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<h1>Configurable Optimizer</h1>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">10</span><span></span><span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Tuple</span>
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<span class="lineno">11</span>
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<span class="lineno">12</span><span class="kn">import</span> <span class="nn">torch</span>
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<span class="lineno">13</span>
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<span class="lineno">14</span><span class="kn">from</span> <span class="nn">labml.configs</span> <span class="kn">import</span> <span class="n">BaseConfigs</span><span class="p">,</span> <span class="n">option</span><span class="p">,</span> <span class="n">meta_config</span>
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<span class="lineno">15</span><span class="kn">from</span> <span class="nn">labml_nn.optimizers</span> <span class="kn">import</span> <span class="n">WeightDecay</span></pre></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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<p><a id="OptimizerConfigs"></p>
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<h2>Optimizer Configurations</h2>
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<p></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">18</span><span class="k">class</span> <span class="nc">OptimizerConfigs</span><span class="p">(</span><span class="n">BaseConfigs</span><span class="p">):</span></pre></div>
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<div class='section' id='section-2'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-2'>#</a>
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</div>
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<p>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">26</span> <span class="n">optimizer</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">optim</span><span class="o">.</span><span class="n">Adam</span></pre></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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<p>Weight 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">29</span> <span class="n">weight_decay_obj</span><span class="p">:</span> <span class="n">WeightDecay</span></pre></div>
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</div>
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<div class='section' id='section-4'>
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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>Whether weight decay is decoupled;
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i.e. weight decay is not added to gradients</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">32</span> <span class="n">weight_decouple</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span></pre></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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<p>Weight 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">34</span> <span class="n">weight_decay</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.0</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='section-link'>
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<a href='#section-6'>#</a>
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</div>
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<p>Whether weight decay is absolute or should be multiplied by learning rate</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">36</span> <span class="n">weight_decay_absolute</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-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>Whether the adam update is optimized (different epsilon)</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">39</span> <span class="n">optimized_adam_update</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</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>Parameters to be optimized</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">42</span> <span class="n">parameters</span><span class="p">:</span> <span class="nb">any</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>Learning rate $\alpha$</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">45</span> <span class="n">learning_rate</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.01</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>Beta values $(\beta_1, \beta_2)$ for Adam</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="n">betas</span><span class="p">:</span> <span class="n">Tuple</span><span class="p">[</span><span class="nb">float</span><span class="p">,</span> <span class="nb">float</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span><span class="mf">0.9</span><span class="p">,</span> <span class="mf">0.999</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>Epsilon $\epsilon$ for adam</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">49</span> <span class="n">eps</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">1e-08</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'>
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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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<p>Momentum for SGD</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">52</span> <span class="n">momentum</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.5</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>Whether to use AMSGrad</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">54</span> <span class="n">amsgrad</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-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>Number of warmup optimizer 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">57</span> <span class="n">warmup</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">2_000</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>Total number of optimizer steps (for 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">59</span> <span class="n">total_steps</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="mf">1e10</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-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>Whether to degenerate to SGD in AdaBelief</p>
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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="n">degenerate_to_sgd</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</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>Whether to use Rectified Adam in AdaBelief</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">65</span> <span class="n">rectify</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</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'>
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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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<p>Model embedding size for Noam 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">68</span> <span class="n">d_model</span><span class="p">:</span> <span class="nb">int</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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</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="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
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<span class="lineno">71</span> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">_primary</span><span class="o">=</span><span class="s1">'optimizer'</span><span class="p">)</span>
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<span class="lineno">72</span>
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<span class="lineno">73</span>
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<span class="lineno">74</span><span class="n">meta_config</span><span class="p">(</span><span class="n">OptimizerConfigs</span><span class="o">.</span><span class="n">parameters</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-20'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-20'>#</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">77</span><span class="nd">@option</span><span class="p">(</span><span class="n">OptimizerConfigs</span><span class="o">.</span><span class="n">weight_decay_obj</span><span class="p">,</span> <span class="s1">'L2'</span><span class="p">)</span>
