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<div class="highlight"><pre><span class="lineno">1</span><span></span><span class="kn">import</span> <span class="nn">random</span>
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<span class="lineno">2</span><span class="kn">from</span> <span class="nn">pathlib</span> <span class="kn">import</span> <span class="n">PurePath</span><span class="p">,</span> <span class="n">Path</span>
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<span class="lineno">3</span><span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">List</span><span class="p">,</span> <span class="n">Callable</span><span class="p">,</span> <span class="n">Dict</span><span class="p">,</span> <span class="n">Optional</span>
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<span class="lineno">4</span>
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<span class="lineno">5</span><span class="kn">from</span> <span class="nn">torchvision</span> <span class="kn">import</span> <span class="n">datasets</span><span class="p">,</span> <span class="n">transforms</span>
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<span class="lineno">6</span>
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<span class="lineno">7</span><span class="kn">import</span> <span class="nn">torch</span>
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<span class="lineno">8</span><span class="kn">from</span> <span class="nn">labml</span> <span class="kn">import</span> <span class="n">lab</span>
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<span class="lineno">9</span><span class="kn">from</span> <span class="nn">labml</span> <span class="kn">import</span> <span class="n">monit</span>
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<span class="lineno">10</span><span class="kn">from</span> <span class="nn">labml.configs</span> <span class="kn">import</span> <span class="n">BaseConfigs</span>
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<span class="lineno">11</span><span class="kn">from</span> <span class="nn">labml.configs</span> <span class="kn">import</span> <span class="n">aggregate</span><span class="p">,</span> <span class="n">option</span>
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<span class="lineno">12</span><span class="kn">from</span> <span class="nn">labml.utils.download</span> <span class="kn">import</span> <span class="n">download_file</span>
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<span class="lineno">13</span><span class="kn">from</span> <span class="nn">torch.utils.data</span> <span class="kn">import</span> <span class="n">DataLoader</span>
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<span class="lineno">14</span><span class="kn">from</span> <span class="nn">torch.utils.data</span> <span class="kn">import</span> <span class="n">IterableDataset</span><span class="p">,</span> <span class="n">Dataset</span></pre></div>
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<a href='#section-1'>#</a>
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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">_mnist_dataset</span><span class="p">(</span><span class="n">is_train</span><span class="p">,</span> <span class="n">transform</span><span class="p">):</span>
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<span class="lineno">18</span> <span class="k">return</span> <span class="n">datasets</span><span class="o">.</span><span class="n">MNIST</span><span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="n">lab</span><span class="o">.</span><span class="n">get_data_path</span><span class="p">()),</span>
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<span class="lineno">19</span> <span class="n">train</span><span class="o">=</span><span class="n">is_train</span><span class="p">,</span>
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<span class="lineno">20</span> <span class="n">download</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
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<span class="lineno">21</span> <span class="n">transform</span><span class="o">=</span><span class="n">transform</span><span class="p">)</span></pre></div>
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<div class='section' id='section-2'>
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<div class='docs doc-strings'>
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<div class='section-link'>
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<a href='#section-2'>#</a>
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</div>
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<p> Configurable MNIST data set.</p>
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<p>Arguments: dataset_name (str): name of the data set, <code class="highlight"><span></span></code>
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MNIST<code class="highlight"><span></span></code>
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dataset_transforms (torchvision.transforms.Compose): image transformations train_dataset (torchvision.datasets.MNIST): training dataset valid_dataset (torchvision.datasets.MNIST): validation dataset</p>
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<p> train_loader (torch.utils.data.DataLoader): training data loader valid_loader (torch.utils.data.DataLoader): validation data loader</p>
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<p> train_batch_size (int): training batch size valid_batch_size (int): validation batch size</p>
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<p> train_loader_shuffle (bool): whether to shuffle training data valid_loader_shuffle (bool): whether to shuffle validation data</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">24</span><span class="k">class</span> <span class="nc">MNISTConfigs</span><span class="p">(</span><span class="n">BaseConfigs</span><span class="p">):</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-3'>
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<div class='docs'>
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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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<div class='code'>
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<div class="highlight"><pre><span class="lineno">44</span> <span class="n">dataset_name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s1">'MNIST'</span>
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<span class="lineno">45</span> <span class="n">dataset_transforms</span><span class="p">:</span> <span class="n">transforms</span><span class="o">.</span><span class="n">Compose</span>
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<span class="lineno">46</span> <span class="n">train_dataset</span><span class="p">:</span> <span class="n">datasets</span><span class="o">.</span><span class="n">MNIST</span>
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<span class="lineno">47</span> <span class="n">valid_dataset</span><span class="p">:</span> <span class="n">datasets</span><span class="o">.</span><span class="n">MNIST</span>
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<span class="lineno">48</span>
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<span class="lineno">49</span> <span class="n">train_loader</span><span class="p">:</span> <span class="n">DataLoader</span>
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<span class="lineno">50</span> <span class="n">valid_loader</span><span class="p">:</span> <span class="n">DataLoader</span>
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<span class="lineno">51</span>
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<span class="lineno">52</span> <span class="n">train_batch_size</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">64</span>
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<span class="lineno">53</span> <span class="n">valid_batch_size</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">1024</span>
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<span class="lineno">54</span>
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<span class="lineno">55</span> <span class="n">train_loader_shuffle</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span>
