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<h1>GPT</h1>
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<p>This is a tutorial/implementation of
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<a href="https://openai.com/blog/better-language-models/">OpenAI GPT architecture</a>
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in <a href="https://pytorch.org">PyTorch</a>.
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We got a bunch of implementation details from
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<a href="https://github.com/karpathy/minGPT">minGPT</a>
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by <a href="https://twitter.com/karpathy">@karpathy</a>.
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This implementation also uses character tiny shakespeare dataset.</p>
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<p>GPT model is essentially a standard transformer with a few tweaks.
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GPT-2 and especially GPT-3 models are quite large and won’t fit on a
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single GPU and will need model parallelism.
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This implementation doesn’t even use data parallelism and is intended to be
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more of a tutorial.</p>
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<p>Main differences of this compared to a simple autoregressive transformer
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are the parameter initialization, weight decay, and learning rate schedule.
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For the transformer we reuse the
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<a href="../transformers/index.html">existing labml/nn transformer implementation</a>.</p>
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<p>Here’s a notebook for training a GPT model on Tiny Shakespeare dataset.</p>
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<p><a href="https://colab.research.google.com/github/lab-ml/nn/blob/master/labml_nn/transformers/gpt/experiment.ipynb"><img alt="Open In Colab" src="https://colab.research.google.com/assets/colab-badge.svg" /></a>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">35</span><span></span><span class="kn">import</span> <span class="nn">torch</span>
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<span class="lineno">36</span><span class="kn">from</span> <span class="nn">torch</span> <span class="kn">import</span> <span class="n">nn</span>
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<span class="lineno">37</span>
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<span class="lineno">38</span><span class="kn">from</span> <span class="nn">labml</span> <span class="kn">import</span> <span class="n">experiment</span>
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<span class="lineno">39</span><span class="kn">from</span> <span class="nn">labml.configs</span> <span class="kn">import</span> <span class="n">option</span>
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<span class="lineno">40</span><span class="kn">from</span> <span class="nn">labml_helpers.module</span> <span class="kn">import</span> <span class="n">Module</span>
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<span class="lineno">41</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>
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<span class="lineno">42</span><span class="kn">from</span> <span class="nn">labml_nn.optimizers.configs</span> <span class="kn">import</span> <span class="n">OptimizerConfigs</span>
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<span class="lineno">43</span><span class="kn">from</span> <span class="nn">labml_nn.transformers</span> <span class="kn">import</span> <span class="n">TransformerConfigs</span><span class="p">,</span> <span class="n">Encoder</span>
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<span class="lineno">44</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>
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</div>
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</div>
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<div class='section' id='section-1'>
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<div class='docs doc-strings'>
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<div class='section-link'>
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<a href='#section-1'>#</a>
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</div>
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<h2>GPT model</h2>
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<p>This consists of a token embedding layer, transformer encoder, and
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a final linear layer that gives token logits.</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">47</span><span class="k">class</span> <span class="nc">GPT</span><span class="p">(</span><span class="n">Module</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-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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<ul>
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<li><code>encoder</code> is the transformer <a href="../models.html#Encoder">Encoder</a></li>
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<li><code>src_embed</code> is the token
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<a href="../models.html#EmbeddingsWithLearnedPositionalEncoding">embedding module (with positional encodings)</a></li>
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<li><code>generator</code> is the <a href="../models.html#Generator">final fully connected layer</a> that gives the logits.</li>
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</ul>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">55</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">encoder</span><span class="p">:</span> <span class="n">Encoder</span><span class="p">,</span> <span class="n">src_embed</span><span class="p">:</span> <span class="n">Module</span><span class="p">,</span> <span class="n">generator</span><span class="p">:</span> <span class="n">Module</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>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">62</span> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span>
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<span class="lineno">63</span> <span class="bp">self</span><span class="o">.</span><span class="n">src_embed</span> <span class="o">=</span> <span class="n">src_embed</span>
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<span class="lineno">64</span> <span class="bp">self</span><span class="o">.</span><span class="n">encoder</span> <span class="o">=</span> <span class="n">encoder</span>
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<span class="lineno">65</span> <span class="bp">self</span><span class="o">.</span><span class="n">generator</span> <span class="o">=</span> <span class="n">generator</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'>
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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>The mask will be initialized on the first call</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">68</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>