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<span class="lineno">78</span><span class="k">def</span> <span class="nf">_weight_decay</span><span class="p">(</span><span class="n">c</span><span class="p">:</span> <span class="n">OptimizerConfigs</span><span class="p">):</span>
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<span class="lineno">79</span> <span class="k">return</span> <span class="n">WeightDecay</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="n">c</span><span class="o">.</span><span class="n">weight_decouple</span><span class="p">,</span> <span class="n">c</span><span class="o">.</span><span class="n">weight_decay_absolute</span><span class="p">)</span>
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<span class="lineno">80</span>
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<span class="lineno">81</span>
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<span class="lineno">82</span><span class="nd">@option</span><span class="p">(</span><span class="n">OptimizerConfigs</span><span class="o">.</span><span class="n">optimizer</span><span class="p">,</span> <span class="s1">'SGD'</span><span class="p">)</span>
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<span class="lineno">83</span><span class="k">def</span> <span class="nf">_sgd_optimizer</span><span class="p">(</span><span class="n">c</span><span class="p">:</span> <span class="n">OptimizerConfigs</span><span class="p">):</span>
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<span class="lineno">84</span> <span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">optim</span><span class="o">.</span><span class="n">SGD</span><span class="p">(</span><span class="n">c</span><span class="o">.</span><span class="n">parameters</span><span class="p">,</span> <span class="n">c</span><span class="o">.</span><span class="n">learning_rate</span><span class="p">,</span> <span class="n">c</span><span class="o">.</span><span class="n">momentum</span><span class="p">)</span>
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<span class="lineno">85</span>
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<span class="lineno">86</span>
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<span class="lineno">87</span><span class="nd">@option</span><span class="p">(</span><span class="n">OptimizerConfigs</span><span class="o">.</span><span class="n">optimizer</span><span class="p">,</span> <span class="s1">'Adam'</span><span class="p">)</span>
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<span class="lineno">88</span><span class="k">def</span> <span class="nf">_adam_optimizer</span><span class="p">(</span><span class="n">c</span><span class="p">:</span> <span class="n">OptimizerConfigs</span><span class="p">):</span>
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<span class="lineno">89</span> <span class="k">if</span> <span class="n">c</span><span class="o">.</span><span class="n">amsgrad</span><span class="p">:</span>
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<span class="lineno">90</span> <span class="kn">from</span> <span class="nn">labml_nn.optimizers.amsgrad</span> <span class="kn">import</span> <span class="n">AMSGrad</span>
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<span class="lineno">91</span> <span class="k">return</span> <span class="n">AMSGrad</span><span class="p">(</span><span class="n">c</span><span class="o">.</span><span class="n">parameters</span><span class="p">,</span>
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<span class="lineno">92</span> <span class="n">lr</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">learning_rate</span><span class="p">,</span> <span class="n">betas</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">betas</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">eps</span><span class="p">,</span>
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<span class="lineno">93</span> <span class="n">optimized_update</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">optimized_adam_update</span><span class="p">,</span>
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<span class="lineno">94</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_obj</span><span class="p">,</span> <span class="n">amsgrad</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">amsgrad</span><span class="p">)</span>
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<span class="lineno">95</span> <span class="k">else</span><span class="p">:</span>
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<span class="lineno">96</span> <span class="kn">from</span> <span class="nn">labml_nn.optimizers.adam</span> <span class="kn">import</span> <span class="n">Adam</span>
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<span class="lineno">97</span> <span class="k">return</span> <span class="n">Adam</span><span class="p">(</span><span class="n">c</span><span class="o">.</span><span class="n">parameters</span><span class="p">,</span>
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<span class="lineno">98</span> <span class="n">lr</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">learning_rate</span><span class="p">,</span> <span class="n">betas</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">betas</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">eps</span><span class="p">,</span>
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<span class="lineno">99</span> <span class="n">optimized_update</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">optimized_adam_update</span><span class="p">,</span>
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<span class="lineno">100</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_obj</span><span class="p">)</span>
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<span class="lineno">101</span>
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<span class="lineno">102</span>
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<span class="lineno">103</span><span class="nd">@option</span><span class="p">(</span><span class="n">OptimizerConfigs</span><span class="o">.</span><span class="n">optimizer</span><span class="p">,</span> <span class="s1">'AdamW'</span><span class="p">)</span>
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<span class="lineno">104</span><span class="k">def</span> <span class="nf">_adam_warmup_optimizer</span><span class="p">(</span><span class="n">c</span><span class="p">:</span> <span class="n">OptimizerConfigs</span><span class="p">):</span>
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<span class="lineno">105</span> <span class="kn">from</span> <span class="nn">labml_nn.optimizers.adam_warmup</span> <span class="kn">import</span> <span class="n">AdamWarmup</span>
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<span class="lineno">106</span> <span class="k">return</span> <span class="n">AdamWarmup</span><span class="p">(</span><span class="n">c</span><span class="o">.</span><span class="n">parameters</span><span class="p">,</span>
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<span class="lineno">107</span> <span class="n">lr</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">learning_rate</span><span class="p">,</span> <span class="n">betas</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">betas</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">eps</span><span class="p">,</span>
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<span class="lineno">108</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_obj</span><span class="p">,</span> <span class="n">amsgrad</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">amsgrad</span><span class="p">,</span> <span class="n">warmup</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">warmup</span><span class="p">)</span>
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<span class="lineno">109</span>
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<span class="lineno">110</span>
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<span class="lineno">111</span><span class="nd">@option</span><span class="p">(</span><span class="n">OptimizerConfigs</span><span class="o">.</span><span class="n">optimizer</span><span class="p">,</span> <span class="s1">'RAdam'</span><span class="p">)</span>
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<span class="lineno">112</span><span class="k">def</span> <span class="nf">_radam_optimizer</span><span class="p">(</span><span class="n">c</span><span class="p">:</span> <span class="n">OptimizerConfigs</span><span class="p">):</span>
