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<span class="kn">import</span> <span class="nn">torch.onnx</span>
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<span class="sd">&quot;&quot;&quot;Broadcasts a sequence tensors to the specified GPUs.</span>
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<span class="s1">&#39;hann_window&#39;</span><span class="p">,</span> <span class="s1">&#39;hamming_window&#39;</span><span class="p">,</span> <span class="s1">&#39;bartlett_window&#39;</span><span class="p">,</span> <span class="s1">&#39;where&#39;</span><span class="p">,</span>
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<span class="p">]</span>
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@@ -697,6 +697,26 @@ <h1>Source code for torch.functional</h1><div class="highlight"><pre>
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<span class="k">return</span> <span class="n">split</span><span class="p">(</span><span class="n">tensor</span><span class="p">,</span> <span class="n">split_size</span><span class="p">,</span> <span class="n">dim</span><span class="p">)</span></div>
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<span class="k">def</span> <span class="nf">empty_like</span><span class="p">(</span><span class="nb">input</span><span class="p">):</span>
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<span class="sa">r</span><span class="sd">&quot;&quot;&quot;empty_like(input) -&gt; Tensor</span>
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<span class="sd"> Returns an uninitialized tensor with the same size as :attr:`input`.</span>
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<span class="sd"> Args:</span>
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<span class="sd"> input (Tensor): the size of :attr:`input` will determine size of the output tensor</span>
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<span class="sd"> Example::</span>
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<span class="sd"> &gt;&gt;&gt; input = torch.LongTensor(2,3)</span>
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<span class="sd"> &gt;&gt;&gt; input.new(input.size())</span>
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<span class="sd"> 1.3996e+14 1.3996e+14 1.3996e+14</span>
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<span class="sd"> 4.0000e+00 0.0000e+00 0.0000e+00</span>
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<span class="sd"> [torch.LongTensor of size 2x3]</span>
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<span class="sd"> &quot;&quot;&quot;</span>
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<span class="k">return</span> <span class="nb">input</span><span class="o">.</span><span class="n">new</span><span class="p">(</span><span class="nb">input</span><span class="o">.</span><span class="n">size</span><span class="p">())</span>
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<div class="viewcode-block" id="stack"><a class="viewcode-back" href="../../torch.html#torch.stack">[docs]</a><span class="k">def</span> <span class="nf">stack</span><span class="p">(</span><span class="n">sequence</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
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<span class="sa">r</span><span class="sd">&quot;&quot;&quot;Concatenates sequence of tensors along a new dimension.</span>
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