.bfloat16)</span></code>.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.bincount.html#torch.Tensor.bincount" title="torch.Tensor.bincount"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.bincount</span></code></a></p></td>
<td><p>See <a class="reference internal" href="generated/torch.bincount.html#torch.bincount" title="torch.bincount"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.bincount()</span></code></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.bitwise_not.html#torch.Tensor.bitwise_not" title="torch.Tensor.bitwise_not"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.bitwise_not</span></code></a></p></td>
<td><p>See <a class="reference internal" href="generated/torch.bitwise_not.html#torch.bitwise_not" title="torch.bitwise_not"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.bitwise_not()</span></code></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.bitwise_not_.html#torch.Tensor.bitwise_not_" title="torch.Tensor.bitwise_not_"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.bitwise_not_</span></code></a></p></td>
<td><p>In-place version of <a class="reference internal" href="generated/torch.Tensor.bitwise_not.html#torch.Tensor.bitwise_not" title="torch.Tensor.bitwise_not"><code class="xref py py-meth docutils literal notranslate"><span class="pre">bitwise_not()</span></code></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.bitwise_and.html#torch.Tensor.bitwise_and" title="torch.Tensor.bitwise_and"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.bitwise_and</span></code></a></p></td>
<td><p>See <a class="reference internal" href="generated/torch.bitwise_and.html#torch.bitwise_and" title="torch.bitwise_and"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.bitwise_and()</span></code></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.bitwise_and_.html#torch.Tensor.bitwise_and_" title="torch.Tensor.bitwise_and_"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.bitwise_and_</span></code></a></p></td>
<td><p>In-place version of <a class="reference internal" href="generated/torch.Tensor.bitwise_and.html#torch.Tensor.bitwise_and" title="torch.Tensor.bitwise_and"><code class="xref py py-meth docutils literal notranslate"><span class="pre">bitwise_and()</span></code></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.bitwise_or.html#torch.Tensor.bitwise_or" title="torch.Tensor.bitwise_or"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.bitwise_or</span></code></a></p></td>
<td><p>See <a class="reference internal" href="generated/torch.bitwise_or.html#torch.bitwise_or" title="torch.bitwise_or"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.bitwise_or()</span></code></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.bitwise_or_.html#torch.Tensor.bitwise_or_" title="torch.Tensor.bitwise_or_"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.bitwise_or_</span></code></a></p></td>
<td><p>In-place version of <a class="reference internal" href="generated/torch.Tensor.bitwise_or.html#torch.Tensor.bitwise_or" title="torch.Tensor.bitwise_or"><code class="xref py py-meth docutils literal notranslate"><span class="pre">bitwise_or()</span></code></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.bitwise_xor.html#torch.Tensor.bitwise_xor" title="torch.Tensor.bitwise_xor"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.bitwise_xor</span></code></a></p></td>
<td><p>See <a class="reference internal" href="generated/torch.bitwise_xor.html#torch.bitwise_xor" title="torch.bitwise_xor"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.bitwise_xor()</span></code></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.bitwise_xor_.html#torch.Tensor.bitwise_xor_" title="torch.Tensor.bitwise_xor_"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.bitwise_xor_</span></code></a></p></td>
<td><p>In-place version of <a class="reference internal" href="generated/torch.Tensor.bitwise_xor.html#torch.Tensor.bitwise_xor" title="torch.Tensor.bitwise_xor"><code class="xref py py-meth docutils literal notranslate"><span class="pre">bitwise_xor()</span></code></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.bitwise_left_shift.html#torch.Tensor.bitwise_left_shift" title="torch.Tensor.bitwise_left_shift"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.bitwise_left_shift</span></code></a></p></td>
<td><p>See <a class="reference internal" href="generated/torch.bitwise_left_shift.html#torch.bitwise_left_shift" title="torch.bitwise_left_shift"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.bitwise_left_shift()</span></code></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.bitwise_left_shift_.html#torch.Tensor.bitwise_left_shift_" title="torch.Tensor.bitwise_left_shift_"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.bitwise_left_shift_</span></code></a></p></td>
<td><p>In-place version of <a class="reference internal" href="generated/torch.Tensor.bitwise_left_shift.html#torch.Tensor.bitwise_left_shift" title="torch.Tensor.bitwise_left_shift"><code class="xref py py-meth docutils literal notranslate"><span class="pre">bitwise_left_shift()</span></code></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.bitwise_right_shift.html#torch.Tensor.bitwise_right_shift" title="torch.Tensor.bitwise_right_shift"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.bitwise_right_shift</span></code></a></p></td>
<td><p>See <a class="reference internal" href="generated/torch.bitwise_right_shift.html#torch.bitwise_right_shift" title="torch.bitwise_right_shift"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.bitwise_right_shift()</span></code></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.bitwise_right_shift_.html#torch.Tensor.bitwise_right_shift_" title="torch.Tensor.bitwise_right_shift_"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.bitwise_right_shift_</span></code></a></p></td>
<td><p>In-place version of <a class="reference internal" href="generated/torch.Tensor.bitwise_right_shift.html#torch.Tensor.bitwise_right_shift" title="torch.Tensor.bitwise_right_shift"><code class="xref py py-meth docutils literal notranslate"><span class="pre">bitwise_right_shift()</span></code></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.bmm.html#torch.Tensor.bmm" title="torch.Tensor.bmm"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.bmm</span></code></a></p></td>
<td><p>See <a class="reference internal" href="generated/torch.bmm.html#torch.bmm" title="torch.bmm"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.bmm()</span></code></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/torch.Tensor.bool.html#torch.Tensor.bool" title="torch.Tensor.bool"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.bool</span></code></a></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">self.bool()</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">self.to(torch.bool)</span></code>.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/torch.Tensor.byte.html#torch.Tensor.byte" title="torch.Tensor.byte"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tensor.byte</span></code></a></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">self.byte()</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">self.to(torch.uint8)</span></code>.</p></td>