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<li class="toctree-l1"><a class="reference internal" href="notes/amp_examples.html">Automatic Mixed Precision examples</a></li>
<li class="toctree-l1"><a class="reference internal" href="notes/autograd.html">Autograd mechanics</a></li>
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<div class="section" id="type-info">
<span id="type-info-doc"></span><h1>Type Info<a class="headerlink" href="#type-info" title="Permalink to this headline">¶</a></h1>
<p>The numerical properties of a <a class="reference internal" href="tensor_attributes.html#torch.torch.dtype" title="torch.torch.dtype"><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.dtype</span></code></a> can be accessed through either the <a class="reference internal" href="#torch.torch.finfo" title="torch.torch.finfo"><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.finfo</span></code></a> or the <a class="reference internal" href="#torch.torch.iinfo" title="torch.torch.iinfo"><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.iinfo</span></code></a>.</p>
<div class="section" id="torch-finfo">
<span id="finfo-doc"></span><h2>torch.finfo<a class="headerlink" href="#torch-finfo" title="Permalink to this headline">¶</a></h2>
<dl class="class">
<dt id="torch.torch.finfo">
<em class="property">class </em><code class="sig-prename descclassname">torch.</code><code class="sig-name descname">finfo</code><a class="headerlink" href="#torch.torch.finfo" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<p>A <a class="reference internal" href="#torch.torch.finfo" title="torch.torch.finfo"><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.finfo</span></code></a> is an object that represents the numerical properties of a floating point
<a class="reference internal" href="tensor_attributes.html#torch.torch.dtype" title="torch.torch.dtype"><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.dtype</span></code></a>, (i.e. <code class="docutils literal notranslate"><span class="pre">torch.float32</span></code>, <code class="docutils literal notranslate"><span class="pre">torch.float64</span></code>, and <code class="docutils literal notranslate"><span class="pre">torch.float16</span></code>). This is similar to <a class="reference external" href="https://docs.scipy.org/doc/numpy/reference/generated/numpy.finfo.html">numpy.finfo</a>.</p>
<p>A <a class="reference internal" href="#torch.torch.finfo" title="torch.torch.finfo"><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.finfo</span></code></a> provides the following attributes:</p>
<table class="docutils colwidths-auto align-default">
<thead>
<tr class="row-odd"><th class="head"><p>Name</p></th>
<th class="head"><p>Type</p></th>
<th class="head"><p>Description</p></th>
</tr>
</thead>
<tbody>
<tr class="row-even"><td><p>bits</p></td>
<td><p>int</p></td>
<td><p>The number of bits occupied by the type.</p></td>
</tr>
<tr class="row-odd"><td><p>eps</p></td>
<td><p>float</p></td>
<td><p>The smallest representable number such that <code class="docutils literal notranslate"><span class="pre">1.0</span> <span class="pre">+</span> <span class="pre">eps</span> <span class="pre">!=</span> <span class="pre">1.0</span></code>.</p></td>
</tr>
<tr class="row-even"><td><p>max</p></td>
<td><p>float</p></td>
<td><p>The largest representable number.</p></td>
</tr>
<tr class="row-odd"><td><p>min</p></td>
<td><p>float</p></td>
<td><p>The smallest representable number (typically <code class="docutils literal notranslate"><span class="pre">-max</span></code>).</p></td>
</tr>
<tr class="row-even"><td><p>tiny</p></td>
<td><p>float</p></td>
<td><p>The smallest positive representable number.</p></td>
</tr>
<tr class="row-odd"><td><p>resolution</p></td>
<td><p>float</p></td>
<td><p>The approximate decimal resolution of this type, i.e., <code class="docutils literal notranslate"><span class="pre">10**-precision</span></code>.</p></td>
</tr>
</tbody>
</table>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>The constructor of <a class="reference internal" href="#torch.torch.finfo" title="torch.torch.finfo"><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.finfo</span></code></a> can be called without argument, in which case the class is created for the pytorch default dtype (as returned by <a class="reference internal" href="generated/torch.get_default_dtype.html#torch.get_default_dtype" title="torch.get_default_dtype"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.get_default_dtype()</span></code></a>).</p>
</div>
</div>
<div class="section" id="torch-iinfo">
<span id="iinfo-doc"></span><h2>torch.iinfo<a class="headerlink" href="#torch-iinfo" title="Permalink to this headline">¶</a></h2>
<dl class="class">
<dt id="torch.torch.iinfo">
<em class="property">class </em><code class="sig-prename descclassname">torch.</code><code class="sig-name descname">iinfo</code><a class="headerlink" href="#torch.torch.iinfo" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<p>A <a class="reference internal" href="#torch.torch.iinfo" title="torch.torch.iinfo"><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.iinfo</span></code></a> is an object that represents the numerical properties of a integer
<a class="reference internal" href="tensor_attributes.html#torch.torch.dtype" title="torch.torch.dtype"><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.dtype</span></code></a> (i.e. <code class="docutils literal notranslate"><span class="pre">torch.uint8</span></code>, <code class="docutils literal notranslate"><span class="pre">torch.int8</span></code>, <code class="docutils literal notranslate"><span class="pre">torch.int16</span></code>, <code class="docutils literal notranslate"><span class="pre">torch.int32</span></code>, and <code class="docutils literal notranslate"><span class="pre">torch.int64</span></code>). This is similar to <a class="reference external" href="https://docs.scipy.org/doc/numpy/reference/generated/numpy.iinfo.html">numpy.iinfo</a>.</p>
<p>A <a class="reference internal" href="#torch.torch.iinfo" title="torch.torch.iinfo"><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.iinfo</span></code></a> provides the following attributes:</p>
<table class="docutils colwidths-auto align-default">
<thead>
<tr class="row-odd"><th class="head"><p>Name</p></th>
<th class="head"><p>Type</p></th>
<th class="head"><p>Description</p></th>
</tr>
</thead>
<tbody>
<tr class="row-even"><td><p>bits</p></td>
<td><p>int</p></td>
<td><p>The number of bits occupied by the type.</p></td>
</tr>
<tr class="row-odd"><td><p>max</p></td>
<td><p>int</p></td>
<td><p>The largest representable number.</p></td>
</tr>
<tr class="row-even"><td><p>min</p></td>
<td><p>int</p></td>
<td><p>The smallest representable number.</p></td>
</tr>
</tbody>
</table>
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