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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>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">70</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>
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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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<p>Create subsequent mask if mask is not initialized
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or if the size of the mask is different</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">73</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>
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</div>
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</div>
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<div class='section' id='section-7'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-7'>#</a>
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</div>
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<p>Subsequent mask, will mask out tokens from seeing future tokens</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">75</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>
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</div>
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</div>
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<div class='section' id='section-8'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-8'>#</a>
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</div>
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<p>Get the token embeddings with positional encodings</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">77</span> <span class="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">src_embed</span><span class="p">(</span><span class="n">x</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-9'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-9'>#</a>
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</div>
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<p>Transformer encoder</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">79</span> <span class="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">encoder</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">mask</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-10'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-10'>#</a>
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</div>
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<p>Get logits</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">81</span> <span class="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">generator</span><span class="p">(</span><span class="n">x</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-11'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-11'>#</a>
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</div>
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<p>Return results
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(second value is for state, since our trainer is used with RNNs also)</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">85</span> <span class="k">return</span> <span class="n">x</span><span class="p">,</span> <span class="kc">None</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-12'>
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<div class='docs doc-strings'>
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<div class='section-link'>
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<a href='#section-12'>#</a>
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</div>
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<h2>Configurations</h2>
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<p>This inherits from
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<a href="../../experiments/nlp_autoregression.html#NLPAutoRegressionConfigs"><code>NLPAutoRegressionConfigs</code></a></p>
|
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">88</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>
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</div>
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</div>
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<div class='section' id='section-13'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-13'>#</a>
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</div>
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<p>GPT model</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">97</span> <span class="n">model</span><span class="p">:</span> <span class="n">GPT</span></pre></div>
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</div>
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</div>
|
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<div class='section' id='section-14'>
|
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<div class='docs'>
|
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<div class='section-link'>
|
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<a href='#section-14'>#</a>
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</div>
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<p>Transformer</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">99</span> <span class="n">transformer</span><span class="p">:</span> <span class="n">TransformerConfigs</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-15'>
|
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<div class='docs'>
|
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<div class='section-link'>
|
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<a href='#section-15'>#</a>
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</div>
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<p>Weight decay</p>
|
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</div>
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<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">101</span> <span class="n">weight_decay</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.1</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-16'>
|
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-16'>#</a>
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</div>
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<p>Number of tokens for wamup</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">103</span> <span class="n">warmup_steps</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">128</span> <span class="o">*</span> <span class="mi">128</span> <span class="o">*</span> <span class="mi">20</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-17'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-17'>#</a>
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</div>
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<p>Custom optimizer</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">106</span> <span class="n">optimizer</span> <span class="o">=</span> <span class="s1">'transformer_optimizer'</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-18'>
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<div class='docs doc-strings'>
|
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<div class='section-link'>
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<a href='#section-18'>#</a>
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</div>
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<h3>Transformer configurations</h3>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">109</span><span class="nd">@option</span><span class="p">(</span><span class="n">Configs</span><span class="o">.</span><span class="n">transformer</span><span class="p">,</span> <span class="s1">'GPT'</span><span class="p">)</span>
