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<h1><a href="index.html">Fuzzy Tiling Activation</a> Experiment</h1>
<p><a href="https://colab.research.google.com/github/labmlai/annotated_deep_learning_paper_implementations/blob/master/labml_nn/activations/fta/experiment.ipynb"><img alt="Open In Colab" src="https://colab.research.google.com/assets/colab-badge.svg"></a></p>
<p>Here we train a transformer that uses <a href="index.html">Fuzzy Tiling Activation</a> in the <a href="../../transformers/feed_forward.html">Feed-Forward Network</a>. We use it for a language model and train it on Tiny Shakespeare dataset for demonstration.</p>
<p>However, this is probably not the ideal task for FTA, and we believe FTA is more suitable for modeling data with continuous variables.</p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">21</span><span></span><span class="kn">import</span> <span class="nn">copy</span>
<span class="lineno">22</span>
<span class="lineno">23</span><span class="kn">import</span> <span class="nn">torch</span>
<span class="lineno">24</span><span class="kn">import</span> <span class="nn">torch.nn</span> <span class="k">as</span> <span class="nn">nn</span>
<span class="lineno">25</span>
<span class="lineno">26</span><span class="kn">from</span> <span class="nn">labml</span> <span class="kn">import</span> <span class="n">experiment</span>
<span class="lineno">27</span><span class="kn">from</span> <span class="nn">labml.configs</span> <span class="kn">import</span> <span class="n">option</span>
<span class="lineno">28</span><span class="kn">from</span> <span class="nn">labml_nn.activations.fta</span> <span class="kn">import</span> <span class="n">FTA</span>
<span class="lineno">29</span><span class="kn">from</span> <span class="nn">labml_nn.experiments.nlp_autoregression</span> <span class="kn">import</span> <span class="n">NLPAutoRegressionConfigs</span>
<span class="lineno">30</span><span class="kn">from</span> <span class="nn">labml_nn.transformers</span> <span class="kn">import</span> <span class="n">MultiHeadAttention</span><span class="p">,</span> <span class="n">TransformerLayer</span>
<span class="lineno">31</span><span class="kn">from</span> <span class="nn">labml_nn.transformers.utils</span> <span class="kn">import</span> <span class="n">subsequent_mask</span></pre></div>
</div>
</div>
<div class='section' id='section-1'>
<div class='docs doc-strings'>
<div class='section-link'>
<a href='#section-1'>#</a>
</div>
<h2>FFN module with <a href="index.html">FTA</a> activation</h2>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">34</span><span class="k">class</span> <span class="nc">FeedForwardFTA</span><span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">Module</span><span class="p">):</span></pre></div>
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<div class='docs doc-strings'>
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<a href='#section-2'>#</a>
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<ul><li><code class="highlight"><span></span><span class="n">d_model</span></code>
is the number of features in a token embedding </li>
<li><code class="highlight"><span></span><span class="n">d_ff</span></code>
is the number of features in the hidden layer of the FFN </li>
<li><code class="highlight"><span></span><span class="n">activation</span></code>
is FTA activation module </li>
<li><code class="highlight"><span></span><span class="n">dropout</span></code>
is dropout probability for the hidden layer</li></ul>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">39</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">d_model</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">d_ff</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span>
<span class="lineno">40</span> <span class="n">activation</span><span class="p">:</span> <span class="n">FTA</span><span class="p">,</span>
<span class="lineno">41</span> <span class="n">dropout</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.1</span><span class="p">):</span></pre></div>
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<a href='#section-3'>#</a>
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<div class='code'>
<div class="highlight"><pre><span class="lineno">48</span> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span></pre></div>
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<p>Layer one parameterized by weight <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.83333em;vertical-align:-0.15em;"></span><span class="mord coloredeq eqe" style=""><span class="mord" style=""><span class="mord mathnormal" style="margin-right:0.13889em">W</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.30110799999999993em;"><span style="top:-2.5500000000000003em;margin-left:-0.13889em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight" style=""><span class="mord mtight" style="">1</span></span></span></span><span class="vlist-s">​</span></span><span class="vlist-r"><span class="vlist" style="height:0.15em;"><span></span></span></span></span></span></span></span></span></span></span></span> and bias <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.84444em;vertical-align:-0.15em;"></span><span class="mord coloredeq eqf" style=""><span class="mord" style=""><span class="mord mathnormal" style="">b</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.30110799999999993em;"><span style="top:-2.5500000000000003em;margin-left:0em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight" style=""><span class="mord mtight" style="">1</span></span></span></span><span class="vlist-s">​</span></span><span class="vlist-r"><span class="vlist" style="height:0.15em;"><span></span></span></span></span></span></span></span></span></span></span></span> </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">50</span> <span class="bp">self</span><span class="o">.