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<div class="section" id="torch-cdist">
<h1>torch.cdist<a class="headerlink" href="#torch-cdist" title="Permalink to this headline">¶</a></h1>
<dl class="function">
<dt id="torch.cdist">
<code class="sig-prename descclassname">torch.</code><code class="sig-name descname">cdist</code><span class="sig-paren">(</span><em class="sig-param">x1</em>, <em class="sig-param">x2</em>, <em class="sig-param">p=2.0</em>, <em class="sig-param">compute_mode='use_mm_for_euclid_dist_if_necessary'</em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/torch/functional.html#cdist"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#torch.cdist" title="Permalink to this definition">¶</a></dt>
<dd><p>Computes batched the p-norm distance between each pair of the two collections of row vectors.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>x1</strong> (<a class="reference internal" href="../tensors.html#torch.Tensor" title="torch.Tensor"><em>Tensor</em></a>) – input tensor of shape <span class="math"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>B</mi><mo>×</mo><mi>P</mi><mo>×</mo><mi>M</mi></mrow><annotation encoding="application/x-tex">B \times P \times M</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.76666em;vertical-align:-0.08333em;"></span><span class="mord mathnormal" style="margin-right:0.05017em;">B</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span><span class="mbin">×</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span></span><span class="base"><span class="strut" style="height:0.76666em;vertical-align:-0.08333em;"></span><span class="mord mathnormal" style="margin-right:0.13889em;">P</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span><span class="mbin">×</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span></span><span class="base"><span class="strut" style="height:0.68333em;vertical-align:0em;"></span><span class="mord mathnormal" style="margin-right:0.10903em;">M</span></span></span></span>
</span>.</p></li>
<li><p><strong>x2</strong> (<a class="reference internal" href="../tensors.html#torch.Tensor" title="torch.Tensor"><em>Tensor</em></a>) – input tensor of shape <span class="math"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>B</mi><mo>×</mo><mi>R</mi><mo>×</mo><mi>M</mi></mrow><annotation encoding="application/x-tex">B \times R \times M</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.76666em;vertical-align:-0.08333em;"></span><span class="mord mathnormal" style="margin-right:0.05017em;">B</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span><span class="mbin">×</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span></span><span class="base"><span class="strut" style="height:0.76666em;vertical-align:-0.08333em;"></span><span class="mord mathnormal" style="margin-right:0.00773em;">R</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span><span class="mbin">×</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span></span><span class="base"><span class="strut" style="height:0.68333em;vertical-align:0em;"></span><span class="mord mathnormal" style="margin-right:0.10903em;">M</span></span></span></span>
</span>.</p></li>
<li><p><strong>p</strong> – p value for the p-norm distance to calculate between each vector pair
<span class="math"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo>∈</mo><mo stretchy="false">[</mo><mn>0</mn><mo separator="true">,</mo><mi mathvariant="normal">∞</mi><mo stretchy="false">]</mo></mrow><annotation encoding="application/x-tex">\in [0, \infty]</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.5782em;vertical-align:-0.0391em;"></span><span class="mrel">∈</span><span class="mspace" style="margin-right:0.2777777777777778em;"></span></span><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mopen">[</span><span class="mord">0</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.16666666666666666em;"></span><span class="mord">∞</span><span class="mclose">]</span></span></span></span>
</span>.</p></li>
<li><p><strong>compute_mode</strong> – ‘use_mm_for_euclid_dist_if_necessary’ - will use matrix multiplication approach to calculate
euclidean distance (p = 2) if P > 25 or R > 25
‘use_mm_for_euclid_dist’ - will always use matrix multiplication approach to calculate
euclidean distance (p = 2)
‘donot_use_mm_for_euclid_dist’ - will never use matrix multiplication approach to calculate
euclidean distance (p = 2)
Default: use_mm_for_euclid_dist_if_necessary.</p></li>
</ul>
</dd>
</dl>
<p>If x1 has shape <span class="math"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>B</mi><mo>×</mo><mi>P</mi><mo>×</mo><mi>M</mi></mrow><annotation encoding="application/x-tex">B \times P \times M</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.76666em;vertical-align:-0.08333em;"></span><span class="mord mathnormal" style="margin-right:0.05017em;">B</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span><span class="mbin">×</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span></span><span class="base"><span class="strut" style="height:0.76666em;vertical-align:-0.08333em;"></span><span class="mord mathnormal" style="margin-right:0.13889em;">P</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span><span class="mbin">×</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span></span><span class="base"><span class="strut" style="height:0.68333em;vertical-align:0em;"></span><span class="mord mathnormal" style="margin-right:0.10903em;">M</span></span></span></span>