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<span class="lineno">110</span><span class="k">def</span> <span class="nf">_transformer_configs</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>
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</div>
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</div>
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<div class='section' id='section-19'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-19'>#</a>
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</div>
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<p>We use our
|
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<a href="../configs.html#TransformerConfigs">configurable transformer implementation</a></p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">117</span> <span class="n">conf</span> <span class="o">=</span> <span class="n">TransformerConfigs</span><span class="p">()</span></pre></div>
|
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</div>
|
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</div>
|
|
<div class='section' id='section-20'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-20'>#</a>
|
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</div>
|
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<p>Set the vocabulary sizes for embeddings and generating logits</p>
|
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</div>
|
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<div class='code'>
|
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<div class="highlight"><pre><span class="lineno">119</span> <span class="n">conf</span><span class="o">.</span><span class="n">n_src_vocab</span> <span class="o">=</span> <span class="n">c</span><span class="o">.</span><span class="n">n_tokens</span>
|
|
<span class="lineno">120</span> <span class="n">conf</span><span class="o">.</span><span class="n">n_tgt_vocab</span> <span class="o">=</span> <span class="n">c</span><span class="o">.</span><span class="n">n_tokens</span></pre></div>
|
|
</div>
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|
</div>
|
|
<div class='section' id='section-21'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-21'>#</a>
|
|
</div>
|
|
<p>GPT uses GELU activation for position wise feedforward</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">122</span> <span class="n">conf</span><span class="o">.</span><span class="n">ffn</span><span class="o">.</span><span class="n">activation</span> <span class="o">=</span> <span class="s1">'GELU'</span></pre></div>
|
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</div>
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</div>
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<div class='section' id='section-22'>
|
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<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-22'>#</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">125</span> <span class="k">return</span> <span class="n">conf</span></pre></div>
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</div>
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</div>
|
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<div class='section' id='section-23'>
|
|
<div class='docs doc-strings'>
|
|
<div class='section-link'>
|
|
<a href='#section-23'>#</a>
|
|
</div>
|
|
<h3>Initialize weights</h3>
|
|
<p>Weights of linear layers and embedding layers are initialized
|
|
to $\mathcal{N}(0, 0.02)$
|
|
instead of the default Xavier initialzation.</p>
|
|
</div>
|
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<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">128</span><span class="k">def</span> <span class="nf">_init_weights</span><span class="p">(</span><span class="n">module</span><span class="p">):</span></pre></div>
|
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</div>
|
|
</div>
|
|
<div class='section' id='section-24'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-24'>#</a>
|
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</div>
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|
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</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">137</span> <span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">module</span><span class="p">,</span> <span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">,</span> <span class="n">nn</span><span class="o">.</span><span class="n">Embedding</span><span class="p">)):</span>
|
|
<span class="lineno">138</span> <span class="k">return</span>
|
|
<span class="lineno">139</span>
|
|
<span class="lineno">140</span> <span class="n">module</span><span class="o">.</span><span class="n">weight</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">normal_</span><span class="p">(</span><span class="n">mean</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">std</span><span class="o">=</span><span class="mf">0.02</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>Initialize biases to $0$</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">143</span> <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">module</span><span class="p">,</span> <span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">)</span> <span class="ow">and</span> <span class="n">module</span><span class="o">.</span><span class="n">bias</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
|
<span class="lineno">144</span> <span class="n">module</span><span class="o">.</span><span class="n">bias</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">zero_</span><span class="p">()</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>
|
|
<p>Create GPT model and initialize weights</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">147</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">148</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-27'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-27'>#</a>
|
|
</div>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">152</span> <span class="n">m</span> <span class="o">=</span> <span class="n">GPT</span><span class="p">(</span><span class="n">c</span><span class="o">.</span><span class="n">transformer</span><span class="o">.</span><span class="n">encoder</span><span class="p">,</span>
|
|
<span class="lineno">153</span> <span class="n">c</span><span class="o">.</span><span class="n">transformer</span><span class="o">.</span><span class="n">src_embed</span><span class="p">,</span>
|
|
<span class="lineno">154</span> <span class="n">c</span><span class="o">.</span><span class="n">transformer</span><span class="o">.</span><span class="n">generator</span><span class="p">)</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-28'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-28'>#</a>
|
|
</div>
|
|
<p>Apply custom weight initialization</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">157</span> <span class="n">m</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">_init_weights</span><span class="p">)</span>
|
|
<span class="lineno">158</span>
|
|
<span class="lineno">159</span> <span class="k">return</span> <span class="n">m</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-29'>
|
|
<div class='docs doc-strings'>
|
|
<div class='section-link'>
|
|
<a href='#section-29'>#</a>
|
|
</div>
|
|
<h3>Create custom optimizer with weight decay</h3>
|
|
<p>This code is taken from <a href="https://github.com/karpathy/minGPT">minGPT</a>.