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<span class="lineno">56</span> <span class="n">valid_loader_shuffle</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-4'>
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<div class='docs doc-strings'>
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<div class='section-link'>
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<a href='#section-4'>#</a>
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</div>
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<p> Configurable CIFAR 10 data set.</p>
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<p>Arguments: dataset_name (str): name of the data set, <code class="highlight"><span></span></code>
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CIFAR10<code class="highlight"><span></span></code>
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dataset_transforms (torchvision.transforms.Compose): image transformations train_dataset (torchvision.datasets.CIFAR10): training dataset valid_dataset (torchvision.datasets.CIFAR10): validation dataset</p>
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<p> train_loader (torch.utils.data.DataLoader): training data loader valid_loader (torch.utils.data.DataLoader): validation data loader</p>
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<p> train_batch_size (int): training batch size valid_batch_size (int): validation batch size</p>
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<p> train_loader_shuffle (bool): whether to shuffle training data valid_loader_shuffle (bool): whether to shuffle validation data</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">59</span><span class="nd">@option</span><span class="p">(</span><span class="n">MNISTConfigs</span><span class="o">.</span><span class="n">dataset_transforms</span><span class="p">)</span>
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<span class="lineno">60</span><span class="k">def</span> <span class="nf">mnist_transforms</span><span class="p">():</span>
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<span class="lineno">61</span> <span class="k">return</span> <span class="n">transforms</span><span class="o">.</span><span class="n">Compose</span><span class="p">([</span>
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<span class="lineno">62</span> <span class="n">transforms</span><span class="o">.</span><span class="n">ToTensor</span><span class="p">(),</span>
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<span class="lineno">63</span> <span class="n">transforms</span><span class="o">.</span><span class="n">Normalize</span><span class="p">((</span><span class="mf">0.1307</span><span class="p">,),</span> <span class="p">(</span><span class="mf">0.3081</span><span class="p">,))</span>
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<span class="lineno">64</span> <span class="p">])</span>
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<span class="lineno">65</span>
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<span class="lineno">66</span>
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<span class="lineno">67</span><span class="nd">@option</span><span class="p">(</span><span class="n">MNISTConfigs</span><span class="o">.</span><span class="n">train_dataset</span><span class="p">)</span>
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<span class="lineno">68</span><span class="k">def</span> <span class="nf">mnist_train_dataset</span><span class="p">(</span><span class="n">c</span><span class="p">:</span> <span class="n">MNISTConfigs</span><span class="p">):</span>
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<span class="lineno">69</span> <span class="k">return</span> <span class="n">_mnist_dataset</span><span class="p">(</span><span class="kc">True</span><span class="p">,</span> <span class="n">c</span><span class="o">.</span><span class="n">dataset_transforms</span><span class="p">)</span>
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<span class="lineno">70</span>
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<span class="lineno">71</span>
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<span class="lineno">72</span><span class="nd">@option</span><span class="p">(</span><span class="n">MNISTConfigs</span><span class="o">.</span><span class="n">valid_dataset</span><span class="p">)</span>
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<span class="lineno">73</span><span class="k">def</span> <span class="nf">mnist_valid_dataset</span><span class="p">(</span><span class="n">c</span><span class="p">:</span> <span class="n">MNISTConfigs</span><span class="p">):</span>
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<span class="lineno">74</span> <span class="k">return</span> <span class="n">_mnist_dataset</span><span class="p">(</span><span class="kc">False</span><span class="p">,</span> <span class="n">c</span><span class="o">.</span><span class="n">dataset_transforms</span><span class="p">)</span>
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<span class="lineno">75</span>
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<span class="lineno">76</span>
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<span class="lineno">77</span><span class="nd">@option</span><span class="p">(</span><span class="n">MNISTConfigs</span><span class="o">.</span><span class="n">train_loader</span><span class="p">)</span>
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<span class="lineno">78</span><span class="k">def</span> <span class="nf">mnist_train_loader</span><span class="p">(</span><span class="n">c</span><span class="p">:</span> <span class="n">MNISTConfigs</span><span class="p">):</span>
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<span class="lineno">79</span> <span class="k">return</span> <span class="n">DataLoader</span><span class="p">(</span><span class="n">c</span><span class="o">.</span><span class="n">train_dataset</span><span class="p">,</span>
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<span class="lineno">80</span> <span class="n">batch_size</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">train_batch_size</span><span class="p">,</span>
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<span class="lineno">81</span> <span class="n">shuffle</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">train_loader_shuffle</span><span class="p">)</span>
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<span class="lineno">82</span>
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<span class="lineno">83</span>
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<span class="lineno">84</span><span class="nd">@option</span><span class="p">(</span><span class="n">MNISTConfigs</span><span class="o">.</span><span class="n">valid_loader</span><span class="p">)</span>
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<span class="lineno">85</span><span class="k">def</span> <span class="nf">mnist_valid_loader</span><span class="p">(</span><span class="n">c</span><span class="p">:</span> <span class="n">MNISTConfigs</span><span class="p">):</span>
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<span class="lineno">86</span> <span class="k">return</span> <span class="n">DataLoader</span><span class="p">(</span><span class="n">c</span><span class="o">.</span><span class="n">valid_dataset</span><span class="p">,</span>
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<span class="lineno">87</span> <span class="n">batch_size</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">valid_batch_size</span><span class="p">,</span>
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<span class="lineno">88</span> <span class="n">shuffle</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">valid_loader_shuffle</span><span class="p">)</span>
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<span class="lineno">89</span>
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<span class="lineno">90</span>