</span> and x2 has shape <span class="math"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>B</mi><mo>×</mo><mi>R</mi><mo>×</mo><mi>M</mi></mrow><annotation encoding="application/x-tex">B \times R \times M</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.76666em;vertical-align:-0.08333em;"></span><span class="mord mathnormal" style="margin-right:0.05017em;">B</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span><span class="mbin">×</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span></span><span class="base"><span class="strut" style="height:0.76666em;vertical-align:-0.08333em;"></span><span class="mord mathnormal" style="margin-right:0.00773em;">R</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span><span class="mbin">×</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span></span><span class="base"><span class="strut" style="height:0.68333em;vertical-align:0em;"></span><span class="mord mathnormal" style="margin-right:0.10903em;">M</span></span></span></span>
</span> then the
output will have shape <span class="math"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>B</mi><mo>×</mo><mi>P</mi><mo>×</mo><mi>R</mi></mrow><annotation encoding="application/x-tex">B \times P \times R</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.76666em;vertical-align:-0.08333em;"></span><span class="mord mathnormal" style="margin-right:0.05017em;">B</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span><span class="mbin">×</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span></span><span class="base"><span class="strut" style="height:0.76666em;vertical-align:-0.08333em;"></span><span class="mord mathnormal" style="margin-right:0.13889em;">P</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span><span class="mbin">×</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span></span><span class="base"><span class="strut" style="height:0.68333em;vertical-align:0em;"></span><span class="mord mathnormal" style="margin-right:0.00773em;">R</span></span></span></span>
</span>.</p>
<p>This function is equivalent to <cite>scipy.spatial.distance.cdist(input,’minkowski’, p=p)</cite>
if <span class="math"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>p</mi><mo>∈</mo><mo stretchy="false">(</mo><mn>0</mn><mo separator="true">,</mo><mi mathvariant="normal">∞</mi><mo stretchy="false">)</mo></mrow><annotation encoding="application/x-tex">p \in (0, \infty)</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.7335400000000001em;vertical-align:-0.19444em;"></span><span class="mord mathnormal">p</span><span class="mspace" style="margin-right:0.2777777777777778em;"></span><span class="mrel">∈</span><span class="mspace" style="margin-right:0.2777777777777778em;"></span></span><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mopen">(</span><span class="mord">0</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.16666666666666666em;"></span><span class="mord">∞</span><span class="mclose">)</span></span></span></span>
</span>. When <span class="math"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>p</mi><mo>=</mo><mn>0</mn></mrow><annotation encoding="application/x-tex">p = 0</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.19444em;"></span><span class="mord mathnormal">p</span><span class="mspace" style="margin-right:0.2777777777777778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2777777777777778em;"></span></span><span class="base"><span class="strut" style="height:0.64444em;vertical-align:0em;"></span><span class="mord">0</span></span></span></span>
</span> it is equivalent to
<cite>scipy.spatial.distance.cdist(input, ‘hamming’) * M</cite>. When <span class="math"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>p</mi><mo>=</mo><mi mathvariant="normal">∞</mi></mrow><annotation encoding="application/x-tex">p = \infty</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.19444em;"></span><span class="mord mathnormal">p</span><span class="mspace" style="margin-right:0.2777777777777778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2777777777777778em;"></span></span><span class="base"><span class="strut" style="height:0.43056em;vertical-align:0em;"></span><span class="mord">∞</span></span></span></span>
</span>, the closest
scipy function is <cite>scipy.spatial.distance.cdist(xn, lambda x, y: np.abs(x - y).max())</cite>.</p>
<p class="rubric">Example</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">a</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">0.9041</span><span class="p">,</span> <span class="mf">0.0196</span><span class="p">],</span> <span class="p">[</span><span class="o">-</span><span class="mf">0.3108</span><span class="p">,</span> <span class="o">-</span><span class="mf">2.4423</span><span class="p">],</span> <span class="p">[</span><span class="o">-</span><span class="mf">0.4821</span><span class="p">,</span> <span class="mf">1.059</span><span class="p">]])</span>
<span class="gp">>>> </span><span class="n">a</span>
<span class="go">tensor([[ 0.9041, 0.0196],</span>
<span class="go"> [-0.3108, -2.4423],</span>
<span class="go"> [-0.4821, 1.0590]])</span>
<span class="gp">>>> </span><span class="n">b</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">2.1763</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.4713</span><span class="p">],</span> <span class="p">[</span><span class="o">-</span><span class="mf">0.6986</span><span class="p">,</span> <span class="mf">1.3702</span><span class="p">]])</span>
<span class="gp">>>> </span><span class="n">b</span>
<span class="go">tensor([[-2.1763, -0.4713],</span>
<span class="go"> [-0.6986, 1.3702]])</span>
<span class="gp">>>> </span><span class="n">torch</span><span class="o">.</span><span class="n">cdist</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">,</span> <span class="n">p</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span>
<span class="go">tensor([[3.1193, 2.0959],</span>
<span class="go"> [2.7138, 3.8322],</span>
<span class="go"> [2.2830, 0.3791]])</span>
</pre></div>
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