|
|
This applies weight decay only to weights of linear layers.</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">162</span><span class="nd">@option</span><span class="p">(</span><span class="n">NLPAutoRegressionConfigs</span><span class="o">.</span><span class="n">optimizer</span><span class="p">)</span>
|
|
<span class="lineno">163</span><span class="k">def</span> <span class="nf">transformer_optimizer</span><span class="p">(</span><span class="n">c</span><span class="p">:</span> <span class="n">NLPAutoRegressionConfigs</span><span class="p">):</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>Collect names of parameters to apply weight decay</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">171</span> <span class="n">decay</span> <span class="o">=</span> <span class="nb">set</span><span class="p">()</span>
|
|
<span class="lineno">172</span> <span class="k">for</span> <span class="n">mn</span><span class="p">,</span> <span class="n">m</span> <span class="ow">in</span> <span class="n">c</span><span class="o">.</span><span class="n">model</span><span class="o">.</span><span class="n">named_modules</span><span class="p">():</span>
|
|
<span class="lineno">173</span> <span class="k">for</span> <span class="n">pn</span><span class="p">,</span> <span class="n">p</span> <span class="ow">in</span> <span class="n">m</span><span class="o">.</span><span class="n">named_parameters</span><span class="p">():</span>
|
|
<span class="lineno">174</span> <span class="n">fpn</span> <span class="o">=</span> <span class="sa">f</span><span class="s1">'</span><span class="si">{</span><span class="n">mn</span><span class="si">}</span><span class="s1">.</span><span class="si">{</span><span class="n">pn</span><span class="si">}</span><span class="s1">'</span> <span class="k">if</span> <span class="n">mn</span> <span class="k">else</span> <span class="n">pn</span> <span class="c1"># full param name</span>
|
|
<span class="lineno">175</span>
|
|
<span class="lineno">176</span> <span class="k">if</span> <span class="n">fpn</span><span class="o">.</span><span class="n">endswith</span><span class="p">(</span><span class="s1">'weight'</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">m</span><span class="p">,</span> <span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">):</span>
|
|
<span class="lineno">177</span> <span class="n">decay</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">fpn</span><span class="p">)</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>Get all the parameters</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">180</span> <span class="n">param_dict</span> <span class="o">=</span> <span class="p">{</span><span class="n">pn</span><span class="p">:</span> <span class="n">p</span> <span class="k">for</span> <span class="n">pn</span><span class="p">,</span> <span class="n">p</span> <span class="ow">in</span> <span class="n">c</span><span class="o">.</span><span class="n">model</span><span class="o">.</span><span class="n">named_parameters</span><span class="p">()}</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>Parameters that are not decayed</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">182</span> <span class="n">no_decay</span> <span class="o">=</span> <span class="nb">set</span><span class="p">(</span><span class="n">param_dict</span><span class="o">.</span><span class="n">keys</span><span class="p">())</span> <span class="o">-</span> <span class="n">decay</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>create the pytorch optimizer object</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">185</span> <span class="n">opt_groups</span> <span class="o">=</span> <span class="p">[</span>
|
|
<span class="lineno">186</span> <span class="p">{</span><span class="s2">"params"</span><span class="p">:</span> <span class="p">[</span><span class="n">param_dict</span><span class="p">[</span><span class="n">pn</span><span class="p">]</span> <span class="k">for</span> <span class="n">pn</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="n">decay</span><span class="p">))],</span> <span class="s2">"weight_decay"</span><span class="p">:</span> <span class="n">c</span><span class="o">.</span><span class="n">weight_decay</span><span class="p">},</span>
|
|
<span class="lineno">187</span> <span class="p">{</span><span class="s2">"params"</span><span class="p">:</span> <span class="p">[</span><span class="n">param_dict</span><span class="p">[</span><span class="n">pn</span><span class="p">]</span> <span class="k">for</span> <span class="n">pn</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="n">no_decay</span><span class="p">))],</span> <span class="s2">"weight_decay"</span><span class="p">:</span> <span class="mf">0.0</span><span class="p">},</span>
|
|
<span class="lineno">188</span> <span class="p">]</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>Create a <a href="../optimizers/configs.html#OptimizerConfigs">configurable optimizer</a>,
|
|
so that we can change these simply by passing
|
|
a config dictionary.</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">193</span> <span class="n">optimizer</span> <span class="o">=</span> <span class="n">OptimizerConfigs</span><span class="p">()</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-35'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-35'>#</a>
|
|
</div>
|
|
<p>Set parameter groups for optimization.</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">196</span> <span class="n">optimizer</span><span class="o">.</span><span class="n">parameters</span> <span class="o">=</span> <span class="n">opt_groups</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>Use <a href="../optimizers/adam_warmup_cosine_decay.html">cosine decay optimizer</a>.