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<span class="lineno">91</span><span class="n">aggregate</span><span class="p">(</span><span class="n">MNISTConfigs</span><span class="o">.</span><span class="n">dataset_name</span><span class="p">,</span> <span class="s1">'MNIST'</span><span class="p">,</span>
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<span class="lineno">92</span> <span class="p">(</span><span class="n">MNISTConfigs</span><span class="o">.</span><span class="n">dataset_transforms</span><span class="p">,</span> <span class="s1">'mnist_transforms'</span><span class="p">),</span>
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<span class="lineno">93</span> <span class="p">(</span><span class="n">MNISTConfigs</span><span class="o">.</span><span class="n">train_dataset</span><span class="p">,</span> <span class="s1">'mnist_train_dataset'</span><span class="p">),</span>
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<span class="lineno">94</span> <span class="p">(</span><span class="n">MNISTConfigs</span><span class="o">.</span><span class="n">valid_dataset</span><span class="p">,</span> <span class="s1">'mnist_valid_dataset'</span><span class="p">),</span>
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<span class="lineno">95</span> <span class="p">(</span><span class="n">MNISTConfigs</span><span class="o">.</span><span class="n">train_loader</span><span class="p">,</span> <span class="s1">'mnist_train_loader'</span><span class="p">),</span>
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<span class="lineno">96</span> <span class="p">(</span><span class="n">MNISTConfigs</span><span class="o">.</span><span class="n">valid_loader</span><span class="p">,</span> <span class="s1">'mnist_valid_loader'</span><span class="p">))</span>
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<span class="lineno">97</span>
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<span class="lineno">98</span>
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<span class="lineno">99</span><span class="k">def</span> <span class="nf">_cifar_dataset</span><span class="p">(</span><span class="n">is_train</span><span class="p">,</span> <span class="n">transform</span><span class="p">):</span>
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<span class="lineno">100</span> <span class="k">return</span> <span class="n">datasets</span><span class="o">.</span><span class="n">CIFAR10</span><span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="n">lab</span><span class="o">.</span><span class="n">get_data_path</span><span class="p">()),</span>
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<span class="lineno">101</span> <span class="n">train</span><span class="o">=</span><span class="n">is_train</span><span class="p">,</span>
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<span class="lineno">102</span> <span class="n">download</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
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<span class="lineno">103</span> <span class="n">transform</span><span class="o">=</span><span class="n">transform</span><span class="p">)</span>
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<span class="lineno">104</span>
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<span class="lineno">105</span>
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<span class="lineno">106</span><span class="k">class</span> <span class="nc">CIFAR10Configs</span><span class="p">(</span><span class="n">BaseConfigs</span><span class="p">):</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-5'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-5'>#</a>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">125</span> <span class="n">dataset_name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s1">'CIFAR10'</span>
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<span class="lineno">126</span> <span class="n">dataset_transforms</span><span class="p">:</span> <span class="n">transforms</span><span class="o">.</span><span class="n">Compose</span>
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<span class="lineno">127</span> <span class="n">train_dataset</span><span class="p">:</span> <span class="n">datasets</span><span class="o">.</span><span class="n">CIFAR10</span>
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<span class="lineno">128</span> <span class="n">valid_dataset</span><span class="p">:</span> <span class="n">datasets</span><span class="o">.</span><span class="n">CIFAR10</span>
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<span class="lineno">129</span>
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<span class="lineno">130</span> <span class="n">train_loader</span><span class="p">:</span> <span class="n">DataLoader</span>
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<span class="lineno">131</span> <span class="n">valid_loader</span><span class="p">:</span> <span class="n">DataLoader</span>
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<span class="lineno">132</span>
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<span class="lineno">133</span> <span class="n">train_batch_size</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">64</span>
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<span class="lineno">134</span> <span class="n">valid_batch_size</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">1024</span>
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<span class="lineno">135</span>
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<span class="lineno">136</span> <span class="n">train_loader_shuffle</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span>
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<span class="lineno">137</span> <span class="n">valid_loader_shuffle</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-6'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-6'>#</a>
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</div>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">140</span><span class="nd">@CIFAR10Configs</span><span class="o">.</span><span class="n">calc</span><span class="p">(</span><span class="n">CIFAR10Configs</span><span class="o">.</span><span class="n">dataset_transforms</span><span class="p">)</span>
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<span class="lineno">141</span><span class="k">def</span> <span class="nf">cifar10_transforms</span><span class="p">():</span>
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<span class="lineno">142</span> <span class="k">return</span> <span class="n">transforms</span><span class="o">.</span><span class="n">Compose</span><span class="p">([</span>
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<span class="lineno">143</span> <span class="n">transforms</span><span class="o">.</span><span class="n">ToTensor</span><span class="p">(),</span>
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<span class="lineno">144</span> <span class="n">transforms</span><span class="o">.</span><span class="n">Normalize</span><span class="p">((</span><span class="mf">0.5</span><span class="p">,</span> <span class="mf">0.5</span><span class="p">,</span> <span class="mf">0.5</span><span class="p">),</span> <span class="p">(</span><span class="mf">0.5</span><span class="p">,</span> <span class="mf">0.5</span><span class="p">,</span> <span class="mf">0.5</span><span class="p">))</span>
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<span class="lineno">145</span> <span class="p">])</span>
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<span class="lineno">146</span>
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<span class="lineno">147</span>
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<span class="lineno">148</span><span class="nd">@CIFAR10Configs</span><span class="o">.</span><span class="n">calc</span><span class="p">(</span><span class="n">CIFAR10Configs</span><span class="o">.</span><span class="n">train_dataset</span><span class="p">)</span>
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<span class="lineno">149</span><span class="k">def</span> <span class="nf">cifar10_train_dataset</span><span class="p">(</span><span class="n">c</span><span class="p">:</span> <span class="n">CIFAR10Configs</span><span class="p">):</span>