</span><span class="n">layer1</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="n">d_model</span><span class="p">,</span> <span class="n">d_ff</span><span class="p">)</span></pre></div>
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<p>Layer two parameterized by weight <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.83333em;vertical-align:-0.15em;"></span><span class="mord coloredeq eqe" style=""><span class="mord" style=""><span class="mord mathnormal" style="margin-right:0.13889em">W</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.30110799999999993em;"><span style="top:-2.5500000000000003em;margin-left:-0.13889em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight" style=""><span class="mord mtight" style="">1</span></span></span></span><span class="vlist-s">​</span></span><span class="vlist-r"><span class="vlist" style="height:0.15em;"><span></span></span></span></span></span></span></span></span></span></span></span> and bias <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.84444em;vertical-align:-0.15em;"></span><span class="mord coloredeq eqf" style=""><span class="mord" style=""><span class="mord mathnormal" style="">b</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.30110799999999993em;"><span style="top:-2.5500000000000003em;margin-left:0em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight" style=""><span class="mord mtight" style="">1</span></span></span></span><span class="vlist-s">​</span></span><span class="vlist-r"><span class="vlist" style="height:0.15em;"><span></span></span></span></span></span></span></span></span></span></span></span> </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">52</span> <span class="bp">self</span><span class="o">.</span><span class="n">layer2</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="n">d_ff</span> <span class="o">*</span> <span class="n">activation</span><span class="o">.</span><span class="n">expansion_factor</span><span class="p">,</span> <span class="n">d_model</span><span class="p">)</span></pre></div>
</div>
</div>
<div class='section' id='section-6'>
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<a href='#section-6'>#</a>
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<p>Hidden layer dropout </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">54</span> <span class="bp">self</span><span class="o">.</span><span class="n">dropout</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Dropout</span><span class="p">(</span><span class="n">dropout</span><span class="p">)</span></pre></div>
</div>
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<p>Activation function <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.8888799999999999em;vertical-align:-0.19444em;"></span><span class="mord coloredeq eqi" style=""><span class="mord mathnormal" style="margin-right:0.10764em">f</span></span></span></span></span></span> </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">56</span> <span class="bp">self</span><span class="o">.</span><span class="n">activation</span> <span class="o">=</span> <span class="n">activation</span></pre></div>
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</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">58</span> <span class="k">def</span> <span class="nf">forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">):</span></pre></div>
</div>
</div>
<div class='section' id='section-9'>
<div class='docs'>
<div class='section-link'>
<a href='#section-9'>#</a>
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<p><span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord coloredeq eqi" style=""><span class="mord mathnormal" style="margin-right:0.10764em">f</span></span><span class="mopen">(</span><span class="mord mathnormal">x</span><span class="mord coloredeq eqe" style=""><span class="mord" style=""><span class="mord mathnormal" style="margin-right:0.13889em">W</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.30110799999999993em;"><span style="top:-2.5500000000000003em;margin-left:-0.13889em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight" style=""><span class="mord mtight" style="">1</span></span></span></span><span class="vlist-s">​</span></span><span class="vlist-r"><span class="vlist" style="height:0.15em;"><span></span></span></span></span></span></span></span><span class="mspace" style="margin-right:0.2222222222222222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span></span><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord coloredeq eqf" style=""><span class="mord" style=""><span class="mord mathnormal" style="">b</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.30110799999999993em;"><span style="top:-2.5500000000000003em;margin-left:0em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight" style=""><span class="mord mtight" style="">1</span></span></span></span><span class="vlist-s">​</span></span><span class="vlist-r"><span class="vlist" style="height:0.15em;"><span></span></span></span></span></span></span></span><span class="mclose">)</span></span></span></span></span> </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">60</span> <span class="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">activation</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">layer1</span><span class="p">(</span><span class="n">x</span><span class="p">))</span></pre></div>
