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  <section id="log2">
<h1>log2<a class="headerlink" href="#log2" title="Permalink to this headline"></a></h1>
<section id="documentation">
<h2>Documentation<a class="headerlink" href="#documentation" title="Permalink to this headline"></a></h2>
<dl class="py function">
<dt id="treetensor.torch.log2">
<code class="sig-prename descclassname">treetensor.torch.</code><code class="sig-name descname">log2</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">input</span></em>, <em class="sig-param"><span class="o">*</span><span class="n">args</span></em>, <em class="sig-param"><span class="o">**</span><span class="n">kwargs</span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/treetensor/torch/funcs/math.html#log2"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#treetensor.torch.log2" title="Permalink to this definition"></a></dt>
<dd><p>Returns a new tensor with the logarithm to the base 2 of the elements of <code class="docutils literal notranslate"><span class="pre">input</span></code>.</p>
<p>Examples:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">import</span> <span class="nn">torch</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">import</span> <span class="nn">treetensor.torch</span> <span class="k">as</span> <span class="nn">ttorch</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">ttorch</span><span class="o">.</span><span class="n">log2</span><span class="p">(</span><span class="n">ttorch</span><span class="o">.</span><span class="n">tensor</span><span class="p">([</span><span class="o">-</span><span class="mf">4.0</span><span class="p">,</span> <span class="o">-</span><span class="mf">1.0</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mf">2.0</span><span class="p">,</span> <span class="mf">4.8</span><span class="p">,</span> <span class="mf">8.0</span><span class="p">]))</span>
<span class="go">tensor([   nan,    nan,   -inf, 1.0000, 2.2630, 3.0000])</span>

<span class="gp">&gt;&gt;&gt; </span><span class="n">ttorch</span><span class="o">.</span><span class="n">log2</span><span class="p">(</span><span class="n">ttorch</span><span class="o">.</span><span class="n">tensor</span><span class="p">({</span>
<span class="gp">... </span>    <span class="s1">&#39;a&#39;</span><span class="p">:</span> <span class="p">[</span><span class="o">-</span><span class="mf">4.0</span><span class="p">,</span> <span class="o">-</span><span class="mf">1.0</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mf">2.0</span><span class="p">,</span> <span class="mf">4.8</span><span class="p">,</span> <span class="mf">8.0</span><span class="p">],</span>
<span class="gp">... </span>    <span class="s1">&#39;b&#39;</span><span class="p">:</span> <span class="p">{</span><span class="s1">&#39;x&#39;</span><span class="p">:</span> <span class="p">[[</span><span class="o">-</span><span class="mf">2.0</span><span class="p">,</span> <span class="mf">1.2</span><span class="p">,</span> <span class="mf">0.25</span><span class="p">],</span>
<span class="gp">... </span>                <span class="p">[</span><span class="mf">16.0</span><span class="p">,</span> <span class="mf">3.75</span><span class="p">,</span> <span class="o">-</span><span class="mf">2.34</span><span class="p">]]},</span>
<span class="gp">... </span><span class="p">}))</span>
<span class="go">&lt;Tensor 0x7ff90a4cff70&gt;</span>
<span class="go">├── a --&gt; tensor([   nan,    nan,   -inf, 1.0000, 2.2630, 3.0000])</span>
<span class="go">└── b --&gt; &lt;Tensor 0x7ff90a4bc070&gt;</span>
<span class="go">    └── x --&gt; tensor([[    nan,  0.2630, -2.0000],</span>
<span class="go">                      [ 4.0000,  1.9069,     nan]])</span>
</pre></div>
</div>
</dd></dl>

<div class="tip admonition">
<p class="admonition-title">Torch Version Related</p>
<p>This documentation is based on
<a class="reference external" href="https://pytorch.org/docs/1.12.1+cu102/generated/torch.log2.html">torch.log2</a>
in <a class="reference external" href="https://pytorch.org/docs/1.12.1+cu102/">torch v1.12.1+cu102</a>.
<strong>Its arguments’ arrangements depend on the version of pytorch you installed</strong>.</p>
<p>If some arguments listed here are not working properly, please check your pytorch’s version
with the following command and find its documentation.</p>
<div class="highlight-shell notranslate"><div class="highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span class="normal">1</span></pre></div></td><td class="code"><div><pre><span></span>python -c <span class="s1">&#39;import torch;print(torch.__version__)&#39;</span>
</pre></div></td></tr></table></div>
</div>
<p>The arguments and keyword arguments supported in torch v1.12.1+cu102 is listed below.</p>
</div>
</section>
<section id="description-from-torch-v1-12-1-cu102">
<h2>Description From Torch v1.12.1+cu102<a class="headerlink" href="#description-from-torch-v1-12-1-cu102" title="Permalink to this headline"></a></h2>
<dl class="py function">
<dt id="torch.log2">
<code class="sig-prename descclassname">torch.</code><code class="sig-name descname">log2</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">input</span></em>, <em class="sig-param"><span class="o">*</span></em>, <em class="sig-param"><span class="n">out</span><span class="o">=</span><span class="default_value">None</span></em><span class="sig-paren">)</span> &#x2192; <a class="reference internal" href="trees.Tensor.where.auto.html#torch.Tensor" title="torch.Tensor">Tensor</a><a class="headerlink" href="#torch.log2" title="Permalink to this definition"></a></dt>
<dd><p>Returns a new tensor with the logarithm to the base 2 of the elements
of <code class="xref py py-attr docutils literal notranslate"><span class="pre">input</span></code>.</p>
<div class="math notranslate nohighlight">
\[y_{i} = \log_{2} (x_{i})\]</div>
<dl class="simple">
<dt>Args:</dt><dd><p>input (Tensor): the input tensor.</p>
</dd>
<dt>Keyword args:</dt><dd><p>out (Tensor, optional): the output tensor.</p>
</dd>
</dl>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">a</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">rand</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">a</span>
<span class="go">tensor([ 0.8419,  0.8003,  0.9971,  0.5287,  0.0490])</span>


<span class="gp">&gt;&gt;&gt; </span><span class="n">torch</span><span class="o">.</span><span class="n">log2</span><span class="p">(</span><span class="n">a</span><span class="p">)</span>
<span class="go">tensor([-0.2483, -0.3213, -0.0042, -0.9196, -4.3504])</span>
</pre></div>
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