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<span class="lineno">150</span> <span class="k">return</span> <span class="n">_cifar_dataset</span><span class="p">(</span><span class="kc">True</span><span class="p">,</span> <span class="n">c</span><span class="o">.</span><span class="n">dataset_transforms</span><span class="p">)</span>
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<span class="lineno">151</span>
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<span class="lineno">152</span>
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<span class="lineno">153</span><span class="nd">@CIFAR10Configs</span><span class="o">.</span><span class="n">calc</span><span class="p">(</span><span class="n">CIFAR10Configs</span><span class="o">.</span><span class="n">valid_dataset</span><span class="p">)</span>
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<span class="lineno">154</span><span class="k">def</span> <span class="nf">cifar10_valid_dataset</span><span class="p">(</span><span class="n">c</span><span class="p">:</span> <span class="n">CIFAR10Configs</span><span class="p">):</span>
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<span class="lineno">155</span> <span class="k">return</span> <span class="n">_cifar_dataset</span><span class="p">(</span><span class="kc">False</span><span class="p">,</span> <span class="n">c</span><span class="o">.</span><span class="n">dataset_transforms</span><span class="p">)</span>
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<span class="lineno">156</span>
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<span class="lineno">157</span>
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<span class="lineno">158</span><span class="nd">@CIFAR10Configs</span><span class="o">.</span><span class="n">calc</span><span class="p">(</span><span class="n">CIFAR10Configs</span><span class="o">.</span><span class="n">train_loader</span><span class="p">)</span>
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<span class="lineno">159</span><span class="k">def</span> <span class="nf">cifar10_train_loader</span><span class="p">(</span><span class="n">c</span><span class="p">:</span> <span class="n">CIFAR10Configs</span><span class="p">):</span>
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<span class="lineno">160</span> <span class="k">return</span> <span class="n">DataLoader</span><span class="p">(</span><span class="n">c</span><span class="o">.</span><span class="n">train_dataset</span><span class="p">,</span>
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<span class="lineno">161</span> <span class="n">batch_size</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">train_batch_size</span><span class="p">,</span>
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<span class="lineno">162</span> <span class="n">shuffle</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">train_loader_shuffle</span><span class="p">)</span>
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<span class="lineno">163</span>
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<span class="lineno">164</span>
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<span class="lineno">165</span><span class="nd">@CIFAR10Configs</span><span class="o">.</span><span class="n">calc</span><span class="p">(</span><span class="n">CIFAR10Configs</span><span class="o">.</span><span class="n">valid_loader</span><span class="p">)</span>
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<span class="lineno">166</span><span class="k">def</span> <span class="nf">cifar10_valid_loader</span><span class="p">(</span><span class="n">c</span><span class="p">:</span> <span class="n">CIFAR10Configs</span><span class="p">):</span>
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<span class="lineno">167</span> <span class="k">return</span> <span class="n">DataLoader</span><span class="p">(</span><span class="n">c</span><span class="o">.</span><span class="n">valid_dataset</span><span class="p">,</span>
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<span class="lineno">168</span> <span class="n">batch_size</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">valid_batch_size</span><span class="p">,</span>
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<span class="lineno">169</span> <span class="n">shuffle</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">valid_loader_shuffle</span><span class="p">)</span>
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<span class="lineno">170</span>
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<span class="lineno">171</span>
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<span class="lineno">172</span><span class="n">CIFAR10Configs</span><span class="o">.</span><span class="n">aggregate</span><span class="p">(</span><span class="n">CIFAR10Configs</span><span class="o">.</span><span class="n">dataset_name</span><span class="p">,</span> <span class="s1">'CIFAR10'</span><span class="p">,</span>
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<span class="lineno">173</span> <span class="p">(</span><span class="n">CIFAR10Configs</span><span class="o">.</span><span class="n">dataset_transforms</span><span class="p">,</span> <span class="s1">'cifar10_transforms'</span><span class="p">),</span>
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<span class="lineno">174</span> <span class="p">(</span><span class="n">CIFAR10Configs</span><span class="o">.</span><span class="n">train_dataset</span><span class="p">,</span> <span class="s1">'cifar10_train_dataset'</span><span class="p">),</span>
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<span class="lineno">175</span> <span class="p">(</span><span class="n">CIFAR10Configs</span><span class="o">.</span><span class="n">valid_dataset</span><span class="p">,</span> <span class="s1">'cifar10_valid_dataset'</span><span class="p">),</span>
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<span class="lineno">176</span> <span class="p">(</span><span class="n">CIFAR10Configs</span><span class="o">.</span><span class="n">train_loader</span><span class="p">,</span> <span class="s1">'cifar10_train_loader'</span><span class="p">),</span>
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<span class="lineno">177</span> <span class="p">(</span><span class="n">CIFAR10Configs</span><span class="o">.</span><span class="n">valid_loader</span><span class="p">,</span> <span class="s1">'cifar10_valid_loader'</span><span class="p">))</span>
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<span class="lineno">178</span>
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<span class="lineno">179</span>
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<span class="lineno">180</span><span class="k">class</span> <span class="nc">TextDataset</span><span class="p">:</span>
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<span class="lineno">181</span> <span class="n">itos</span><span class="p">:</span> <span class="n">List</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span>
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<span class="lineno">182</span> <span class="n">stoi</span><span class="p">:</span> <span class="n">Dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">int</span><span class="p">]</span>
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<span class="lineno">183</span> <span class="n">n_tokens</span><span class="p">:</span> <span class="nb">int</span>
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<span class="lineno">184</span> <span class="n">train</span><span class="p">:</span> <span class="nb">str</span>
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<span class="lineno">185</span> <span class="n">valid</span><span class="p">:</span> <span class="nb">str</span>
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<span class="lineno">186</span> <span class="n">standard_tokens</span><span class="p">:</span> <span class="n">List</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="p">[]</span>
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<span class="lineno">187</span>
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<span class="lineno">188</span> <span class="nd">@staticmethod</span>