</div>
</div>
<div class='section' id='section-10'>
<div class='docs'>
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<a href='#section-10'>#</a>
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<p>Apply dropout </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">62</span> <span class="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">dropout</span><span class="p">(</span><span class="n">x</span><span class="p">)</span></pre></div>
</div>
</div>
<div class='section' id='section-11'>
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<a href='#section-11'>#</a>
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<p> </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">64</span> <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">layer2</span><span class="p">(</span><span class="n">x</span><span class="p">)</span></pre></div>
</div>
</div>
<div class='section' id='section-12'>
<div class='docs doc-strings'>
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<a href='#section-12'>#</a>
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<h2>Auto-Regressive model</h2>
<p>This is an autoregressive transformer model that uses Feed-Forward Networks with (Fuzzy Tiling Activations)(index.html).</p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">67</span><span class="k">class</span> <span class="nc">AutoregressiveTransformer</span><span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">Module</span><span class="p">):</span></pre></div>
</div>
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<div class='section' id='section-13'>
<div class='docs doc-strings'>
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<ul><li><code class="highlight"><span></span><span class="n">n_tokens</span></code>
is the number of tokens in the vocabulary </li>
<li><code class="highlight"><span></span><span class="n">d_model</span></code>
is the embedding size </li>
<li><code class="highlight"><span></span><span class="n">n_layers</span></code>
is the number of transformer layers </li>
<li><code class="highlight"><span></span><span class="n">layer</span></code>
is the layer. We use <code class="highlight"><span></span><span class="n">n_layers</span></code>
copies of this for the transformer.</li></ul>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">75</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">n_tokens</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">d_model</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">n_layers</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">layer</span><span class="p">:</span> <span class="n">TransformerLayer</span><span class="p">):</span></pre></div>
</div>
</div>
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<a href='#section-14'>#</a>
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</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">82</span> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span></pre></div>
</div>
</div>
<div class='section' id='section-15'>
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<a href='#section-15'>#</a>
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<p>Transformer with <code class="highlight"><span></span><span class="n">n_layers</span></code>
layers </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">84</span> <span class="bp">self</span><span class="o">.</span><span class="n">transformer_layers</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">ModuleList</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">layer</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_layers</span><span class="p">)])</span></pre></div>
</div>
</div>
<div class='section' id='section-16'>
<div class='docs'>
<div class='section-link'>
<a href='#section-16'>#</a>
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<p>Token embedding layer </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">87</span> <span class="bp">self</span><span class="o">.</span><span class="n">emb</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Embedding</span><span class="p">(</span><span class="n">n_tokens</span><span class="p">,</span> <span class="n">d_model</span><span class="p">)</span></pre></div>
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<div class='section' id='section-17'>
<div class='docs'>
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<a href='#section-17'>#</a>
