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<h1>Utilities</h1>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">10</span><span></span><span class="kn">import</span> <span class="nn">copy</span>
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<span class="lineno">11</span>
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<span class="lineno">12</span><span class="kn">from</span> <span class="nn">torch.utils.data</span> <span class="kn">import</span> <span class="n">Dataset</span><span class="p">,</span> <span class="n">IterableDataset</span>
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<span class="lineno">13</span>
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<span class="lineno">14</span><span class="kn">from</span> <span class="nn">labml_helpers.module</span> <span class="kn">import</span> <span class="n">M</span><span class="p">,</span> <span class="n">TypedModuleList</span></pre></div>
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<a href='#section-1'>#</a>
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<h2>Clone Module</h2>
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<p>Make a <code>nn.ModuleList</code> with clones of a given module</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">17</span><span class="k">def</span> <span class="nf">clone_module_list</span><span class="p">(</span><span class="n">module</span><span class="p">:</span> <span class="n">M</span><span class="p">,</span> <span class="n">n</span><span class="p">:</span> <span class="nb">int</span><span class="p">)</span> <span class="o">-></span> <span class="n">TypedModuleList</span><span class="p">[</span><span class="n">M</span><span class="p">]:</span></pre></div>
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<div class="highlight"><pre><span class="lineno">23</span> <span class="k">return</span> <span class="n">TypedModuleList</span><span class="p">([</span><span class="n">copy</span><span class="o">.</span><span class="n">deepcopy</span><span class="p">(</span><span class="n">module</span><span class="p">)</span> <span class="k">for</span> <span class="n">_</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">n</span><span class="p">)])</span></pre></div>
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<div class='section-link'>
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<a href='#section-3'>#</a>
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</div>
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<p><a id="cycle_dataloader"></a></p>
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<h2>Cycle Data Loader</h2>
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<p>Infinite loader that recycles the data loader after each epoch</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">26</span><span class="k">def</span> <span class="nf">cycle_dataloader</span><span class="p">(</span><span class="n">data_loader</span><span class="p">):</span></pre></div>
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<a href='#section-4'>#</a>
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<div class="highlight"><pre><span class="lineno">33</span> <span class="k">while</span> <span class="kc">True</span><span class="p">:</span>
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<span class="lineno">34</span> <span class="k">for</span> <span class="n">batch</span> <span class="ow">in</span> <span class="n">data_loader</span><span class="p">:</span>
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<span class="lineno">35</span> <span class="k">yield</span> <span class="n">batch</span></pre></div>
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<a href='#section-5'>#</a>
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<p><a id="map_style_dataset"></a></p>
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<h2>Map Style Dataset</h2>
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<p>This converts an <a href="https://pytorch.org/docs/stable/data.html#torch.utils.data.IterableDataset"><code>IterableDataset</code></a>
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to a <a href="https://pytorch.org/docs/stable/data.html#map-style-datasets">map-style dataset</a>
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so that we can shuffle the dataset.</p>
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<p><em>This only works when the dataset size is small and can be held in memory.</em></p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">38</span><span class="k">class</span> <span class="nc">MapStyleDataset</span><span class="p">(</span><span class="n">Dataset</span><span class="p">):</span></pre></div>
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<div class="highlight"><pre><span class="lineno">50</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">dataset</span><span class="p">:</span> <span class="n">IterableDataset</span><span class="p">):</span></pre></div>
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<div class='section' id='section-7'>
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<p>Load the data to memory</p>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">52</span> <span class="bp">self</span><span class="o">.</span><span class="n">data</span> <span class="o">=</span> <span class="p">[</span><span class="n">d</span> <span class="k">for</span> <span class="n">d</span> <span class="ow">in</span> <span class="n">dataset</span><span class="p">]</span></pre></div>
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<div class='section' id='section-8'>
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<div class='section-link'>
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<a href='#section-8'>#</a>
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<p>Get a sample by index</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">54</span> <span class="k">def</span> <span class="fm">__getitem__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">idx</span><span class="p">:</span> <span class="nb">int</span><span class="p">):</span></pre></div>
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<div class='docs'>
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<a href='#section-9'>#</a>
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<div class="highlight"><pre><span class="lineno">56</span> <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span></pre></div>
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<div class='section' id='section-10'>
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<div class='docs doc-strings'>
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<div class='section-link'>
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<a href='#section-10'>#</a>
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<p>Create an iterator</p>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">58</span> <span class="k">def</span> <span class="fm">__iter__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span></pre></div>
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<div class="highlight"><pre><span class="lineno">60</span> <span class="k">return</span> <span class="nb">iter</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="p">)</span></pre></div>