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<span class="lineno">189</span> <span class="k">def</span> <span class="nf">load</span><span class="p">(</span><span class="n">path</span><span class="p">:</span> <span class="n">PurePath</span><span class="p">):</span>
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<span class="lineno">190</span> <span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="n">path</span><span class="p">),</span> <span class="s1">'r'</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
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<span class="lineno">191</span> <span class="k">return</span> <span class="n">f</span><span class="o">.</span><span class="n">read</span><span class="p">()</span>
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<span class="lineno">192</span>
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<span class="lineno">193</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">path</span><span class="p">:</span> <span class="n">PurePath</span><span class="p">,</span> <span class="n">tokenizer</span><span class="p">:</span> <span class="n">Callable</span><span class="p">,</span> <span class="n">train</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">valid</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">test</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span>
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<span class="lineno">194</span> <span class="n">n_tokens</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">int</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
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<span class="lineno">195</span> <span class="n">stoi</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">int</span><span class="p">]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
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<span class="lineno">196</span> <span class="n">itos</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">List</span><span class="p">[</span><span class="nb">str</span><span class="p">]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">):</span>
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<span class="lineno">197</span> <span class="bp">self</span><span class="o">.</span><span class="n">test</span> <span class="o">=</span> <span class="n">test</span>
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<span class="lineno">198</span> <span class="bp">self</span><span class="o">.</span><span class="n">valid</span> <span class="o">=</span> <span class="n">valid</span>
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<span class="lineno">199</span> <span class="bp">self</span><span class="o">.</span><span class="n">train</span> <span class="o">=</span> <span class="n">train</span>
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<span class="lineno">200</span> <span class="bp">self</span><span class="o">.</span><span class="n">tokenizer</span> <span class="o">=</span> <span class="n">tokenizer</span>
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<span class="lineno">201</span> <span class="bp">self</span><span class="o">.</span><span class="n">path</span> <span class="o">=</span> <span class="n">path</span>
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<span class="lineno">202</span>
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<span class="lineno">203</span> <span class="k">if</span> <span class="n">n_tokens</span> <span class="ow">or</span> <span class="n">stoi</span> <span class="ow">or</span> <span class="n">itos</span><span class="p">:</span>
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<span class="lineno">204</span> <span class="k">assert</span> <span class="n">stoi</span> <span class="ow">and</span> <span class="n">itos</span> <span class="ow">and</span> <span class="n">n_tokens</span>
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<span class="lineno">205</span> <span class="bp">self</span><span class="o">.</span><span class="n">n_tokens</span> <span class="o">=</span> <span class="n">n_tokens</span>
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<span class="lineno">206</span> <span class="bp">self</span><span class="o">.</span><span class="n">stoi</span> <span class="o">=</span> <span class="n">stoi</span>
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<span class="lineno">207</span> <span class="bp">self</span><span class="o">.</span><span class="n">itos</span> <span class="o">=</span> <span class="n">itos</span>
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<span class="lineno">208</span> <span class="k">else</span><span class="p">:</span>
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<span class="lineno">209</span> <span class="bp">self</span><span class="o">.</span><span class="n">n_tokens</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">standard_tokens</span><span class="p">)</span>
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<span class="lineno">210</span> <span class="bp">self</span><span class="o">.</span><span class="n">stoi</span> <span class="o">=</span> <span class="p">{</span><span class="n">t</span><span class="p">:</span> <span class="n">i</span> <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">t</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">standard_tokens</span><span class="p">)}</span>
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<span class="lineno">211</span>
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<span class="lineno">212</span> <span class="k">with</span> <span class="n">monit</span><span class="o">.</span><span class="n">section</span><span class="p">(</span><span class="s2">"Tokenize"</span><span class="p">):</span>
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<span class="lineno">213</span> <span class="n">tokens</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tokenizer</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">train</span><span class="p">)</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">tokenizer</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">valid</span><span class="p">)</span>
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<span class="lineno">214</span> <span class="n">tokens</span> <span class="o">=</span> <span class="nb">sorted</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="nb">set</span><span class="p">(</span><span class="n">tokens</span><span class="p">)))</span>
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<span class="lineno">215</span>
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<span class="lineno">216</span> <span class="k">for</span> <span class="n">t</span> <span class="ow">in</span> <span class="n">monit</span><span class="o">.</span><span class="n">iterate</span><span class="p">(</span><span class="s2">"Build vocabulary"</span><span class="p">,</span> <span class="n">tokens</span><span class="p">):</span>
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<span class="lineno">217</span> <span class="bp">self</span><span class="o">.</span><span class="n">stoi</span><span class="p">[</span><span class="n">t</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">n_tokens</span>
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<span class="lineno">218</span> <span class="bp">self</span><span class="o">.</span><span class="n">n_tokens</span> <span class="o">+=</span> <span class="mi">1</span>
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<span class="lineno">219</span>
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<span class="lineno">220</span> <span class="bp">self</span><span class="o">.</span><span class="n">itos</span> <span class="o">=</span> <span class="p">[</span><span class="s1">''</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">n_tokens</span>
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<span class="lineno">221</span> <span class="k">for</span> <span class="n">t</span><span class="p">,</span> <span class="n">n</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">stoi</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