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<p>Readout layer </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">89</span> <span class="bp">self</span><span class="o">.</span><span class="n">readout</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="n">d_model</span><span class="p">,</span> <span class="n">n_tokens</span><span class="p">)</span></pre></div>
</div>
</div>
<div class='section' id='section-18'>
<div class='docs'>
<div class='section-link'>
<a href='#section-18'>#</a>
</div>
<p>The mask will be initialized on the first call </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">92</span> <span class="bp">self</span><span class="o">.</span><span class="n">mask</span> <span class="o">=</span> <span class="kc">None</span></pre></div>
</div>
</div>
<div class='section' id='section-19'>
<div class='docs doc-strings'>
<div class='section-link'>
<a href='#section-19'>#</a>
</div>
<ul><li><code class="highlight"><span></span><span class="n">x</span></code>
are the input tokens of shape <code class="highlight"><span></span><span class="p">[</span><span class="n">seq_len</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">]</span></code>
</li></ul>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">94</span> <span class="k">def</span> <span class="nf">forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">):</span></pre></div>
</div>
</div>
<div class='section' id='section-20'>
<div class='docs'>
<div class='section-link'>
<a href='#section-20'>#</a>
</div>
<p>Create auto-regressive mask </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">99</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">mask</span> <span class="ow">is</span> <span class="kc">None</span> <span class="ow">or</span> <span class="bp">self</span><span class="o">.</span><span class="n">mask</span><span class="o">.</span><span class="n">size</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span> <span class="o">!=</span> <span class="nb">len</span><span class="p">(</span><span class="n">x</span><span class="p">):</span></pre></div>
</div>
</div>
<div class='section' id='section-21'>
<div class='docs'>
<div class='section-link'>
<a href='#section-21'>#</a>
</div>
<p>Subsequent mask, will mask out tokens from seeing future tokens </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">101</span> <span class="bp">self</span><span class="o">.</span><span class="n">mask</span> <span class="o">=</span> <span class="n">subsequent_mask</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">x</span><span class="p">))</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">x</span><span class="o">.</span><span class="n">device</span><span class="p">)</span></pre></div>
</div>
</div>
<div class='section' id='section-22'>
<div class='docs'>
<div class='section-link'>
<a href='#section-22'>#</a>
</div>
<p>Get the token embeddings </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">104</span> <span class="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">emb</span><span class="p">(</span><span class="n">x</span><span class="p">)</span></pre></div>
</div>
</div>
<div class='section' id='section-23'>
<div class='docs'>
<div class='section-link'>
<a href='#section-23'>#</a>
</div>
<p>Transformer encoder </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">106</span> <span class="k">for</span> <span class="n">layer</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">transformer_layers</span><span class="p">:</span>
<span class="lineno">107</span> <span class="n">x</span> <span class="o">=</span> <span class="n">layer</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="n">x</span><span class="p">,</span> <span class="n">mask</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">mask</span><span class="p">)</span></pre></div>
</div>
</div>
<div class='section' id='section-24'>
<div class='docs'>
<div class='section-link'>
<a href='#section-24'>#</a>
</div>
<p>Get logits </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">109</span> <span class="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">readout</span><span class="p">(</span><span class="n">x</span><span class="p">)</span></pre></div>
</div>
</div>
<div class='section' id='section-25'>
<div class='docs'>
<div class='section-link'>
<a href='#section-25'>#</a>
</div>
<p>Return results </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">112</span> <span class="k">return</span> <span class="n">x</span><span class="p">,</span> <span class="kc">None</span></pre></div>
</div>
</div>
<div class='section' id='section-26'>
<div class='docs doc-strings'>
<div class='section-link'>
<a href='#section-26'>#</a>
</div>
<h2>Configurations</h2>
<p>This inherits from <a href="../../experiments/nlp_autoregression.html#NLPAutoRegressionConfigs"><code class="highlight"><span></span><span class="n">NLPAutoRegressionConfigs</span></code>
</a></p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">115</span><span class="k">class</span> <span class="nc">Configs</span><span class="p">(</span><span class="n">NLPAutoRegressionConfigs</span><span class="p">):</span></pre></div>
</div>
</div>
<div class='section' id='section-27'>
<div class='docs'>
<div class='section-link'>
<a href='#section-27'>#</a>
</div>
