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<!DOCTYPE html>
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<title>brevitas.core.function_wrapper package — Brevitas 0.2.0b1.dev0+gc32fb31.d20210127 documentation</title>
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<li><a class="reference internal" href="#">brevitas.core.function_wrapper package</a><ul>
<li><a class="reference internal" href="#submodules">Submodules</a></li>
<li><a class="reference internal" href="#module-brevitas.core.function_wrapper.clamp">brevitas.core.function_wrapper.clamp module</a></li>
<li><a class="reference internal" href="#module-brevitas.core.function_wrapper.misc">brevitas.core.function_wrapper.misc module</a></li>
<li><a class="reference internal" href="#module-brevitas.core.function_wrapper.ops_ste">brevitas.core.function_wrapper.ops_ste module</a></li>
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<div class="section" id="brevitas-core-function-wrapper-package">
<h1>brevitas.core.function_wrapper package<a class="headerlink" href="#brevitas-core-function-wrapper-package" title="Permalink to this headline">¶</a></h1>
<div class="section" id="submodules">
<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this headline">¶</a></h2>
</div>
<div class="section" id="module-brevitas.core.function_wrapper.clamp">
<span id="brevitas-core-function-wrapper-clamp-module"></span><h2>brevitas.core.function_wrapper.clamp module<a class="headerlink" href="#module-brevitas.core.function_wrapper.clamp" title="Permalink to this headline">¶</a></h2>
<p>ScriptModule wrappers for various variants of clamping.</p>
<dl class="py class">
<dt id="brevitas.core.function_wrapper.clamp.ClampMin">
<em class="property">class </em><code class="sig-prename descclassname">brevitas.core.function_wrapper.clamp.</code><code class="sig-name descname">ClampMin</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">min_val</span></em><span class="sig-paren">)</span><a class="headerlink" href="#brevitas.core.function_wrapper.clamp.ClampMin" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torch.nn.modules.module.Module</span></code></p>
<p>ScriptModule wrapper for <code class="xref py py-func docutils literal notranslate"><span class="pre">clamp_min()</span></code>.</p>
<p class="rubric">Examples</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">clamp_min</span> <span class="o">=</span> <span class="n">ClampMin</span><span class="p">(</span><span class="n">min_val</span><span class="o">=-</span><span class="mf">2.0</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">clamp_min</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">(</span><span class="o">-</span><span class="mf">3.0</span><span class="p">))</span>
<span class="go">tensor(-2.)</span>
</pre></div>
</div>
<dl class="py method">
<dt id="brevitas.core.function_wrapper.clamp.ClampMin.forward">
<code class="sig-name descname">forward</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">x</span></em><span class="sig-paren">)</span><a class="headerlink" href="#brevitas.core.function_wrapper.clamp.ClampMin.forward" title="Permalink to this definition">¶</a></dt>
<dd><p>Defines the computation performed at every call.</p>
<p>Should be overridden by all subclasses.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>Although the recipe for forward pass needs to be defined within
this function, one should call the <code class="xref py py-class docutils literal notranslate"><span class="pre">Module</span></code> instance afterwards
instead of this since the former takes care of running the
registered hooks while the latter silently ignores them.</p>
</div>
</dd></dl>
<dl class="py attribute">
<dt id="brevitas.core.function_wrapper.clamp.ClampMin.training">
<code class="sig-name descname">training</code><em class="property">: bool</em><a class="headerlink" href="#brevitas.core.function_wrapper.clamp.ClampMin.training" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
</dd></dl>
<dl class="py class">
<dt id="brevitas.core.function_wrapper.clamp.ScalarClamp">
<em class="property">class </em><code class="sig-prename descclassname">brevitas.core.function_wrapper.clamp.</code><code class="sig-name descname">ScalarClamp</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">min_val</span></em>, <em class="sig-param"><span class="n">max_val</span></em><span class="sig-paren">)</span><a class="headerlink" href="#brevitas.core.function_wrapper.clamp.ScalarClamp" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torch.nn.modules.module.Module</span></code></p>
<p>ScriptModule wrapper for <code class="xref py py-func docutils literal notranslate"><span class="pre">clamp()</span></code>.</p>
<p class="rubric">Examples</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">scalar_clamp</span> <span class="o">=</span> <span class="n">ScalarClamp</span><span class="p">(</span><span class="n">min_val</span><span class="o">=-</span><span class="mf">2.0</span><span class="p">,</span> <span class="n">max_val</span><span class="o">=</span><span class="mf">2.0</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">scalar_clamp</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">([</span><span class="o">-</span><span class="mf">3.0</span><span class="p">,</span> <span class="mf">3.0</span><span class="p">]))</span>
<span class="go">tensor([-2., 2.])</span>
</pre></div>
</div>
<dl class="py method">
<dt id="brevitas.core.function_wrapper.clamp.ScalarClamp.forward">
<code class="sig-name descname">forward</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">x</span></em><span class="sig-paren">)</span><a class="headerlink" href="#brevitas.core.function_wrapper.clamp.ScalarClamp.forward" title="Permalink to this definition">¶</a></dt>
<dd><p>Defines the computation performed at every call.</p>
<p>Should be overridden by all subclasses.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>Although the recipe for forward pass needs to be defined within
this function, one should call the <code class="xref py py-class docutils literal notranslate"><span class="pre">Module</span></code> instance afterwards
instead of this since the former takes care of running the
registered hooks while the latter silently ignores them.</p>
</div>
</dd></dl>
<dl class="py attribute">
<dt id="brevitas.core.function_wrapper.clamp.ScalarClamp.training">