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<span class="lineno">222</span> <span class="bp">self</span><span class="o">.</span><span class="n">itos</span><span class="p">[</span><span class="n">n</span><span class="p">]</span> <span class="o">=</span> <span class="n">t</span>
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<span class="lineno">223</span>
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<span class="lineno">224</span> <span class="k">def</span> <span class="nf">text_to_i</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">text</span><span class="p">:</span> <span class="nb">str</span><span class="p">)</span> <span class="o">-></span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">:</span>
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<span class="lineno">225</span> <span class="n">tokens</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tokenizer</span><span class="p">(</span><span class="n">text</span><span class="p">)</span>
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<span class="lineno">226</span> <span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">stoi</span><span class="p">[</span><span class="n">s</span><span class="p">]</span> <span class="k">for</span> <span class="n">s</span> <span class="ow">in</span> <span class="n">tokens</span> <span class="k">if</span> <span class="n">s</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">stoi</span><span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">long</span><span class="p">)</span>
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<span class="lineno">227</span>
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<span class="lineno">228</span> <span class="k">def</span> <span class="fm">__repr__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
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<span class="lineno">229</span> <span class="k">return</span> <span class="sa">f</span><span class="s1">'</span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">train</span><span class="p">)</span><span class="w"> </span><span class="o">/</span><span class="w"> </span><span class="mi">1_000_000</span><span class="w"> </span><span class="si">:</span><span class="s1">,.2f</span><span class="si">}</span><span class="s1">M, </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">valid</span><span class="p">)</span><span class="w"> </span><span class="o">/</span><span class="w"> </span><span class="mi">1_000_000</span><span class="w"> </span><span class="si">:</span><span class="s1">,.2f</span><span class="si">}</span><span class="s1">M - </span><span class="si">{</span><span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">path</span><span class="p">)</span><span class="si">}</span><span class="s1">'</span>
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<span class="lineno">230</span>
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<span class="lineno">231</span>
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<span class="lineno">232</span><span class="k">class</span> <span class="nc">SequentialDataLoader</span><span class="p">(</span><span class="n">IterableDataset</span><span class="p">):</span>
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<span class="lineno">233</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="o">*</span><span class="p">,</span> <span class="n">text</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">dataset</span><span class="p">:</span> <span class="n">TextDataset</span><span class="p">,</span>
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<span class="lineno">234</span> <span class="n">batch_size</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">seq_len</span><span class="p">:</span> <span class="nb">int</span><span class="p">):</span>
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<span class="lineno">235</span> <span class="bp">self</span><span class="o">.</span><span class="n">seq_len</span> <span class="o">=</span> <span class="n">seq_len</span>
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<span class="lineno">236</span> <span class="n">data</span> <span class="o">=</span> <span class="n">dataset</span><span class="o">.</span><span class="n">text_to_i</span><span class="p">(</span><span class="n">text</span><span class="p">)</span>
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<span class="lineno">237</span> <span class="n">n_batch</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">//</span> <span class="n">batch_size</span>
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<span class="lineno">238</span> <span class="n">data</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">narrow</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="n">n_batch</span> <span class="o">*</span> <span class="n">batch_size</span><span class="p">)</span>
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<span class="lineno">239</span> <span class="n">data</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="n">batch_size</span><span class="p">,</span> <span class="o">-</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">t</span><span class="p">()</span><span class="o">.</span><span class="n">contiguous</span><span class="p">()</span>
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<span class="lineno">240</span> <span class="bp">self</span><span class="o">.</span><span class="n">data</span> <span class="o">=</span> <span class="n">data</span>
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<span class="lineno">241</span>
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<span class="lineno">242</span> <span class="k">def</span> <span class="fm">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
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<span class="lineno">243</span> <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">//</span> <span class="bp">self</span><span class="o">.</span><span class="n">seq_len</span>
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<span class="lineno">244</span>
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<span class="lineno">245</span> <span class="k">def</span> <span class="fm">__iter__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
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<span class="lineno">246</span> <span class="bp">self</span><span class="o">.</span><span class="n">idx</span> <span class="o">=</span> <span class="mi">0</span>
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<span class="lineno">247</span> <span class="k">return</span> <span class="bp">self</span>
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<span class="lineno">248</span>
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<span class="lineno">249</span> <span class="k">def</span> <span class="fm">__next__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
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<span class="lineno">250</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">idx</span> <span class="o">>=</span> <span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">-</span> <span class="mi">1</span><span class="p">:</span>
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<span class="lineno">251</span> <span class="k">raise</span> <span class="ne">StopIteration</span><span class="p">()</span>
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<span class="lineno">252</span>
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<span class="lineno">253</span> <span class="n">seq_len</span> <span class="o">=</span> <span class="nb">min</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">seq_len</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">-</span> <span class="mi">1</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">idx</span><span class="p">)</span>
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<span class="lineno">254</span> <span class="n">i</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">idx</span> <span class="o">+</span> <span class="n">seq_len</span>
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<span class="lineno">255</span> <span class="n">data</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">idx</span><span class="p">:</span> <span class="n">i</span><span class="p">]</span>
