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<h1>Generator<a class="headerlink" href="#generator" title="Permalink to this headline">¶</a></h1>
<p>PyTorch provides methods to create random number generation (RNG) as part of your PyTorch program. <cite>torch.generator</cite> is the primary API to use for standard <em>in the clear</em> application where there is no application of privacy preserving techniques such as differential privacy. To create a cryptographically secure RNG, please use torchcsprng which can be found in the repo <a class="reference external" href="https://github.com/pytorch/csprng">here</a>.</p>
<dl class="class">
<dt id="torch.Generator">
<em class="property">class </em><code class="sig-prename descclassname">torch.</code><code class="sig-name descname">Generator</code><span class="sig-paren">(</span><em class="sig-param">device='cpu'</em><span class="sig-paren">)</span> → Generator<a class="headerlink" href="#torch.Generator" title="Permalink to this definition">¶</a></dt>
<dd><p>Creates and returns a generator object which manages the state of the algorithm that
produces pseudo random numbers. Used as a keyword argument in many <a class="reference internal" href="../torch.html#inplace-random-sampling"><span class="std std-ref">In-place random sampling</span></a>
functions.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>device</strong> (<a class="reference internal" href="../tensor_attributes.html#torch.torch.device" title="torch.torch.device"><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.device</span></code></a>, optional) – the desired device for the generator.</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>An torch.Generator object.</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p><a class="reference internal" href="#torch.Generator" title="torch.Generator">Generator</a></p>
</dd>
</dl>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">g_cpu</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">Generator</span><span class="p">()</span>
<span class="gp">>>> </span><span class="n">g_cuda</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">Generator</span><span class="p">(</span><span class="n">device</span><span class="o">=</span><span class="s1">'cuda'</span><span class="p">)</span>
</pre></div>
</div>
<dl class="attribute">
<dt id="torch.Generator.device">
<code class="sig-name descname">device</code><a class="headerlink" href="#torch.Generator.device" title="Permalink to this definition">¶</a></dt>
<dd><p>Generator.device -> device</p>
<p>Gets the current device of the generator.</p>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">g_cpu</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">Generator</span><span class="p">()</span>
<span class="gp">>>> </span><span class="n">g_cpu</span><span class="o">.</span><span class="n">device</span>
<span class="go">device(type='cpu')</span>
</pre></div>
</div>
</dd></dl>
<dl class="method">
<dt id="torch.Generator.get_state">
<code class="sig-name descname">get_state</code><span class="sig-paren">(</span><span class="sig-paren">)</span> → Tensor<a class="headerlink" href="#torch.Generator.get_state" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns the Generator state as a <code class="docutils literal notranslate"><span class="pre">torch.ByteTensor</span></code>.</p>
<dl class="field-list simple">
<dt class="field-odd">Returns</dt>
<dd class="field-odd"><p>A <code class="docutils literal notranslate"><span class="pre">torch.ByteTensor</span></code> which contains all the necessary bits
to restore a Generator to a specific point in time.</p>
</dd>
<dt class="field-even">Return type</dt>
<dd class="field-even"><p><a class="reference internal" href="../tensors.html#torch.Tensor" title="torch.Tensor">Tensor</a></p>
</dd>
</dl>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">g_cpu</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">Generator</span><span class="p">()</span>
<span class="gp">>>> </span><span class="n">g_cpu</span><span class="o">.</span><span class="n">get_state</span><span class="p">()</span>
</pre></div>
</div>
</dd></dl>
<dl class="method">
<dt id="torch.Generator.initial_seed">
<code class="sig-name descname">initial_seed</code><span class="sig-paren">(</span><span class="sig-paren">)</span> → int<a class="headerlink" href="#torch.Generator.initial_seed" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns the initial seed for generating random numbers.</p>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">g_cpu</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">Generator</span><span class="p">()</span>
<span class="gp">>>> </span><span class="n">g_cpu</span><span class="o">.</span><span class="n">initial_seed</span><span class="p">()</span>
<span class="go">2147483647</span>
</pre></div>
</div>
</dd></dl>
<dl class="method">
<dt id="torch.Generator.manual_seed">
<code class="sig-name descname">manual_seed</code><span class="sig-paren">(</span><em class="sig-param">seed</em><span class="sig-paren">)</span> → Generator<a class="headerlink" href="#torch.Generator.manual_seed" title="Permalink to this definition">¶</a></dt>
<dd><p>Sets the seed for generating random numbers. Returns a <cite>torch.Generator</cite> object.
It is recommended to set a large seed, i.e. a number that has a good balance of 0
and 1 bits. Avoid having many 0 bits in the seed.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>seed</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.8)"><em>int</em></a>) – The desired seed.</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>An torch.Generator object.</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p><a class="reference internal" href="#torch.Generator" title="torch.Generator">Generator</a></p>
</dd>
</dl>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">g_cpu</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">Generator</span><span class="p">()</span>
<span class="gp">>>> </span><span class="n">g_cpu</span><span class="o">.</span><span class="n">manual_seed</span><span class="p">(</span><span class="mi">2147483647</span><span class="p">)</span>
</pre></div>
</div>
</dd></dl>
<dl class="method">
<dt id="torch.Generator.seed">
<code class="sig-name descname">seed</code><span class="sig-paren">(</span><span class="sig-paren">)</span> → int<a class="headerlink" href="#torch.Generator.seed" title="Permalink to this definition">¶</a></dt>
<dd><p>Gets a non-deterministic random number from std::random_device or the current
time and uses it to seed a Generator.</p>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">g_cpu</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">Generator</span><span class="p">()</span>
<span class="gp">>>> </span><span class="n">g_cpu</span><span class="o">.</span><span class="n">seed</span><span class="p">()</span>
<span class="go">1516516984916</span>
</pre></div>
</div>
</dd></dl>
<dl class="method">
<dt id="torch.Generator.set_state">
<code class="sig-name descname">set_state</code><span class="sig-paren">(</span><em class="sig-param">new_state</em><span class="sig-paren">)</span> → void<a class="headerlink" href="#torch.Generator.set_state" title="Permalink to this definition">¶</a></dt>
<dd><p>Sets the Generator state.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>new_state</strong> (<em>torch.ByteTensor</em>) – The desired state.</p>
</dd>
</dl>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">g_cpu</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">Generator</span><span class="p">()</span>
<span class="gp">>>> </span><span class="n">g_cpu_other</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">Generator</span><span class="p">()</span>
<span class="gp">>>> </span><span class="n">g_cpu</span><span class="o">.</span><span class="n">set_state</span><span class="p">(</span><span class="n">g_cpu_other</span><span class="o">.</span><span class="n">get_state</span><span class="p">())</span>
</pre></div>
</div>
</dd></dl>
</dd></dl>
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