<code class="sig-name descname">training</code><em class="property">: bool</em><a class="headerlink" href="#brevitas.core.function_wrapper.clamp.ScalarClamp.training" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
</dd></dl>
<dl class="py class">
<dt id="brevitas.core.function_wrapper.clamp.TensorClamp">
<em class="property">class </em><code class="sig-prename descclassname">brevitas.core.function_wrapper.clamp.</code><code class="sig-name descname">TensorClamp</code><a class="headerlink" href="#brevitas.core.function_wrapper.clamp.TensorClamp" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torch.nn.modules.module.Module</span></code></p>
<p>ScriptModule wrapper for <a class="reference internal" href="brevitas.function.html#brevitas.function.ops.tensor_clamp" title="brevitas.function.ops.tensor_clamp"><code class="xref py py-func docutils literal notranslate"><span class="pre">tensor_clamp()</span></code></a>.</p>
<p class="rubric">Examples</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">tensor_clamp</span> <span class="o">=</span> <span class="n">TensorClamp</span><span class="p">()</span>
<span class="gp">>>> </span><span class="n">min_val</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="o">-</span><span class="mf">2.0</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">max_val</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">2.0</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">tensor_clamp</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">([</span><span class="o">-</span><span class="mf">3.0</span><span class="p">,</span> <span class="mf">3.0</span><span class="p">]),</span> <span class="n">min_val</span><span class="p">,</span> <span class="n">max_val</span><span class="p">)</span>
<span class="go">tensor([-2., 2.])</span>
</pre></div>
</div>
<dl class="py method">
<dt id="brevitas.core.function_wrapper.clamp.TensorClamp.forward">
<code class="sig-name descname">forward</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">x</span></em>, <em class="sig-param"><span class="n">min_val</span></em>, <em class="sig-param"><span class="n">max_val</span></em><span class="sig-paren">)</span><a class="headerlink" href="#brevitas.core.function_wrapper.clamp.TensorClamp.forward" title="Permalink to this definition">¶</a></dt>
<dd><p>Defines the computation performed at every call.</p>
<p>Should be overridden by all subclasses.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>Although the recipe for forward pass needs to be defined within
this function, one should call the <code class="xref py py-class docutils literal notranslate"><span class="pre">Module</span></code> instance afterwards
instead of this since the former takes care of running the
registered hooks while the latter silently ignores them.</p>
</div>
</dd></dl>
<dl class="py attribute">
<dt id="brevitas.core.function_wrapper.clamp.TensorClamp.training">
<code class="sig-name descname">training</code><em class="property">: bool</em><a class="headerlink" href="#brevitas.core.function_wrapper.clamp.TensorClamp.training" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
</dd></dl>
</div>
<div class="section" id="module-brevitas.core.function_wrapper.misc">
<span id="brevitas-core-function-wrapper-misc-module"></span><h2>brevitas.core.function_wrapper.misc module<a class="headerlink" href="#module-brevitas.core.function_wrapper.misc" title="Permalink to this headline">¶</a></h2>
<p>A collection of miscellaneous ScriptModule used in various quantizers.</p>
<dl class="py class">
<dt id="brevitas.core.function_wrapper.misc.Identity">
<em class="property">class </em><code class="sig-prename descclassname">brevitas.core.function_wrapper.misc.</code><code class="sig-name descname">Identity</code><a class="headerlink" href="#brevitas.core.function_wrapper.misc.Identity" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torch.nn.modules.module.Module</span></code></p>
<p>Identity ScriptModule.</p>
<p class="rubric">Examples</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">identity</span> <span class="o">=</span> <span class="n">Identity</span><span class="p">()</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">randn</span><span class="p">(</span><span class="n">size</span><span class="o">=</span><span class="p">[</span><span class="mi">10</span><span class="p">,])</span>
<span class="gp">>>> </span><span class="n">y</span> <span class="o">=</span> <span class="n">identity</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">y</span> <span class="ow">is</span> <span class="n">x</span>
<span class="go">True</span>
</pre></div>
</div>
<dl class="py method">
<dt id="brevitas.core.function_wrapper.misc.Identity.forward">
<code class="sig-name descname">forward</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">x</span></em><span class="sig-paren">)</span><a class="headerlink" href="#brevitas.core.function_wrapper.misc.Identity.forward" title="Permalink to this definition">¶</a></dt>
<dd><p>Defines the computation performed at every call.</p>
<p>Should be overridden by all subclasses.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>Although the recipe for forward pass needs to be defined within
this function, one should call the <code class="xref py py-class docutils literal notranslate"><span class="pre">Module</span></code> instance afterwards
instead of this since the former takes care of running the
registered hooks while the latter silently ignores them.</p>
</div>
<dl class="field-list simple">
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></p>
</dd>
</dl>
</dd></dl>
<dl class="py attribute">
<dt id="brevitas.core.function_wrapper.misc.Identity.training">
<code class="sig-name descname">training</code><em class="property">: bool</em><a class="headerlink" href="#brevitas.core.function_wrapper.misc.Identity.training" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
</dd></dl>
<dl class="py class">
<dt id="brevitas.core.function_wrapper.misc.InplaceLogTwo">
<em class="property">class </em><code class="sig-prename descclassname">brevitas.core.function_wrapper.misc.</code><code class="sig-name descname">InplaceLogTwo</code><a class="headerlink" href="#brevitas.core.function_wrapper.misc.InplaceLogTwo" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torch.nn.modules.module.Module</span></code></p>
<p>ScriptModule wrapper for <code class="xref py py-func docutils literal notranslate"><span class="pre">log2_()</span></code>.</p>