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<span class="lineno">256</span> <span class="n">target</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">idx</span> <span class="o">+</span> <span class="mi">1</span><span class="p">:</span> <span class="n">i</span> <span class="o">+</span> <span class="mi">1</span><span class="p">]</span>
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<span class="lineno">257</span> <span class="bp">self</span><span class="o">.</span><span class="n">idx</span> <span class="o">=</span> <span class="n">i</span>
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<span class="lineno">258</span> <span class="k">return</span> <span class="n">data</span><span class="p">,</span> <span class="n">target</span>
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<span class="lineno">259</span>
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<span class="lineno">260</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>
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<span class="lineno">261</span> <span class="n">seq_len</span> <span class="o">=</span> <span class="nb">min</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">seq_len</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">-</span> <span class="mi">1</span> <span class="o">-</span> <span class="n">idx</span><span class="p">)</span>
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<span class="lineno">262</span> <span class="n">i</span> <span class="o">=</span> <span class="n">idx</span> <span class="o">+</span> <span class="n">seq_len</span>
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<span class="lineno">263</span> <span class="n">data</span> <span class="o">=</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> <span class="n">i</span><span class="p">]</span>
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<span class="lineno">264</span> <span class="n">target</span> <span class="o">=</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="o">+</span> <span class="mi">1</span><span class="p">:</span> <span class="n">i</span> <span class="o">+</span> <span class="mi">1</span><span class="p">]</span>
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<span class="lineno">265</span> <span class="k">return</span> <span class="n">data</span><span class="p">,</span> <span class="n">target</span>
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<span class="lineno">266</span>
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<span class="lineno">267</span>
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<span class="lineno">268</span><span class="k">class</span> <span class="nc">SequentialUnBatchedDataset</span><span class="p">(</span><span class="n">Dataset</span><span class="p">):</span>
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<span class="lineno">269</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="o">*</span><span class="p">,</span> <span class="n">text</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">dataset</span><span class="p">:</span> <span class="n">TextDataset</span><span class="p">,</span>
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<span class="lineno">270</span> <span class="n">seq_len</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span>
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<span class="lineno">271</span> <span class="n">is_random_offset</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">):</span>
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<span class="lineno">272</span> <span class="bp">self</span><span class="o">.</span><span class="n">is_random_offset</span> <span class="o">=</span> <span class="n">is_random_offset</span>
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<span class="lineno">273</span> <span class="bp">self</span><span class="o">.</span><span class="n">seq_len</span> <span class="o">=</span> <span class="n">seq_len</span>
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<span class="lineno">274</span> <span class="bp">self</span><span class="o">.</span><span class="n">data</span> <span class="o">=</span> <span class="n">dataset</span><span class="o">.</span><span class="n">text_to_i</span><span class="p">(</span><span class="n">text</span><span class="p">)</span>
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<span class="lineno">275</span>
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<span class="lineno">276</span> <span class="k">def</span> <span class="fm">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
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<span class="lineno">277</span> <span class="k">return</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)</span> <span class="o">//</span> <span class="bp">self</span><span class="o">.</span><span class="n">seq_len</span>
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<span class="lineno">278</span>
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<span class="lineno">279</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>
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<span class="lineno">280</span> <span class="n">start</span> <span class="o">=</span> <span class="n">idx</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">seq_len</span>
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<span class="lineno">281</span> <span class="k">assert</span> <span class="n">start</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">seq_len</span> <span class="o">+</span> <span class="mi">1</span> <span class="o"><=</span> <span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
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<span class="lineno">282</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">is_random_offset</span><span class="p">:</span>
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<span class="lineno">283</span> <span class="n">start</span> <span class="o">+=</span> <span class="n">random</span><span class="o">.</span><span class="n">randint</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="nb">min</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">seq_len</span> <span class="o">-</span> <span class="mi">1</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">-</span> <span class="p">(</span><span class="n">start</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">seq_len</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)))</span>
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<span class="lineno">284</span>
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<span class="lineno">285</span> <span class="n">end</span> <span class="o">=</span> <span class="n">start</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">seq_len</span>
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<span class="lineno">286</span> <span class="n">data</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="p">[</span><span class="n">start</span><span class="p">:</span> <span class="n">end</span><span class="p">]</span>
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<span class="lineno">287</span> <span class="n">target</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="p">[</span><span class="n">start</span> <span class="o">+</span> <span class="mi">1</span><span class="p">:</span> <span class="n">end</span> <span class="o">+</span> <span class="mi">1</span><span class="p">]</span>
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<span class="lineno">288</span> <span class="k">return</span> <span class="n">data</span><span class="p">,</span> <span class="n">target</span>
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<span class="lineno">289</span>
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<span class="lineno">290</span>
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<span class="lineno">291</span><span class="k">class</span> <span class="nc">TextFileDataset</span><span class="p">(</span><span class="n">TextDataset</span><span class="p">):</span>
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<span class="lineno">292</span> <span class="n">standard_tokens</span> <span class="o">=</span> <span class="p">[]</span>
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<span class="lineno">293</span>
