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<!DOCTYPE html>
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<title>smaug.math — SMAUG: Simulating Machine Learning Applications Using gem5-Aladdin</title>
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<div class="section" id="smaug-math">
<h1>smaug.math<a class="headerlink" href="#smaug-math" title="Permalink to this headline">¶</a></h1>
<dl class="py function">
<dt id="smaug.math.add">
<code class="sig-prename descclassname">smaug.math.</code><code class="sig-name descname">add</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">tensor_a</span></em>, <em class="sig-param"><span class="n">tensor_b</span></em>, <em class="sig-param"><span class="n">name</span><span class="o">=</span><span class="default_value">'add'</span></em><span class="sig-paren">)</span><a class="headerlink" href="#smaug.math.add" title="Permalink to this definition">¶</a></dt>
<dd><p>Elementwise addition.</p>
<p>If the inputs have different shapes, broadcasting is used to to make the
shapes compatible.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>tensor_a</strong> – First input tensor.</p></li>
<li><p><strong>tensor_b</strong> – Second input tensor.</p></li>
<li><p><strong>name</strong> – Name of the operator.</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>A tensor with the same shape as the inputs (or broadcast inputs).</p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt id="smaug.math.mul">
<code class="sig-prename descclassname">smaug.math.</code><code class="sig-name descname">mul</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">tensor_a</span></em>, <em class="sig-param"><span class="n">tensor_b</span></em>, <em class="sig-param"><span class="n">name</span><span class="o">=</span><span class="default_value">'mul'</span></em><span class="sig-paren">)</span><a class="headerlink" href="#smaug.math.mul" title="Permalink to this definition">¶</a></dt>
<dd><p>Elementwise multiplication.</p>
<p>If the inputs have different shapes, broadcasting is used to to make the
shapes compatible.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>tensor_a</strong> – First input tensor.</p></li>
<li><p><strong>tensor_b</strong> – Second input tensor.</p></li>
<li><p><strong>name</strong> – Name of the operator.</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>A tensor with the same shape as the inputs (or broadcast inputs).</p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt id="smaug.math.less">
<code class="sig-prename descclassname">smaug.math.</code><code class="sig-name descname">less</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">tensor_a</span></em>, <em class="sig-param"><span class="n">tensor_b</span></em>, <em class="sig-param"><span class="n">name</span><span class="o">=</span><span class="default_value">'less'</span></em><span class="sig-paren">)</span><a class="headerlink" href="#smaug.math.less" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns the truth value of (tensor_a < tensor_b) element-wise.</p>
<p>If the inputs have different shapes, broadcasting is used to to make the
shapes compatible.</p>
</dd></dl>
<dl class="py function">
<dt id="smaug.math.less_equal">
<code class="sig-prename descclassname">smaug.math.</code><code class="sig-name descname">less_equal</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">tensor_a</span></em>, <em class="sig-param"><span class="n">tensor_b</span></em>, <em class="sig-param"><span class="n">name</span><span class="o">=</span><span class="default_value">'less_equal'</span></em><span class="sig-paren">)</span><a class="headerlink" href="#smaug.math.less_equal" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns the truth value of (tensor_a <= tensor_b) element-wise.</p>
<p>If the inputs have different shapes, broadcasting is used to to make the
shapes compatible.</p>
</dd></dl>
<dl class="py function">
<dt id="smaug.math.greater">
<code class="sig-prename descclassname">smaug.math.</code><code class="sig-name descname">greater</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">tensor_a</span></em>, <em class="sig-param"><span class="n">tensor_b</span></em>, <em class="sig-param"><span class="n">name</span><span class="o">=</span><span class="default_value">'great'</span></em><span class="sig-paren">)</span><a class="headerlink" href="#smaug.math.greater" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns the truth value of (tensor_a > tensor_b) element-wise.</p>
<p>If the inputs have different shapes, broadcasting is used to to make the
shapes compatible.</p>
</dd></dl>
<dl class="py function">
<dt id="smaug.math.greater_equal">
<code class="sig-prename descclassname">smaug.math.</code><code class="sig-name descname">greater_equal</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">tensor_a</span></em>, <em class="sig-param"><span class="n">tensor_b</span></em>, <em class="sig-param"><span class="n">name</span><span class="o">=</span><span class="default_value">'great_equal'</span></em><span class="sig-paren">)</span><a class="headerlink" href="#smaug.math.greater_equal" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns the truth value of (tensor_a >= tensor_b) element-wise.</p>
<p>If the inputs have different shapes, broadcasting is used to to make the
shapes compatible.</p>
</dd></dl>
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