<p class="rubric">Examples</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">inplace_log_two</span> <span class="o">=</span> <span class="n">InplaceLogTwo</span><span class="p">()</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">8.0</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">inplace_log_two</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">x</span>
<span class="go">tensor(3.)</span>
</pre></div>
</div>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>The forward method returns None.</p>
</div>
<dl class="py method">
<dt id="brevitas.core.function_wrapper.misc.InplaceLogTwo.forward">
<code class="sig-name descname">forward</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">x</span></em><span class="sig-paren">)</span><a class="headerlink" href="#brevitas.core.function_wrapper.misc.InplaceLogTwo.forward" title="Permalink to this definition">¶</a></dt>
<dd><p>Defines the computation performed at every call.</p>
<p>Should be overridden by all subclasses.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>Although the recipe for forward pass needs to be defined within
this function, one should call the <code class="xref py py-class docutils literal notranslate"><span class="pre">Module</span></code> instance afterwards
instead of this since the former takes care of running the
registered hooks while the latter silently ignores them.</p>
</div>
<dl class="field-list simple">
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">None</span></code></p>
</dd>
</dl>
</dd></dl>
<dl class="py attribute">
<dt id="brevitas.core.function_wrapper.misc.InplaceLogTwo.training">
<code class="sig-name descname">training</code><em class="property">: bool</em><a class="headerlink" href="#brevitas.core.function_wrapper.misc.InplaceLogTwo.training" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
</dd></dl>
<dl class="py class">
<dt id="brevitas.core.function_wrapper.misc.InplaceNoOp">
<em class="property">class </em><code class="sig-prename descclassname">brevitas.core.function_wrapper.misc.</code><code class="sig-name descname">InplaceNoOp</code><a class="headerlink" href="#brevitas.core.function_wrapper.misc.InplaceNoOp" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torch.nn.modules.module.Module</span></code></p>
<p>ScriptModule in-place no-op placehoder.</p>
<p class="rubric">Examples</p>
<div class="doctest 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">1.0</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">no_op</span> <span class="o">=</span> <span class="n">InplaceNoOp</span><span class="p">()</span>
<span class="gp">>>> </span><span class="n">no_op</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
</pre></div>
</div>
<dl class="py method">
<dt id="brevitas.core.function_wrapper.misc.InplaceNoOp.forward">
<code class="sig-name descname">forward</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">x</span></em><span class="sig-paren">)</span><a class="headerlink" href="#brevitas.core.function_wrapper.misc.InplaceNoOp.forward" title="Permalink to this definition">¶</a></dt>
<dd><p>Defines the computation performed at every call.</p>
<p>Should be overridden by all subclasses.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>Although the recipe for forward pass needs to be defined within
this function, one should call the <code class="xref py py-class docutils literal notranslate"><span class="pre">Module</span></code> instance afterwards
instead of this since the former takes care of running the
registered hooks while the latter silently ignores them.</p>
</div>
<dl class="field-list simple">
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">None</span></code></p>
</dd>
</dl>
</dd></dl>
<dl class="py attribute">
<dt id="brevitas.core.function_wrapper.misc.InplaceNoOp.training">
<code class="sig-name descname">training</code><em class="property">: bool</em><a class="headerlink" href="#brevitas.core.function_wrapper.misc.InplaceNoOp.training" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
</dd></dl>
<dl class="py class">
<dt id="brevitas.core.function_wrapper.misc.LogTwo">
<em class="property">class </em><code class="sig-prename descclassname">brevitas.core.function_wrapper.misc.</code><code class="sig-name descname">LogTwo</code><a class="headerlink" href="#brevitas.core.function_wrapper.misc.LogTwo" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torch.nn.modules.module.Module</span></code></p>
<p>ScriptModule wrapper for <code class="xref py py-func docutils literal notranslate"><span class="pre">log2()</span></code>.</p>
<p class="rubric">Examples</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">log_two</span> <span class="o">=</span> <span class="n">LogTwo</span><span class="p">()</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">8.0</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">log_two</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
<span class="go">tensor(3.)</span>
</pre></div>
</div>
<dl class="py method">
<dt id="brevitas.core.function_wrapper.misc.LogTwo.forward">
<code class="sig-name descname">forward</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">x</span></em><span class="sig-paren">)</span><a class="headerlink" href="#brevitas.core.function_wrapper.misc.LogTwo.forward" title="Permalink to this definition">¶</a></dt>
<dd><p>Defines the computation performed at every call.</p>
<p>Should be overridden by all subclasses.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>Although the recipe for forward pass needs to be defined within
this function, one should call the <code class="xref py py-class docutils literal notranslate"><span class="pre">Module</span></code> instance afterwards
instead of this since the former takes care of running the
registered hooks while the latter silently ignores them.</p>
</div>
<dl class="field-list simple">
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></p>
</dd>
</dl>
</dd></dl>
<dl class="py attribute">
<dt id="brevitas.core.function_wrapper.misc.LogTwo.training">
<code class="sig-name descname">training</code><em class="property">: bool</em><a class="headerlink" href="#brevitas.core.function_wrapper.misc.LogTwo.training" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
</dd></dl>
<dl class="py class">
<dt id="brevitas.core.function_wrapper.misc.PowerOfTwo">
<em class="property">class </em><code class="sig-prename descclassname">brevitas.core.function_wrapper.misc.</code><code class="sig-name descname">PowerOfTwo</code><a class="headerlink" href="#brevitas.core.function_wrapper.misc.PowerOfTwo" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torch.nn.modules.module.Module</span></code></p>