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<span class="lineno">113</span> <span class="kn">from</span> <span class="nn">labml_nn.optimizers.radam</span> <span class="kn">import</span> <span class="n">RAdam</span>
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<span class="lineno">114</span> <span class="k">return</span> <span class="n">RAdam</span><span class="p">(</span><span class="n">c</span><span class="o">.</span><span class="n">parameters</span><span class="p">,</span>
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<span class="lineno">115</span> <span class="n">lr</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">learning_rate</span><span class="p">,</span> <span class="n">betas</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">betas</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">eps</span><span class="p">,</span>
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<span class="lineno">116</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_obj</span><span class="p">,</span> <span class="n">amsgrad</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">amsgrad</span><span class="p">,</span>
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<span class="lineno">117</span> <span class="n">degenerated_to_sgd</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">degenerate_to_sgd</span><span class="p">)</span>
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<span class="lineno">118</span>
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<span class="lineno">119</span>
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<span class="lineno">120</span><span class="nd">@option</span><span class="p">(</span><span class="n">OptimizerConfigs</span><span class="o">.</span><span class="n">optimizer</span><span class="p">,</span> <span class="s1">'AdaBelief'</span><span class="p">)</span>
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<span class="lineno">121</span><span class="k">def</span> <span class="nf">_ada_belief_optimizer</span><span class="p">(</span><span class="n">c</span><span class="p">:</span> <span class="n">OptimizerConfigs</span><span class="p">):</span>
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<span class="lineno">122</span> <span class="kn">from</span> <span class="nn">labml_nn.optimizers.ada_belief</span> <span class="kn">import</span> <span class="n">AdaBelief</span>
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<span class="lineno">123</span> <span class="k">return</span> <span class="n">AdaBelief</span><span class="p">(</span><span class="n">c</span><span class="o">.</span><span class="n">parameters</span><span class="p">,</span>
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<span class="lineno">124</span> <span class="n">lr</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">learning_rate</span><span class="p">,</span> <span class="n">betas</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">betas</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">eps</span><span class="p">,</span>
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<span class="lineno">125</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_obj</span><span class="p">,</span> <span class="n">amsgrad</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">amsgrad</span><span class="p">,</span>
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<span class="lineno">126</span> <span class="n">degenerate_to_sgd</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">degenerate_to_sgd</span><span class="p">,</span>
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<span class="lineno">127</span> <span class="n">rectify</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">rectify</span><span class="p">)</span>
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<span class="lineno">128</span>
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<span class="lineno">129</span>
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<span class="lineno">130</span><span class="nd">@option</span><span class="p">(</span><span class="n">OptimizerConfigs</span><span class="o">.</span><span class="n">optimizer</span><span class="p">,</span> <span class="s1">'Noam'</span><span class="p">)</span>
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<span class="lineno">131</span><span class="k">def</span> <span class="nf">_noam_optimizer</span><span class="p">(</span><span class="n">c</span><span class="p">:</span> <span class="n">OptimizerConfigs</span><span class="p">):</span>
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<span class="lineno">132</span> <span class="kn">from</span> <span class="nn">labml_nn.optimizers.noam</span> <span class="kn">import</span> <span class="n">Noam</span>
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<span class="lineno">133</span> <span class="k">return</span> <span class="n">Noam</span><span class="p">(</span><span class="n">c</span><span class="o">.</span><span class="n">parameters</span><span class="p">,</span>
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<span class="lineno">134</span> <span class="n">lr</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">learning_rate</span><span class="p">,</span> <span class="n">betas</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">betas</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">eps</span><span class="p">,</span>
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<span class="lineno">135</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_obj</span><span class="p">,</span> <span class="n">amsgrad</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">amsgrad</span><span class="p">,</span> <span class="n">warmup</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">warmup</span><span class="p">,</span>
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<span class="lineno">136</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>
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<span class="lineno">137</span>
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<span class="lineno">138</span>
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<span class="lineno">139</span><span class="nd">@option</span><span class="p">(</span><span class="n">OptimizerConfigs</span><span class="o">.</span><span class="n">optimizer</span><span class="p">,</span> <span class="s1">'AdamWarmupCosineDecay'</span><span class="p">)</span>
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<span class="lineno">140</span><span class="k">def</span> <span class="nf">_noam_optimizer</span><span class="p">(</span><span class="n">c</span><span class="p">:</span> <span class="n">OptimizerConfigs</span><span class="p">):</span>
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<span class="lineno">141</span> <span class="kn">from</span> <span class="nn">labml_nn.optimizers.adam_warmup_cosine_decay</span> <span class="kn">import</span> <span class="n">AdamWarmupCosineDecay</span>
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<span class="lineno">142</span> <span class="k">return</span> <span class="n">AdamWarmupCosineDecay</span><span class="p">(</span><span class="n">c</span><span class="o">.</span><span class="n">parameters</span><span class="p">,</span>
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|
<span class="lineno">143</span> <span class="n">lr</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">learning_rate</span><span class="p">,</span> <span class="n">betas</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">betas</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">eps</span><span class="p">,</span>
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<span class="lineno">144</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_obj</span><span class="p">,</span> <span class="n">amsgrad</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">amsgrad</span><span class="p">,</span>
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<span class="lineno">145</span> <span class="n">warmup</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">warmup</span><span class="p">,</span> <span class="n">total_steps</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">total_steps</span><span class="p">)</span></pre></div>
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