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<span class="lineno">294</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">path</span><span class="p">:</span> <span class="n">PurePath</span><span class="p">,</span> <span class="n">tokenizer</span><span class="p">:</span> <span class="n">Callable</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span>
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<span class="lineno">295</span> <span class="n">url</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
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<span class="lineno">296</span> <span class="n">filter_subset</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">int</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">):</span>
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<span class="lineno">297</span> <span class="n">path</span> <span class="o">=</span> <span class="n">Path</span><span class="p">(</span><span class="n">path</span><span class="p">)</span>
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<span class="lineno">298</span> <span class="k">if</span> <span class="ow">not</span> <span class="n">path</span><span class="o">.</span><span class="n">exists</span><span class="p">():</span>
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<span class="lineno">299</span> <span class="k">if</span> <span class="ow">not</span> <span class="n">url</span><span class="p">:</span>
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<span class="lineno">300</span> <span class="k">raise</span> <span class="ne">FileNotFoundError</span><span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="n">path</span><span class="p">))</span>
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<span class="lineno">301</span> <span class="k">else</span><span class="p">:</span>
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<span class="lineno">302</span> <span class="n">download_file</span><span class="p">(</span><span class="n">url</span><span class="p">,</span> <span class="n">path</span><span class="p">)</span>
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<span class="lineno">303</span>
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<span class="lineno">304</span> <span class="k">with</span> <span class="n">monit</span><span class="o">.</span><span class="n">section</span><span class="p">(</span><span class="s2">"Load data"</span><span class="p">):</span>
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<span class="lineno">305</span> <span class="n">text</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="n">path</span><span class="p">)</span>
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<span class="lineno">306</span> <span class="k">if</span> <span class="n">filter_subset</span><span class="p">:</span>
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<span class="lineno">307</span> <span class="n">text</span> <span class="o">=</span> <span class="n">text</span><span class="p">[:</span><span class="n">filter_subset</span><span class="p">]</span>
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<span class="lineno">308</span> <span class="n">split</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">text</span><span class="p">)</span> <span class="o">*</span> <span class="mf">.9</span><span class="p">)</span>
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<span class="lineno">309</span> <span class="n">train</span> <span class="o">=</span> <span class="n">text</span><span class="p">[:</span><span class="n">split</span><span class="p">]</span>
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<span class="lineno">310</span> <span class="n">valid</span> <span class="o">=</span> <span class="n">text</span><span class="p">[</span><span class="n">split</span><span class="p">:]</span>
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<span class="lineno">311</span>
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<span class="lineno">312</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">path</span><span class="p">,</span> <span class="n">tokenizer</span><span class="p">,</span> <span class="n">train</span><span class="p">,</span> <span class="n">valid</span><span class="p">,</span> <span class="s1">''</span><span class="p">)</span>
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<span class="lineno">313</span>
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<span class="lineno">314</span>
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<span class="lineno">315</span><span class="k">def</span> <span class="nf">_test_tiny_shakespeare</span><span class="p">():</span>
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|
<span class="lineno">316</span> <span class="kn">from</span> <span class="nn">labml</span> <span class="kn">import</span> <span class="n">lab</span>
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|
<span class="lineno">317</span> <span class="n">_</span> <span class="o">=</span> <span class="n">TextFileDataset</span><span class="p">(</span><span class="n">lab</span><span class="o">.</span><span class="n">get_data_path</span><span class="p">()</span> <span class="o">/</span> <span class="s1">'tiny_shakespeare.txt'</span><span class="p">,</span> <span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="nb">list</span><span class="p">(</span><span class="n">x</span><span class="p">),</span>
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<span class="lineno">318</span> <span class="n">url</span><span class="o">=</span><span class="s1">'https://raw.githubusercontent.com/karpathy/char-rnn/master/data/tinyshakespeare/input.txt'</span><span class="p">)</span>
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|
<span class="lineno">319</span>
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<span class="lineno">320</span>
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<span class="lineno">321</span><span class="k">if</span> <span class="vm">__name__</span> <span class="o">==</span> <span class="s1">'__main__'</span><span class="p">:</span>
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<span class="lineno">322</span> <span class="n">_test_tiny_shakespeare</span><span class="p">()</span></pre></div>
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</div>
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</div>
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<div class='footer'>
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<a href="https://labml.ai">labml.ai</a>
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</div>
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</div>
|
|
<script src=../interactive.js?v=1"></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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|
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for (var i = 0; i < images.length; ++i) {
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|
handleImage(images[i])
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|
}
|
|
}
|
|
|
|
function handleImage(img) {
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|
img.parentElement.style.textAlign = 'center'
|
|
|
|
var modal = document.createElement('div')
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|
modal.id = 'modal'
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|
|
|
var modalContent = document.createElement('div')
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|
modal.appendChild(modalContent)
|
|
|
|
var modalImage = document.createElement('img')
|
|
modalContent.appendChild(modalImage)
|
|
|
|
var span = document.createElement('span')
|
|
span.classList.add('close')
|
|
span.textContent = 'x'
|
|
modal.appendChild(span)
|
|
|
|
img.onclick = function () {
|
|
console.log('clicked')
|
|
document.body.appendChild(modal)
|
|
modalImage.src = img.src
|
|
}
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|
|
|
span.onclick = function () {
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|
document.body.removeChild(modal)
|
|
}
|
|
}
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|
|
|
handleImages()
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|
</script>
|
|
</body>
|
|
</html> |