<p>ScriptModule implementation of 2.0 ** x.</p>
<p class="rubric">Examples</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">power_of_two</span> <span class="o">=</span> <span class="n">PowerOfTwo</span><span class="p">()</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">5.0</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">power_of_two</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
<span class="go">tensor(32.)</span>
</pre></div>
</div>
<dl class="py method">
<dt id="brevitas.core.function_wrapper.misc.PowerOfTwo.forward">
<code class="sig-name descname">forward</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">x</span></em><span class="sig-paren">)</span><a class="headerlink" href="#brevitas.core.function_wrapper.misc.PowerOfTwo.forward" title="Permalink to this definition">¶</a></dt>
<dd><p>Defines the computation performed at every call.</p>
<p>Should be overridden by all subclasses.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>Although the recipe for forward pass needs to be defined within
this function, one should call the <code class="xref py py-class docutils literal notranslate"><span class="pre">Module</span></code> instance afterwards
instead of this since the former takes care of running the
registered hooks while the latter silently ignores them.</p>
</div>
<dl class="field-list simple">
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></p>
</dd>
</dl>
</dd></dl>
<dl class="py attribute">
<dt id="brevitas.core.function_wrapper.misc.PowerOfTwo.training">
<code class="sig-name descname">training</code><em class="property">: bool</em><a class="headerlink" href="#brevitas.core.function_wrapper.misc.PowerOfTwo.training" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
</dd></dl>
</div>
<div class="section" id="module-brevitas.core.function_wrapper.ops_ste">
<span id="brevitas-core-function-wrapper-ops-ste-module"></span><h2>brevitas.core.function_wrapper.ops_ste module<a class="headerlink" href="#module-brevitas.core.function_wrapper.ops_ste" title="Permalink to this headline">¶</a></h2>
<p>ScriptModule wrappers of various functions defined in <a class="reference internal" href="brevitas.function.html#module-brevitas.function.ops_ste" title="brevitas.function.ops_ste"><code class="xref py py-obj docutils literal notranslate"><span class="pre">ops_ste</span></code></a>.</p>
<dl class="py class">
<dt id="brevitas.core.function_wrapper.ops_ste.CeilSte">
<em class="property">class </em><code class="sig-prename descclassname">brevitas.core.function_wrapper.ops_ste.</code><code class="sig-name descname">CeilSte</code><a class="headerlink" href="#brevitas.core.function_wrapper.ops_ste.CeilSte" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torch.nn.modules.module.Module</span></code></p>
<p>ScriptModule wrapper for <a class="reference internal" href="brevitas.function.html#brevitas.function.ops_ste.ceil_ste" title="brevitas.function.ops_ste.ceil_ste"><code class="xref py py-func docutils literal notranslate"><span class="pre">ceil_ste()</span></code></a>.</p>
<dl class="py method">
<dt id="brevitas.core.function_wrapper.ops_ste.CeilSte.forward">
<code class="sig-name descname">forward</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">x</span></em><span class="sig-paren">)</span><a class="headerlink" href="#brevitas.core.function_wrapper.ops_ste.CeilSte.forward" title="Permalink to this definition">¶</a></dt>
<dd><p>Defines the computation performed at every call.</p>
<p>Should be overridden by all subclasses.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>Although the recipe for forward pass needs to be defined within
this function, one should call the <code class="xref py py-class docutils literal notranslate"><span class="pre">Module</span></code> instance afterwards
instead of this since the former takes care of running the
registered hooks while the latter silently ignores them.</p>
</div>
</dd></dl>
<dl class="py attribute">
<dt id="brevitas.core.function_wrapper.ops_ste.CeilSte.training">
<code class="sig-name descname">training</code><em class="property">: bool</em><a class="headerlink" href="#brevitas.core.function_wrapper.ops_ste.CeilSte.training" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
</dd></dl>
<dl class="py class">
<dt id="brevitas.core.function_wrapper.ops_ste.FloorSte">
<em class="property">class </em><code class="sig-prename descclassname">brevitas.core.function_wrapper.ops_ste.</code><code class="sig-name descname">FloorSte</code><a class="headerlink" href="#brevitas.core.function_wrapper.ops_ste.FloorSte" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torch.nn.modules.module.Module</span></code></p>
<p>ScriptModule wrapper for <a class="reference internal" href="brevitas.function.html#brevitas.function.ops_ste.floor_ste" title="brevitas.function.ops_ste.floor_ste"><code class="xref py py-func docutils literal notranslate"><span class="pre">floor_ste()</span></code></a>.</p>
<dl class="py method">
<dt id="brevitas.core.function_wrapper.ops_ste.FloorSte.forward">
<code class="sig-name descname">forward</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">x</span></em><span class="sig-paren">)</span><a class="headerlink" href="#brevitas.core.function_wrapper.ops_ste.FloorSte.forward" title="Permalink to this definition">¶</a></dt>
<dd><p>Defines the computation performed at every call.</p>
<p>Should be overridden by all subclasses.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>Although the recipe for forward pass needs to be defined within
this function, one should call the <code class="xref py py-class docutils literal notranslate"><span class="pre">Module</span></code> instance afterwards
instead of this since the former takes care of running the
registered hooks while the latter silently ignores them.</p>
</div>
</dd></dl>
<dl class="py attribute">
<dt id="brevitas.core.function_wrapper.ops_ste.FloorSte.training">
<code class="sig-name descname">training</code><em class="property">: bool</em><a class="headerlink" href="#brevitas.core.function_wrapper.ops_ste.FloorSte.training" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
</dd></dl>
<dl class="py class">
<dt id="brevitas.core.function_wrapper.ops_ste.RoundSte">
