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<div class="section" id="identity">
<h1>Identity<a class="headerlink" href="#identity" title="Permalink to this headline">¶</a></h1>
<dl class="class">
<dt id="torch.nn.utils.prune.Identity">
<em class="property">class </em><code class="sig-prename descclassname">torch.nn.utils.prune.</code><code class="sig-name descname">Identity</code><a class="reference internal" href="../_modules/torch/nn/utils/prune.html#Identity"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#torch.nn.utils.prune.Identity" title="Permalink to this definition">¶</a></dt>
<dd><p>Utility pruning method that does not prune any units but generates the
pruning parametrization with a mask of ones.</p>
<dl class="method">
<dt id="torch.nn.utils.prune.Identity.apply">
<em class="property">classmethod </em><code class="sig-name descname">apply</code><span class="sig-paren">(</span><em class="sig-param">module</em>, <em class="sig-param">name</em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/torch/nn/utils/prune.html#Identity.apply"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#torch.nn.utils.prune.Identity.apply" title="Permalink to this definition">¶</a></dt>
<dd><p>Adds the forward pre-hook that enables pruning on the fly and
the reparametrization of a tensor in terms of the original tensor
and the pruning mask.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>module</strong> (<a class="reference internal" href="torch.nn.Module.html#torch.nn.Module" title="torch.nn.Module"><em>nn.Module</em></a>) – module containing the tensor to prune</p></li>
<li><p><strong>name</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.9)"><em>str</em></a>) – parameter name within <code class="docutils literal notranslate"><span class="pre">module</span></code> on which pruning
will act.</p></li>
</ul>
</dd>
</dl>
</dd></dl>
<dl class="method">
<dt id="torch.nn.utils.prune.Identity.apply_mask">
<code class="sig-name descname">apply_mask</code><span class="sig-paren">(</span><em class="sig-param">module</em><span class="sig-paren">)</span><a class="headerlink" href="#torch.nn.utils.prune.Identity.apply_mask" title="Permalink to this definition">¶</a></dt>
<dd><p>Simply handles the multiplication between the parameter being
pruned and the generated mask.
Fetches the mask and the original tensor from the module
and returns the pruned version of the tensor.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>module</strong> (<a class="reference internal" href="torch.nn.Module.html#torch.nn.Module" title="torch.nn.Module"><em>nn.Module</em></a>) – module containing the tensor to prune</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>pruned version of the input tensor</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>pruned_tensor (<a class="reference internal" href="../tensors.html#torch.Tensor" title="torch.Tensor">torch.Tensor</a>)</p>
</dd>
</dl>
</dd></dl>
<dl class="method">
<dt id="torch.nn.utils.prune.Identity.prune">
<code class="sig-name descname">prune</code><span class="sig-paren">(</span><em class="sig-param">t</em>, <em class="sig-param">default_mask=None</em><span class="sig-paren">)</span><a class="headerlink" href="#torch.nn.utils.prune.Identity.prune" title="Permalink to this definition">¶</a></dt>
<dd><p>Computes and returns a pruned version of input tensor <code class="docutils literal notranslate"><span class="pre">t</span></code>
according to the pruning rule specified in <code class="xref py py-meth docutils literal notranslate"><span class="pre">compute_mask()</span></code>.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>t</strong> (<a class="reference internal" href="../tensors.html#torch.Tensor" title="torch.Tensor"><em>torch.Tensor</em></a>) – tensor to prune (of same dimensions as
<code class="docutils literal notranslate"><span class="pre">default_mask</span></code>).</p></li>
<li><p><strong>default_mask</strong> (<a class="reference internal" href="../tensors.html#torch.Tensor" title="torch.Tensor"><em>torch.Tensor</em></a><em>, </em><em>optional</em>) – mask from previous pruning
iteration, if any. To be considered when determining what
portion of the tensor that pruning should act on. If None,
default to a mask of ones.</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>pruned version of tensor <code class="docutils literal notranslate"><span class="pre">t</span></code>.</p>
</dd>
</dl>
</dd></dl>
<dl class="method">
<dt id="torch.nn.utils.prune.Identity.remove">
<code class="sig-name descname">remove</code><span class="sig-paren">(</span><em class="sig-param">module</em><span class="sig-paren">)</span><a class="headerlink" href="#torch.nn.utils.prune.Identity.remove" title="Permalink to this definition">¶</a></dt>
<dd><p>Removes the pruning reparameterization from a module. The pruned
parameter named <code class="docutils literal notranslate"><span class="pre">name</span></code> remains permanently pruned, and the parameter
named <code class="docutils literal notranslate"><span class="pre">name+'_orig'</span></code> is removed from the parameter list. Similarly,
the buffer named <code class="docutils literal notranslate"><span class="pre">name+'_mask'</span></code> is removed from the buffers.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>Pruning itself is NOT undone or reversed!</p>
</div>
</dd></dl>
</dd></dl>
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