<p>Model </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">124</span> <span class="n">model</span><span class="p">:</span> <span class="n">AutoregressiveTransformer</span></pre></div>
</div>
</div>
<div class='section' id='section-28'>
<div class='docs'>
<div class='section-link'>
<a href='#section-28'>#</a>
</div>
<p>Number of layers </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">127</span> <span class="n">n_layers</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">4</span></pre></div>
</div>
</div>
<div class='section' id='section-29'>
<div class='docs'>
<div class='section-link'>
<a href='#section-29'>#</a>
</div>
<p><span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.43056em;vertical-align:0em;"></span><span class="mord mathnormal" style="margin-right:0.0037em;">α</span></span></span></span></span> and <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.8888799999999999em;vertical-align:-0.19444em;"></span><span class="mord mathnormal" style="margin-right:0.05278em;">β</span></span></span></span></span> for DeepNorm </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">130</span> <span class="n">deep_norm_alpha</span><span class="p">:</span> <span class="nb">float</span>
<span class="lineno">131</span> <span class="n">deep_norm_beta</span><span class="p">:</span> <span class="nb">float</span></pre></div>
</div>
</div>
<div class='section' id='section-30'>
<div class='docs'>
<div class='section-link'>
<a href='#section-30'>#</a>
</div>
<p>Number of heads in the attention </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">134</span> <span class="n">n_heads</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">4</span></pre></div>
</div>
</div>
<div class='section' id='section-31'>
<div class='docs'>
<div class='section-link'>
<a href='#section-31'>#</a>
</div>
<p>Embedding size </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">136</span> <span class="n">d_model</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">256</span></pre></div>
</div>
</div>
<div class='section' id='section-32'>
<div class='docs'>
<div class='section-link'>
<a href='#section-32'>#</a>
</div>
<p>Size of each attention head </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">138</span> <span class="n">d_k</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">16</span></pre></div>
</div>
</div>
<div class='section' id='section-33'>
<div class='docs'>
<div class='section-link'>
<a href='#section-33'>#</a>
</div>
<p>Feed forward layer size </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">140</span> <span class="n">d_ff</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">256</span></pre></div>
</div>
</div>
<div class='section' id='section-34'>
<div class='docs'>
<div class='section-link'>
<a href='#section-34'>#</a>
</div>
<p>FTA </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">143</span> <span class="n">fta_lower_limit</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="o">-</span><span class="mf">1.</span>
<span class="lineno">144</span> <span class="n">fta_upper_limit</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="o">+</span><span class="mf">1.</span>
<span class="lineno">145</span> <span class="n">fta_delta</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.2</span>
<span class="lineno">146</span> <span class="n">fta_eta</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.05</span></pre></div>
</div>
</div>
<div class='section' id='section-35'>
<div class='docs doc-strings'>
<div class='section-link'>
<a href='#section-35'>#</a>
</div>
<h4>Initialize the model</h4>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">149</span><span class="nd">@option</span><span class="p">(</span><span class="n">Configs</span><span class="o">.</span><span class="n">model</span><span class="p">)</span>
<span class="lineno">150</span><span class="k">def</span> <span class="nf">_model</span><span class="p">(</span><span class="n">c</span><span class="p">:</span> <span class="n">Configs</span><span class="p">):</span></pre></div>
</div>
</div>
<div class='section' id='section-36'>
<div class='docs'>
<div class='section-link'>
<a href='#section-36'>#</a>
</div>
<p>Create FTA activation module </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">156</span> <span class="n">fta</span> <span class="o">=</span> <span class="n">FTA</span><span class="p">(</span><span class="n">c</span><span class="o">.</span><span class="n">fta_lower_limit</span><span class="p">,</span> <span class="n">c</span><span class="o">.</span><span class="n">fta_upper_limit</span><span class="p">,</span> <span class="n">c</span><span class="o">.</span><span class="n">fta_delta</span><span class="p">,</span> <span class="n">c</span><span class="o">.</span><span class="n">fta_eta</span><span class="p">)</span></pre></div>
</div>
</div>
<div class='section' id='section-37'>
<div class='docs'>
<div class='section-link'>
<a href='#section-37'>#</a>
</div>
<p>Create the transformer. We re-use <a href="../../transformers/models.html#TransformerLayer"><code class="highlight"><span></span><span class="n">TransformerLayer</span></code>
</a> and <a href="../../transformers/mha.html"><code class="highlight"><span></span><span class="n">MultiHeadAttention</span></code>