<em class="property">class </em><code class="sig-prename descclassname">brevitas.core.function_wrapper.ops_ste.</code><code class="sig-name descname">RoundSte</code><a class="headerlink" href="#brevitas.core.function_wrapper.ops_ste.RoundSte" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torch.nn.modules.module.Module</span></code></p>
<p>ScriptModule wrapper for <a class="reference internal" href="brevitas.function.html#brevitas.function.ops_ste.round_ste" title="brevitas.function.ops_ste.round_ste"><code class="xref py py-func docutils literal notranslate"><span class="pre">round_ste()</span></code></a>.</p>
<dl class="py method">
<dt id="brevitas.core.function_wrapper.ops_ste.RoundSte.forward">
<code class="sig-name descname">forward</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">x</span></em><span class="sig-paren">)</span><a class="headerlink" href="#brevitas.core.function_wrapper.ops_ste.RoundSte.forward" title="Permalink to this definition">¶</a></dt>
<dd><p>Defines the computation performed at every call.</p>
<p>Should be overridden by all subclasses.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>Although the recipe for forward pass needs to be defined within
this function, one should call the <code class="xref py py-class docutils literal notranslate"><span class="pre">Module</span></code> instance afterwards
instead of this since the former takes care of running the
registered hooks while the latter silently ignores them.</p>
</div>
</dd></dl>
<dl class="py attribute">
<dt id="brevitas.core.function_wrapper.ops_ste.RoundSte.training">
<code class="sig-name descname">training</code><em class="property">: bool</em><a class="headerlink" href="#brevitas.core.function_wrapper.ops_ste.RoundSte.training" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
</dd></dl>
<dl class="py class">
<dt id="brevitas.core.function_wrapper.ops_ste.RoundToZeroSte">
<em class="property">class </em><code class="sig-prename descclassname">brevitas.core.function_wrapper.ops_ste.</code><code class="sig-name descname">RoundToZeroSte</code><a class="headerlink" href="#brevitas.core.function_wrapper.ops_ste.RoundToZeroSte" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torch.nn.modules.module.Module</span></code></p>
<p>ScriptModule wrapper for <a class="reference internal" href="brevitas.function.html#brevitas.function.ops_ste.round_to_zero_ste" title="brevitas.function.ops_ste.round_to_zero_ste"><code class="xref py py-func docutils literal notranslate"><span class="pre">round_to_zero_ste()</span></code></a>.</p>
<dl class="py method">
<dt id="brevitas.core.function_wrapper.ops_ste.RoundToZeroSte.forward">
<code class="sig-name descname">forward</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">x</span></em><span class="sig-paren">)</span><a class="headerlink" href="#brevitas.core.function_wrapper.ops_ste.RoundToZeroSte.forward" title="Permalink to this definition">¶</a></dt>
<dd><p>Defines the computation performed at every call.</p>
<p>Should be overridden by all subclasses.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>Although the recipe for forward pass needs to be defined within
this function, one should call the <code class="xref py py-class docutils literal notranslate"><span class="pre">Module</span></code> instance afterwards
instead of this since the former takes care of running the
registered hooks while the latter silently ignores them.</p>
</div>
</dd></dl>
<dl class="py attribute">
<dt id="brevitas.core.function_wrapper.ops_ste.RoundToZeroSte.training">
<code class="sig-name descname">training</code><em class="property">: bool</em><a class="headerlink" href="#brevitas.core.function_wrapper.ops_ste.RoundToZeroSte.training" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
</dd></dl>
<dl class="py class">
<dt id="brevitas.core.function_wrapper.ops_ste.ScalarClampMinSte">
<em class="property">class </em><code class="sig-prename descclassname">brevitas.core.function_wrapper.ops_ste.</code><code class="sig-name descname">ScalarClampMinSte</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">min_val</span></em><span class="sig-paren">)</span><a class="headerlink" href="#brevitas.core.function_wrapper.ops_ste.ScalarClampMinSte" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torch.nn.modules.module.Module</span></code></p>
<p>ScriptModule wrapper for <a class="reference internal" href="brevitas.function.html#brevitas.function.ops_ste.scalar_clamp_min_ste" title="brevitas.function.ops_ste.scalar_clamp_min_ste"><code class="xref py py-func docutils literal notranslate"><span class="pre">scalar_clamp_min_ste()</span></code></a>.</p>
<dl class="py method">
<dt id="brevitas.core.function_wrapper.ops_ste.ScalarClampMinSte.forward">
<code class="sig-name descname">forward</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">x</span></em><span class="sig-paren">)</span><a class="headerlink" href="#brevitas.core.function_wrapper.ops_ste.ScalarClampMinSte.forward" title="Permalink to this definition">¶</a></dt>
<dd><p>Defines the computation performed at every call.</p>
<p>Should be overridden by all subclasses.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>Although the recipe for forward pass needs to be defined within
this function, one should call the <code class="xref py py-class docutils literal notranslate"><span class="pre">Module</span></code> instance afterwards
instead of this since the former takes care of running the
registered hooks while the latter silently ignores them.</p>
</div>
</dd></dl>
<dl class="py attribute">
<dt id="brevitas.core.function_wrapper.ops_ste.ScalarClampMinSte.training">
<code class="sig-name descname">training</code><em class="property">: bool</em><a class="headerlink" href="#brevitas.core.function_wrapper.ops_ste.ScalarClampMinSte.training" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
</dd></dl>
<dl class="py class">
<dt id="brevitas.core.function_wrapper.ops_ste.TensorClampSte">
<em class="property">class </em><code class="sig-prename descclassname">brevitas.core.function_wrapper.ops_ste.</code><code class="sig-name descname">TensorClampSte</code><a class="headerlink" href="#brevitas.core.function_wrapper.ops_ste.TensorClampSte" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torch.nn.modules.module.Module</span></code></p>
<p>ScriptModule wrapper for <a class="reference internal" href="brevitas.function.html#brevitas.function.ops_ste.tensor_clamp_ste" title="brevitas.function.ops_ste.tensor_clamp_ste"><code class="xref py py-func docutils literal notranslate"><span class="pre">tensor_clamp_ste()</span></code></a>.</p>
