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<a href="https://github.com/labmlai/annotated_deep_learning_paper_implementations/tree/master/labml_nn/sampling/top_k.py" target="_blank">
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View code on Github</a>
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<a href='#section-0'>#</a>
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<h1>Top-k Sampling</h1>
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<p>Here we first pick the top-k tokens from the distribution of logits, and then sample from them.</p>
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<p>Here's an <a href="experiment.html">experiment</a> that uses these sampling techniques.</p>
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<div class="highlight"><pre><span class="lineno">15</span><span></span><span class="kn">import</span> <span class="nn">torch</span>
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<span class="lineno">16</span>
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<span class="lineno">17</span><span class="kn">from</span> <span class="nn">labml_nn.sampling</span> <span class="kn">import</span> <span class="n">Sampler</span></pre></div>
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<a href='#section-1'>#</a>
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<h2>Top-k Sampler</h2>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">20</span><span class="k">class</span> <span class="nc">TopKSampler</span><span class="p">(</span><span class="n">Sampler</span><span class="p">):</span></pre></div>
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<a href='#section-2'>#</a>
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<ul><li><code class="highlight"><span></span><span class="n">k</span></code>
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is the number of tokens to pick </li>
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<li><code class="highlight"><span></span><span class="n">sampler</span></code>
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is the sampler to use for the top-k tokens</li></ul>
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<p><code class="highlight"><span></span><span class="n">sampler</span></code>
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can be any sampler that takes a logits tensor as input and returns a token tensor; e.g. <a href="temperature.html">`TemperatureSampler'</a>.</p>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">24</span> <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">k</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">sampler</span><span class="p">:</span> <span class="n">Sampler</span><span class="p">):</span></pre></div>
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<a href='#section-3'>#</a>
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<div class="highlight"><pre><span class="lineno">32</span> <span class="bp">self</span><span class="o">.</span><span class="n">k</span> <span class="o">=</span> <span class="n">k</span>
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<span class="lineno">33</span> <span class="bp">self</span><span class="o">.</span><span class="n">sampler</span> <span class="o">=</span> <span class="n">sampler</span></pre></div>
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<div class='section' id='section-4'>
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<div class='docs doc-strings'>
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<a href='#section-4'>#</a>
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<p> Sample from logits</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">35</span> <span class="k">def</span> <span class="fm">__call__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">logits</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">):</span></pre></div>
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<div class='section' id='section-5'>
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<div class='docs'>
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<a href='#section-5'>#</a>
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<p>New logits filled with <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.66666em;vertical-align:-0.08333em;"></span><span class="mord coloredeq eqa" style=""><span class="mord" style="">−</span><span class="mord" style="">∞</span></span></span></span></span></span>; i.e. zero probability </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">40</span> <span class="n">zeros</span> <span class="o">=</span> <span class="n">logits</span><span class="o">.</span><span class="n">new_ones</span><span class="p">(</span><span class="n">logits</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span> <span class="o">*</span> <span class="nb">float</span><span class="p">(</span><span class="s1">'-inf'</span><span class="p">)</span></pre></div>
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<div class='section' id='section-6'>
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<div class='docs'>
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<a href='#section-6'>#</a>
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<p>Pick the largest <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.69444em;vertical-align:0em;"></span><span class="mord mathnormal" style="margin-right:0.03148em;">k</span></span></span></span></span> logits and their indices </p>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">42</span> <span class="n">values</span><span class="p">,</span> <span class="n">indices</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">topk</span><span class="p">(</span><span class="n">logits</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">k</span><span class="p">,</span> <span class="n">dim</span><span class="o">=-</span><span class="mi">1</span><span class="p">)</span></pre></div>
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<a href='#section-7'>#</a>
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<p>Set the values of the top-k selected indices to actual logits. Logits of other tokens remain <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.66666em;vertical-align:-0.08333em;"></span><span class="mord coloredeq eqa" style=""><span class="mord" style="">−</span><span class="mord" style="">∞</span></span></span></span></span></span> </p>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">45</span> <span class="n">zeros</span><span class="o">.</span><span class="n">scatter_</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="n">indices</span><span class="p">,</span> <span class="n">values</span><span class="p">)</span></pre></div>
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<div class='section' id='section-8'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-8'>#</a>
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<p>Sample from the top-k logits with the specified sampler. </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">48</span> <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">sampler</span><span class="p">(</span><span class="n">zeros</span><span class="p">)</span></pre></div>
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