</a> implementations. </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">160</span> <span class="n">m</span> <span class="o">=</span> <span class="n">AutoregressiveTransformer</span><span class="p">(</span><span class="n">c</span><span class="o">.</span><span class="n">n_tokens</span><span class="p">,</span> <span class="n">c</span><span class="o">.</span><span class="n">d_model</span><span class="p">,</span> <span class="n">c</span><span class="o">.</span><span class="n">n_layers</span><span class="p">,</span>
<span class="lineno">161</span> <span class="n">TransformerLayer</span><span class="p">(</span><span class="n">d_model</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">d_model</span><span class="p">,</span>
<span class="lineno">162</span> <span class="n">feed_forward</span><span class="o">=</span><span class="n">FeedForwardFTA</span><span class="p">(</span><span class="n">d_model</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">d_model</span><span class="p">,</span>
<span class="lineno">163</span> <span class="n">d_ff</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">d_ff</span><span class="p">,</span>
<span class="lineno">164</span> <span class="n">activation</span><span class="o">=</span><span class="n">fta</span><span class="p">,</span>
<span class="lineno">165</span> <span class="n">dropout</span><span class="o">=</span><span class="mf">0.1</span><span class="p">),</span>
<span class="lineno">166</span> <span class="n">self_attn</span><span class="o">=</span><span class="n">MultiHeadAttention</span><span class="p">(</span><span class="n">c</span><span class="o">.</span><span class="n">n_heads</span><span class="p">,</span> <span class="n">c</span><span class="o">.</span><span class="n">d_model</span><span class="p">,</span>
<span class="lineno">167</span> <span class="n">dropout_prob</span><span class="o">=</span><span class="mf">0.0</span><span class="p">),</span>
<span class="lineno">168</span> <span class="n">dropout_prob</span><span class="o">=</span><span class="mf">0.0</span><span class="p">))</span></pre></div>
</div>
</div>
<div class='section' id='section-38'>
<div class='docs'>
<div class='section-link'>
<a href='#section-38'>#</a>
</div>
<p>Move to the device </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">171</span> <span class="k">return</span> <span class="n">m</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">c</span><span class="o">.</span><span class="n">device</span><span class="p">)</span></pre></div>
</div>
</div>
<div class='section' id='section-39'>
<div class='docs doc-strings'>
<div class='section-link'>
<a href='#section-39'>#</a>
</div>
<h4>Create and run the experiment</h4>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">174</span><span class="k">def</span> <span class="nf">main</span><span class="p">():</span></pre></div>
</div>
</div>
<div class='section' id='section-40'>
<div class='docs'>
<div class='section-link'>
<a href='#section-40'>#</a>
</div>
<p>Create experiment </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">179</span> <span class="n">experiment</span><span class="o">.</span><span class="n">create</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">&quot;fta&quot;</span><span class="p">,</span> <span class="n">writers</span><span class="o">=</span><span class="p">{</span><span class="s1">&#39;screen&#39;</span><span class="p">,</span> <span class="s1">&#39;labml&#39;</span><span class="p">})</span></pre></div>
</div>
</div>
<div class='section' id='section-41'>
<div class='docs'>
<div class='section-link'>
<a href='#section-41'>#</a>
</div>
<p>Create configs </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">181</span> <span class="n">conf</span> <span class="o">=</span> <span class="n">Configs</span><span class="p">()</span></pre></div>
</div>
</div>
<div class='section' id='section-42'>
<div class='docs'>
<div class='section-link'>
<a href='#section-42'>#</a>
</div>
<p>Override configurations </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">183</span> <span class="n">experiment</span><span class="o">.</span><span class="n">configs</span><span class="p">(</span><span class="n">conf</span><span class="p">,</span> <span class="p">{</span></pre></div>
</div>
</div>
<div class='section' id='section-43'>
<div class='docs'>
<div class='section-link'>
<a href='#section-43'>#</a>
</div>
<p>Use character level tokenizer </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">185</span> <span class="s1">&#39;tokenizer&#39;</span><span class="p">:</span> <span class="s1">&#39;character&#39;</span><span class="p">,</span></pre></div>
</div>
</div>
<div class='section' id='section-44'>
<div class='docs'>
<div class='section-link'>
<a href='#section-44'>#</a>
</div>
<p>Prompt separator is blank </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">187</span> <span class="s1">&#39;prompt_separator&#39;</span><span class="p">:</span> <span class="s1">&#39;&#39;</span><span class="p">,</span></pre></div>
</div>
</div>
<div class='section' id='section-45'>
<div class='docs'>
<div class='section-link'>
<a href='#section-45'>#</a>
</div>
<p>Starting prompt for sampling </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">189</span> <span class="s1">&#39;prompt&#39;</span><span class="p">:</span> <span class="s1">&#39;It is &#39;</span><span class="p">,</span></pre></div>