|
|
This is what GPT uses.</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">199</span> <span class="n">optimizer</span><span class="o">.</span><span class="n">optimizer</span> <span class="o">=</span> <span class="s1">'AdamWarmupCosineDecay'</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>Set model embedding size, required if we use <a href="../optimizers/noam.html">Noam optimizer</a>
|
|
which has an exponential decay.</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">202</span> <span class="n">optimizer</span><span class="o">.</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></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-38'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-38'>#</a>
|
|
</div>
|
|
<p>Set default weight decay.
|
|
This is not required since we set the weight decay in the parameter groups.</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">205</span> <span class="n">optimizer</span><span class="o">.</span><span class="n">weight_decay</span> <span class="o">=</span> <span class="n">c</span><span class="o">.</span><span class="n">weight_decay</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-39'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-39'>#</a>
|
|
</div>
|
|
<p>GPT uses a maximum learning rate of $6 \times 10^{-4}$.</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">207</span> <span class="n">optimizer</span><span class="o">.</span><span class="n">learning_rate</span> <span class="o">=</span> <span class="mf">6e-4</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>$\beta_1 = 0.9, \beta_2 = 0.95$</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">209</span> <span class="n">optimizer</span><span class="o">.</span><span class="n">betas</span> <span class="o">=</span> <span class="p">(</span><span class="mf">0.9</span><span class="p">,</span> <span class="mf">0.95</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>$\epsilon = 10^{-8}$</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">211</span> <span class="n">optimizer</span><span class="o">.</span><span class="n">eps</span> <span class="o">=</span> <span class="mf">1e-8</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>Weight decay is decoupled from gradients</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">213</span> <span class="n">optimizer</span><span class="o">.</span><span class="n">weight_decouple</span> <span class="o">=</span> <span class="kc">True</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-43'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
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<a href='#section-43'>#</a>
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</div>
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<p>Total number of optimization steps for learning rate cosine decay</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">215</span> <span class="n">optimizer</span><span class="o">.</span><span class="n">total_steps</span> <span class="o">=</span> <span class="n">c</span><span class="o">.</span><span class="n">epochs</span> <span class="o">*</span> <span class="nb">len</span><span class="p">(</span><span class="n">c</span><span class="o">.</span><span class="n">text</span><span class="o">.</span><span class="n">train</span><span class="p">)</span> <span class="o">//</span> <span class="p">(</span><span class="n">c</span><span class="o">.</span><span class="n">batch_size</span> <span class="o">*</span> <span class="n">c</span><span class="o">.</span><span class="n">seq_len</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-44'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-44'>#</a>
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</div>
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<p>Number of warmup optimization steps</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">217</span> <span class="n">optimizer</span><span class="o">.</span><span class="n">warmup</span> <span class="o">=</span> <span class="n">c</span><span class="o">.</span><span class="n">warmup_steps</span> <span class="o">//</span> <span class="p">(</span><span class="n">c</span><span class="o">.</span><span class="n">batch_size</span> <span class="o">*</span> <span class="n">c</span><span class="o">.</span><span class="n">seq_len</span><span class="p">)</span>
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<span class="lineno">218</span>
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<span class="lineno">219</span> <span class="k">return</span> <span class="n">optimizer</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-45'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-45'>#</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">222</span><span class="k">def</span> <span class="nf">main</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-46'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-46'>#</a>
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</div>
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<p>Create experiment</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">224</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">"gpt"</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-47'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-47'>#</a>
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</div>
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<p>Create configs</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">226</span> <span class="n">conf</span> <span class="o">=</span> <span class="n">Configs</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-48'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-48'>#</a>
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</div>
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<p>Override configurations</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">228</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>
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</div>
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</div>
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<div class='section' id='section-49'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-49'>#</a>