<dl class="py method">
<dt id="brevitas.core.function_wrapper.ops_ste.TensorClampSte.forward">
<code class="sig-name descname">forward</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">x</span></em>, <em class="sig-param"><span class="n">min_val</span></em>, <em class="sig-param"><span class="n">max_val</span></em><span class="sig-paren">)</span><a class="headerlink" href="#brevitas.core.function_wrapper.ops_ste.TensorClampSte.forward" title="Permalink to this definition">¶</a></dt>
<dd><p>Defines the computation performed at every call.</p>
<p>Should be overridden by all subclasses.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>Although the recipe for forward pass needs to be defined within
this function, one should call the <code class="xref py py-class docutils literal notranslate"><span class="pre">Module</span></code> instance afterwards
instead of this since the former takes care of running the
registered hooks while the latter silently ignores them.</p>
</div>
</dd></dl>
<dl class="py attribute">
<dt id="brevitas.core.function_wrapper.ops_ste.TensorClampSte.training">
<code class="sig-name descname">training</code><em class="property">: bool</em><a class="headerlink" href="#brevitas.core.function_wrapper.ops_ste.TensorClampSte.training" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
</dd></dl>
</div>
<div class="section" id="module-brevitas.core.function_wrapper.shape">
<span id="brevitas-core-function-wrapper-shape-module"></span><h2>brevitas.core.function_wrapper.shape module<a class="headerlink" href="#module-brevitas.core.function_wrapper.shape" title="Permalink to this headline">¶</a></h2>
<p>ScriptModule classes to compute the view of a tensor according to various different criteria.</p>
<dl class="py class">
<dt id="brevitas.core.function_wrapper.shape.OverBatchOverOutputChannelView">
<em class="property">class </em><code class="sig-prename descclassname">brevitas.core.function_wrapper.shape.</code><code class="sig-name descname">OverBatchOverOutputChannelView</code><a class="headerlink" href="#brevitas.core.function_wrapper.shape.OverBatchOverOutputChannelView" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torch.nn.modules.module.Module</span></code></p>
<p>ScriptModule to compute the <a class="reference internal" href="brevitas.function.html#brevitas.function.shape.over_batch_over_output_channels" title="brevitas.function.shape.over_batch_over_output_channels"><code class="xref py py-func docutils literal notranslate"><span class="pre">over_batch_over_output_channels()</span></code></a>
view of an input tensor.</p>
<p class="rubric">Examples</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">view_module</span> <span class="o">=</span> <span class="n">OverBatchOverOutputChannelView</span><span class="p">()</span>
<span class="gp">>>> </span><span class="n">y</span> <span class="o">=</span> <span class="n">view_module</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">empty</span><span class="p">(</span><span class="n">size</span><span class="o">=</span><span class="p">[</span><span class="mi">8</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">5</span><span class="p">]))</span>
<span class="gp">>>> </span><span class="n">y</span><span class="o">.</span><span class="n">shape</span>
<span class="go">torch.Size([8, 10, 25])</span>
</pre></div>
</div>
<dl class="py method">
<dt id="brevitas.core.function_wrapper.shape.OverBatchOverOutputChannelView.forward">
<code class="sig-name descname">forward</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">x</span></em><span class="sig-paren">)</span><a class="headerlink" href="#brevitas.core.function_wrapper.shape.OverBatchOverOutputChannelView.forward" title="Permalink to this definition">¶</a></dt>
<dd><p>Defines the computation performed at every call.</p>
<p>Should be overridden by all subclasses.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>Although the recipe for forward pass needs to be defined within
this function, one should call the <code class="xref py py-class docutils literal notranslate"><span class="pre">Module</span></code> instance afterwards
instead of this since the former takes care of running the
registered hooks while the latter silently ignores them.</p>
</div>
</dd></dl>
<dl class="py method">
<dt id="brevitas.core.function_wrapper.shape.OverBatchOverOutputChannelView.shape">
<code class="sig-name descname">shape</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">x</span></em><span class="sig-paren">)</span><a class="headerlink" href="#brevitas.core.function_wrapper.shape.OverBatchOverOutputChannelView.shape" title="Permalink to this definition">¶</a></dt>
<dd><p>Wrapper for <a class="reference internal" href="brevitas.function.html#brevitas.function.shape.over_batch_over_output_channels" title="brevitas.function.shape.over_batch_over_output_channels"><code class="xref py py-func docutils literal notranslate"><span class="pre">over_batch_over_output_channels()</span></code></a>.</p>
</dd></dl>
<dl class="py attribute">
<dt id="brevitas.core.function_wrapper.shape.OverBatchOverOutputChannelView.training">
<code class="sig-name descname">training</code><em class="property">: bool</em><a class="headerlink" href="#brevitas.core.function_wrapper.shape.OverBatchOverOutputChannelView.training" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
</dd></dl>
<dl class="py class">
<dt id="brevitas.core.function_wrapper.shape.OverBatchOverTensorView">
<em class="property">class </em><code class="sig-prename descclassname">brevitas.core.function_wrapper.shape.</code><code class="sig-name descname">OverBatchOverTensorView</code><a class="headerlink" href="#brevitas.core.function_wrapper.shape.OverBatchOverTensorView" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torch.nn.modules.module.Module</span></code></p>
<p>ScriptMoodule to compute the <a class="reference internal" href="brevitas.function.html#brevitas.function.shape.over_batch_over_tensor" title="brevitas.function.shape.over_batch_over_tensor"><code class="xref py py-func docutils literal notranslate"><span class="pre">over_batch_over_tensor()</span></code></a> view of an
input tensor.</p>
<p class="rubric">Examples</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">view_module</span> <span class="o">=</span> <span class="n">OverBatchOverTensorView</span><span class="p">()</span>