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<div class='section-link'>
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<p>Size of the dataset</p>
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<div class="highlight"><pre><span class="lineno">62</span> <span class="k">def</span> <span class="fm">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span></pre></div>
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<div class="highlight"><pre><span class="lineno">64</span> <span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="p">)</span></pre></div>
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<a href="https://papers.labml.ai">Trending Research Papers</a>
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<div class="highlight"><pre><span class="lineno">1</span><span></span><span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Callable</span>
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<span class="lineno">2</span>
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<span class="lineno">3</span><span class="kn">from</span> <span class="nn">labml.configs</span> <span class="kn">import</span> <span class="n">BaseConfigs</span><span class="p">,</span> <span class="n">option</span></pre></div>
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<div class='docs doc-strings'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-1'>#</a>
|
||||
</div>
|
||||
<p><a id="OptimizerConfigs"></p>
|
||||
<h2>Optimizer Configurations</h2>
|
||||
<p></a></p>
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">6</span><span class="k">class</span> <span class="nc">TokenizerConfigs</span><span class="p">(</span><span class="n">BaseConfigs</span><span class="p">):</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-2'>
|
||||
<div class='docs'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-2'>#</a>
|
||||
</div>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">13</span> <span class="n">tokenizer</span><span class="p">:</span> <span class="n">Callable</span> <span class="o">=</span> <span class="s1">'character'</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-3'>
|
||||
<div class='docs'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-3'>#</a>
|
||||
</div>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">15</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="lineno">16</span> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">_primary</span><span class="o">=</span><span class="s1">'tokenizer'</span><span class="p">)</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-4'>
|
||||
<div class='docs doc-strings'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-4'>#</a>
|
||||
</div>
|
||||
<h3>Basic english tokenizer</h3>
|
||||
<p>We use character level tokenizer in this experiment.
|
||||
You can switch by setting,</p>
|
||||
<pre><code> 'tokenizer': 'basic_english',
|
||||
</code></pre>
|
||||
|
||||
<p>as the configurations dictionary when starting the experiment.</p>
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">19</span><span class="nd">@option</span><span class="p">(</span><span class="n">TokenizerConfigs</span><span class="o">.</span><span class="n">tokenizer</span><span class="p">)</span>
|
||||
<span class="lineno">20</span><span class="k">def</span> <span class="nf">basic_english</span><span class="p">():</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-5'>
|
||||
<div class='docs'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-5'>#</a>
|
||||
</div>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">34</span> <span class="kn">from</span> <span class="nn">torchtext.data</span> <span class="kn">import</span> <span class="n">get_tokenizer</span>
|
||||
<span class="lineno">35</span> <span class="k">return</span> <span class="n">get_tokenizer</span><span class="p">(</span><span class="s1">'basic_english'</span><span class="p">)</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-6'>
|
||||
<div class='docs doc-strings'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-6'>#</a>
|
||||
</div>
|
||||
<h3>Character level tokenizer</h3>
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">38</span><span class="k">def</span> <span class="nf">character_tokenizer</span><span class="p">(</span><span class="n">x</span><span class="p">:</span> <span class="nb">str</span><span class="p">):</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-7'>
|
||||
<div class='docs'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-7'>#</a>
|
||||
</div>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">42</span> <span class="k">return</span> <span class="nb">list</span><span class="p">(</span><span class="n">x</span><span class="p">)</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-8'>
|
||||
<div class='docs doc-strings'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-8'>#</a>
|
||||
</div>
|
||||
<p>Character level tokenizer configuration</p>
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">45</span><span class="nd">@option</span><span class="p">(</span><span class="n">TokenizerConfigs</span><span class="o">.</span><span class="n">tokenizer</span><span class="p">)</span>
|
||||
<span class="lineno">46</span><span class="k">def</span> <span class="nf">character</span><span class="p">():</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='section' id='section-9'>
|
||||
<div class='docs'>
|
||||
<div class='section-link'>
|
||||
<a href='#section-9'>#</a>
|
||||
</div>
|
||||
|
||||
</div>
|
||||
<div class='code'>
|
||||
<div class="highlight"><pre><span class="lineno">50</span> <span class="k">return</span> <span class="n">character_tokenizer</span></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class='footer'>
|
||||
<a href="https://papers.labml.ai">Trending Research Papers</a>
|
||||
<a href="https://labml.ai">labml.ai</a>
|
||||
</div>
|
||||
</div>
|
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<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.4/MathJax.js?config=TeX-AMS_HTML">
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</script>
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<script type="text/x-mathjax-config">
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// Center justify equations in code and markdown cells. Elsewhere
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|
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|
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"HTML-CSS": { fonts: ["TeX"] }
|
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|
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|
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</script>
|
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<script>
|
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function handleImages() {
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var images = document.querySelectorAll('p>img')
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console.log(images);
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