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</div>
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<p>Use character level tokenizer</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">230</span> <span class="s1">'tokenizer'</span><span class="p">:</span> <span class="s1">'character'</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-50'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-50'>#</a>
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</div>
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<p>Prompt separator is blank</p>
|
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">232</span> <span class="s1">'prompt_separator'</span><span class="p">:</span> <span class="s1">''</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-51'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-51'>#</a>
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</div>
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<p>Starting prompt for sampling</p>
|
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">234</span> <span class="s1">'prompt'</span><span class="p">:</span> <span class="s1">'It is '</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-52'>
|
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-52'>#</a>
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</div>
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|
<p>Use Tiny Shakespeare dataset</p>
|
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</div>
|
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<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">236</span> <span class="s1">'text'</span><span class="p">:</span> <span class="s1">'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='section' id='section-53'>
|
|
<div class='docs'>
|
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<div class='section-link'>
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<a href='#section-53'>#</a>
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</div>
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<p>Use a context size of $128$</p>
|
|
</div>
|
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<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">239</span> <span class="s1">'seq_len'</span><span class="p">:</span> <span class="mi">128</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-54'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-54'>#</a>
|
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</div>
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<p>Train for $32$ epochs</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">241</span> <span class="s1">'epochs'</span><span class="p">:</span> <span class="mi">32</span><span class="p">,</span></pre></div>
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</div>
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</div>
|
|
<div class='section' id='section-55'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-55'>#</a>
|
|
</div>
|
|
<p>Batch size $128$</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">243</span> <span class="s1">'batch_size'</span><span class="p">:</span> <span class="mi">128</span><span class="p">,</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-56'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-56'>#</a>
|
|
</div>
|
|
<p>Switch between training and validation for $10$ times
|
|
per epoch</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">246</span> <span class="s1">'inner_iterations'</span><span class="p">:</span> <span class="mi">10</span><span class="p">,</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-57'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-57'>#</a>
|
|
</div>
|
|
<p>Transformer configurations</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">249</span> <span class="s1">'transformer.d_model'</span><span class="p">:</span> <span class="mi">512</span><span class="p">,</span>
|
|
<span class="lineno">250</span> <span class="s1">'transformer.ffn.d_ff'</span><span class="p">:</span> <span class="mi">2048</span><span class="p">,</span>
|
|
<span class="lineno">251</span> <span class="s1">'transformer.n_heads'</span><span class="p">:</span> <span class="mi">8</span><span class="p">,</span>
|
|
<span class="lineno">252</span> <span class="s1">'transformer.n_layers'</span><span class="p">:</span> <span class="mi">6</span>
|
|
<span class="lineno">253</span> <span class="p">})</span></pre></div>
|
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</div>
|
|
</div>
|
|
<div class='section' id='section-58'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-58'>#</a>
|
|
</div>
|
|
<p>Set models for saving and loading</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">256</span> <span class="n">experiment</span><span class="o">.</span><span class="n">add_pytorch_models</span><span class="p">({</span><span class="s1">'model'</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>
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</div>
|
|
<div class='section' id='section-59'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-59'>#</a>
|
|
</div>
|
|
<p>Start the experiment</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">259</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-60'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-60'>#</a>
|
|
</div>
|
|
<p>Run training</p>
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">261</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>
|
|
</div>
|
|
<div class='section' id='section-61'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-61'>#</a>
|
|
</div>
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|
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|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">265</span><span class="k">if</span> <span class="vm">__name__</span> <span class="o">==</span> <span class="s1">'__main__'</span><span class="p">:</span>
|
|
<span class="lineno">266</span> <span class="n">main</span><span class="p">()</span></pre></div>
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