</div>
</div>
<div class='section' id='section-46'>
<div class='docs'>
<div class='section-link'>
<a href='#section-46'>#</a>
</div>
<p>Use Tiny Shakespeare dataset </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">191</span> <span class="s1">&#39;text&#39;</span><span class="p">:</span> <span class="s1">&#39;tiny_shakespeare&#39;</span><span class="p">,</span></pre></div>
</div>
</div>
<div class='section' id='section-47'>
<div class='docs'>
<div class='section-link'>
<a href='#section-47'>#</a>
</div>
<p>Use a context size of <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.64444em;vertical-align:0em;"></span><span class="mord">256</span></span></span></span></span> </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">194</span> <span class="s1">&#39;seq_len&#39;</span><span class="p">:</span> <span class="mi">256</span><span class="p">,</span></pre></div>
</div>
</div>
<div class='section' id='section-48'>
<div class='docs'>
<div class='section-link'>
<a href='#section-48'>#</a>
</div>
<p>Train for 32 epochs </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">196</span> <span class="s1">&#39;epochs&#39;</span><span class="p">:</span> <span class="mi">32</span><span class="p">,</span></pre></div>
</div>
</div>
<div class='section' id='section-49'>
<div class='docs'>
<div class='section-link'>
<a href='#section-49'>#</a>
</div>
<p>Batch size <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.64444em;vertical-align:0em;"></span><span class="mord">16</span></span></span></span></span> </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">198</span> <span class="s1">&#39;batch_size&#39;</span><span class="p">:</span> <span class="mi">16</span><span class="p">,</span></pre></div>
</div>
</div>
<div class='section' id='section-50'>
<div class='docs'>
<div class='section-link'>
<a href='#section-50'>#</a>
</div>
<p>Switch between training and validation for <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.64444em;vertical-align:0em;"></span><span class="mord">10</span></span></span></span></span> times per epoch </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">200</span> <span class="s1">&#39;inner_iterations&#39;</span><span class="p">:</span> <span class="mi">10</span><span class="p">,</span></pre></div>
</div>
</div>
<div class='section' id='section-51'>
<div class='docs'>
<div class='section-link'>
<a href='#section-51'>#</a>
</div>
<p>Adam optimizer with no warmup </p>
</div>
<div class='code'>
<div class="highlight"><pre><span class="lineno">203</span> <span class="s1">&#39;optimizer.optimizer&#39;</span><span class="p">:</span> <span class="s1">&#39;Adam&#39;</span><span class="p">,</span>
<span class="lineno">204</span> <span class="s1">&#39;optimizer.learning_rate&#39;</span><span class="p">:</span> <span class="mf">3e-4</span><span class="p">,</span>
<span class="lineno">205</span> <span class="p">})</span></pre></div>
</div>
</div>
<div class='section' id='section-52'>
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<div class='section-link'>
<a href='#section-52'>#</a>
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<p>Set model(s) for saving and loading </p>
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<div class='code'>
<div class="highlight"><pre><span class="lineno">208</span> <span class="n">experiment</span><span class="o">.</span><span class="n">add_pytorch_models</span><span class="p">({</span><span class="s1">&#39;model&#39;</span><span class="p">:</span> <span class="n">conf</span><span class="o">.</span><span class="n">model</span><span class="p">})</span></pre></div>
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<div class='docs'>
<div class='section-link'>
<a href='#section-53'>#</a>
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<p>Start the experiment </p>
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<div class='code'>
<div class="highlight"><pre><span class="lineno">211</span> <span class="k">with</span> <span class="n">experiment</span><span class="o">.</span><span class="n">start</span><span class="p">():</span></pre></div>
</div>
</div>
<div class='section' id='section-54'>
<div class='docs'>
<div class='section-link'>
<a href='#section-54'>#</a>
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<p>Run training </p>
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<div class='code'>
<div class="highlight"><pre><span class="lineno">213</span> <span class="n">conf</span><span class="o">.</span><span class="n">run</span><span class="p">()</span></pre></div>
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<div class='section' id='section-55'>
<div class='docs'>
<div class='section-link'>
<a href='#section-55'>#</a>
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<p> </p>
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<div class='code'>
<div class="highlight"><pre><span class="lineno">217</span><span class="k">if</span> <span class="vm">__name__</span> <span class="o">==</span> <span class="s1">&#39;__main__&#39;</span><span class="p">:</span>
<span class="lineno">218</span> <span class="n">main</span><span class="p">()</span></pre></div>
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