<span class="gp">>>> </span><span class="n">y</span> <span class="o">=</span> <span class="n">view_module</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">empty</span><span class="p">(</span><span class="n">size</span><span class="o">=</span><span class="p">[</span><span class="mi">8</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">5</span><span class="p">]))</span>
<span class="gp">>>> </span><span class="n">y</span><span class="o">.</span><span class="n">shape</span>
<span class="go">torch.Size([8, 250])</span>
</pre></div>
</div>
<dl class="py method">
<dt id="brevitas.core.function_wrapper.shape.OverBatchOverTensorView.forward">
<code class="sig-name descname">forward</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">x</span></em><span class="sig-paren">)</span><a class="headerlink" href="#brevitas.core.function_wrapper.shape.OverBatchOverTensorView.forward" title="Permalink to this definition">¶</a></dt>
<dd><p>Defines the computation performed at every call.</p>
<p>Should be overridden by all subclasses.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>Although the recipe for forward pass needs to be defined within
this function, one should call the <code class="xref py py-class docutils literal notranslate"><span class="pre">Module</span></code> instance afterwards
instead of this since the former takes care of running the
registered hooks while the latter silently ignores them.</p>
</div>
</dd></dl>
<dl class="py method">
<dt id="brevitas.core.function_wrapper.shape.OverBatchOverTensorView.shape">
<code class="sig-name descname">shape</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">x</span></em><span class="sig-paren">)</span><a class="headerlink" href="#brevitas.core.function_wrapper.shape.OverBatchOverTensorView.shape" title="Permalink to this definition">¶</a></dt>
<dd><p>Wrapper for <a class="reference internal" href="brevitas.function.html#brevitas.function.shape.over_batch_over_tensor" title="brevitas.function.shape.over_batch_over_tensor"><code class="xref py py-func docutils literal notranslate"><span class="pre">over_batch_over_tensor()</span></code></a>.</p>
</dd></dl>
<dl class="py attribute">
<dt id="brevitas.core.function_wrapper.shape.OverBatchOverTensorView.training">
<code class="sig-name descname">training</code><em class="property">: bool</em><a class="headerlink" href="#brevitas.core.function_wrapper.shape.OverBatchOverTensorView.training" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
</dd></dl>
<dl class="py class">
<dt id="brevitas.core.function_wrapper.shape.OverOutputChannelView">
<em class="property">class </em><code class="sig-prename descclassname">brevitas.core.function_wrapper.shape.</code><code class="sig-name descname">OverOutputChannelView</code><a class="headerlink" href="#brevitas.core.function_wrapper.shape.OverOutputChannelView" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torch.nn.modules.module.Module</span></code></p>
<p>ScriptMoodule to compute the <a class="reference internal" href="brevitas.function.html#brevitas.function.shape.over_output_channels" title="brevitas.function.shape.over_output_channels"><code class="xref py py-func docutils literal notranslate"><span class="pre">over_output_channels()</span></code></a> view of an
input tensor.</p>
<p class="rubric">Examples</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">view_module</span> <span class="o">=</span> <span class="n">OverOutputChannelView</span><span class="p">()</span>
<span class="gp">>>> </span><span class="n">y</span> <span class="o">=</span> <span class="n">view_module</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">empty</span><span class="p">(</span><span class="n">size</span><span class="o">=</span><span class="p">[</span><span class="mi">16</span><span class="p">,</span> <span class="mi">8</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">5</span><span class="p">]))</span>
<span class="gp">>>> </span><span class="n">y</span><span class="o">.</span><span class="n">shape</span>
<span class="go">torch.Size([16, 200])</span>
</pre></div>
</div>
<dl class="py method">
<dt id="brevitas.core.function_wrapper.shape.OverOutputChannelView.forward">
<code class="sig-name descname">forward</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">x</span></em><span class="sig-paren">)</span><a class="headerlink" href="#brevitas.core.function_wrapper.shape.OverOutputChannelView.forward" title="Permalink to this definition">¶</a></dt>
<dd><p>Defines the computation performed at every call.</p>
<p>Should be overridden by all subclasses.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>Although the recipe for forward pass needs to be defined within
this function, one should call the <code class="xref py py-class docutils literal notranslate"><span class="pre">Module</span></code> instance afterwards
instead of this since the former takes care of running the
registered hooks while the latter silently ignores them.</p>
</div>
</dd></dl>
<dl class="py method">
<dt id="brevitas.core.function_wrapper.shape.OverOutputChannelView.shape">
<code class="sig-name descname">shape</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">x</span></em><span class="sig-paren">)</span><a class="headerlink" href="#brevitas.core.function_wrapper.shape.OverOutputChannelView.shape" title="Permalink to this definition">¶</a></dt>
<dd><p>Wrapper for <a class="reference internal" href="brevitas.function.html#brevitas.function.shape.over_output_channels" title="brevitas.function.shape.over_output_channels"><code class="xref py py-func docutils literal notranslate"><span class="pre">over_output_channels()</span></code></a>.</p>
</dd></dl>
<dl class="py attribute">
<dt id="brevitas.core.function_wrapper.shape.OverOutputChannelView.training">
<code class="sig-name descname">training</code><em class="property">: bool</em><a class="headerlink" href="#brevitas.core.function_wrapper.shape.OverOutputChannelView.training" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
</dd></dl>
<dl class="py class">
<dt id="brevitas.core.function_wrapper.shape.OverTensorView">
<em class="property">class </em><code class="sig-prename descclassname">brevitas.core.function_wrapper.shape.</code><code class="sig-name descname">OverTensorView</code><a class="headerlink" href="#brevitas.core.function_wrapper.shape.OverTensorView" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torch.nn.modules.module.Module</span></code></p>
<p>ScriptMoodule to compute the <a class="reference internal" href="brevitas.function.html#brevitas.function.shape.over_tensor" title="brevitas.function.shape.over_tensor"><code class="xref py py-func docutils literal notranslate"><span class="pre">over_tensor()</span></code></a> view of an input tensor.</p>
<p class="rubric">Examples</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">view_module</span> <span class="o">=</span> <span class="n">OverTensorView</span><span class="p">()</span>
<span class="gp">>>> </span><span class="n">y</span> <span class="o">=</span> <span class="n">view_module</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">empty</span><span class="p">(</span><span class="n">size</span><span class="o">=</span><span class="p">[</span><span class="mi">16</span><span class="p">,</span> <span class="mi">6</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">5</span><span class="p">]))</span>
<span class="gp">>>> </span><span class="n">y</span><span class="o">.</span><span class="n">shape</span>
<span class="go">torch.Size([2400])</span>
</pre></div>
</div>
<dl class="py method">
<dt id="brevitas.core.function_wrapper.shape.OverTensorView.forward">
<code class="sig-name descname">forward</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">x</span></em><span class="sig-paren">)</span><a class="headerlink" href="#brevitas.core.function_wrapper.shape.OverTensorView.forward" title="Permalink to this definition">¶</a></dt>
<dd><p>Defines the computation performed at every call.</p>
<p>Should be overridden by all subclasses.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>Although the recipe for forward pass needs to be defined within
this function, one should call the <code class="xref py py-class docutils literal notranslate"><span class="pre">Module</span></code> instance afterwards
instead of this since the former takes care of running the
registered hooks while the latter silently ignores them.</p>
</div>
</dd></dl>
<dl class="py method">
<dt id="brevitas.core.function_wrapper.shape.OverTensorView.shape">
<code class="sig-name descname">shape</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">x</span></em><span class="sig-paren">)</span><a class="headerlink" href="#brevitas.core.function_wrapper.shape.OverTensorView.shape" title="Permalink to this definition">¶</a></dt>
<dd><p>Wrapper for <a class="reference internal" href="brevitas.function.html#brevitas.function.shape.over_tensor" title="brevitas.function.shape.over_tensor"><code class="xref py py-func docutils literal notranslate"><span class="pre">over_tensor()</span></code></a>.</p>
</dd></dl>
<dl class="py attribute">
<dt id="brevitas.core.function_wrapper.shape.OverTensorView.training">
<code class="sig-name descname">training</code><em class="property">: bool</em><a class="headerlink" href="#brevitas.core.function_wrapper.shape.OverTensorView.training" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
</dd></dl>
<dl class="py class">
<dt id="brevitas.core.function_wrapper.shape.StatsInputViewShapeImpl">
<em class="property">class </em><code class="sig-prename descclassname">brevitas.core.function_wrapper.shape.</code><code class="sig-name descname">StatsInputViewShapeImpl</code><a class="headerlink" href="#brevitas.core.function_wrapper.shape.StatsInputViewShapeImpl" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
<p>Enum-like object to collect pointers to variants of ScriptModules that perform a view on a tensor.
All adhere to the same interface.</p>
<dl class="py attribute">
<dt id="brevitas.core.function_wrapper.shape.StatsInputViewShapeImpl.OVER_BATCH_OVER_OUTPUT_CHANNELS">
<code class="sig-name descname">OVER_BATCH_OVER_OUTPUT_CHANNELS</code><a class="headerlink" href="#brevitas.core.function_wrapper.shape.StatsInputViewShapeImpl.OVER_BATCH_OVER_OUTPUT_CHANNELS" title="Permalink to this definition">¶</a></dt>
<dd><p>alias of <a class="reference internal" href="#brevitas.core.function_wrapper.shape.OverBatchOverOutputChannelView" title="brevitas.core.function_wrapper.shape.OverBatchOverOutputChannelView"><code class="xref py py-class docutils literal notranslate"><span class="pre">brevitas.core.function_wrapper.shape.OverBatchOverOutputChannelView</span></code></a></p>
</dd></dl>
<dl class="py attribute">
<dt id="brevitas.core.function_wrapper.shape.StatsInputViewShapeImpl.OVER_BATCH_OVER_TENSOR">
<code class="sig-name descname">OVER_BATCH_OVER_TENSOR</code><a class="headerlink" href="#brevitas.core.function_wrapper.shape.StatsInputViewShapeImpl.OVER_BATCH_OVER_TENSOR" title="Permalink to this definition">¶</a></dt>
<dd><p>alias of <a class="reference internal" href="#brevitas.core.function_wrapper.shape.OverBatchOverTensorView" title="brevitas.core.function_wrapper.shape.OverBatchOverTensorView"><code class="xref py py-class docutils literal notranslate"><span class="pre">brevitas.core.function_wrapper.shape.OverBatchOverTensorView</span></code></a></p>
</dd></dl>
<dl class="py attribute">
<dt id="brevitas.core.function_wrapper.shape.StatsInputViewShapeImpl.OVER_OUTPUT_CHANNELS">
<code class="sig-name descname">OVER_OUTPUT_CHANNELS</code><a class="headerlink" href="#brevitas.core.function_wrapper.shape.StatsInputViewShapeImpl.OVER_OUTPUT_CHANNELS" title="Permalink to this definition">¶</a></dt>
<dd><p>alias of <a class="reference internal" href="#brevitas.core.function_wrapper.shape.OverOutputChannelView" title="brevitas.core.function_wrapper.shape.OverOutputChannelView"><code class="xref py py-class docutils literal notranslate"><span class="pre">brevitas.core.function_wrapper.shape.OverOutputChannelView</span></code></a></p>
</dd></dl>
<dl class="py attribute">
<dt id="brevitas.core.function_wrapper.shape.StatsInputViewShapeImpl.OVER_TENSOR">
<code class="sig-name descname">OVER_TENSOR</code><a class="headerlink" href="#brevitas.core.function_wrapper.shape.StatsInputViewShapeImpl.OVER_TENSOR" title="Permalink to this definition">¶</a></dt>
<dd><p>alias of <a class="reference internal" href="#brevitas.core.function_wrapper.shape.OverTensorView" title="brevitas.core.function_wrapper.shape.OverTensorView"><code class="xref py py-class docutils literal notranslate"><span class="pre">brevitas.core.function_wrapper.shape.OverTensorView</span></code></a></p>
</dd></dl>
</dd></dl>
</div>
<div class="section" id="module-brevitas.core.function_wrapper">
<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-brevitas.core.function_wrapper" title="Permalink to this headline">¶</a></h2>
</div>
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