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<li><a class="reference internal" href="#">deepof.model_utils.ExponentialLearningRate</a><ul>
<li><a class="reference internal" href="#deepof.model_utils.ExponentialLearningRate"><code class="docutils literal notranslate"><span class="pre">ExponentialLearningRate</span></code></a><ul>
<li><a class="reference internal" href="#deepof.model_utils.ExponentialLearningRate.__init__"><code class="docutils literal notranslate"><span class="pre">ExponentialLearningRate.__init__()</span></code></a></li>
<li><a class="reference internal" href="#id0"><code class="docutils literal notranslate"><span class="pre">ExponentialLearningRate.__init__()</span></code></a></li>
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<section id="deepof-model-utils-exponentiallearningrate">
<h1>deepof.model_utils.ExponentialLearningRate<a class="headerlink" href="#deepof-model-utils-exponentiallearningrate" title="Permalink to this heading"></a></h1>
<dl class="py class">
<dt class="sig sig-object py" id="deepof.model_utils.ExponentialLearningRate">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">deepof.model_utils.</span></span><span class="sig-name descname"><span class="pre">ExponentialLearningRate</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">factor</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#deepof.model_utils.ExponentialLearningRate" title="Permalink to this definition"></a></dt>
<dd><p>Simple class that allows to grow learning rate exponentially during training.</p>
<p>Used to trigger optimal learning rate search in deepof.train_utils.find_learning_rate.</p>
<dl class="py method">
<dt class="sig sig-object py" id="deepof.model_utils.ExponentialLearningRate.__init__">
<span class="sig-name descname"><span class="pre">__init__</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">factor</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#deepof.model_utils.ExponentialLearningRate.__init__" title="Permalink to this definition"></a></dt>
<dd><p>Initialize the exponential learning rate callback.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>factor</strong> (<em>float</em>) – factor by which to multiply the learning rate</p>
</dd>
</dl>
</dd></dl>
<p class="rubric">Methods</p>
<table class="autosummary longtable docutils align-default">
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="#id0" title="deepof.model_utils.ExponentialLearningRate.__init__"><code class="xref py py-obj docutils literal notranslate"><span class="pre">__init__</span></code></a>(factor)</p></td>
<td><p>Initialize the exponential learning rate callback.</p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">on_batch_begin</span></code>(batch[, logs])</p></td>
<td><p>A backwards compatibility alias for <cite>on_train_batch_begin</cite>.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">on_batch_end</span></code>(batch, logs)</p></td>
<td><p>Apply on batch end.</p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">on_epoch_begin</span></code>(epoch[, logs])</p></td>
<td><p>Called at the start of an epoch.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">on_epoch_end</span></code>(epoch[, logs])</p></td>
<td><p>Called at the end of an epoch.</p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">on_predict_batch_begin</span></code>(batch[, logs])</p></td>
<td><p>Called at the beginning of a batch in <cite>predict</cite> methods.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">on_predict_batch_end</span></code>(batch[, logs])</p></td>
<td><p>Called at the end of a batch in <cite>predict</cite> methods.</p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">on_predict_begin</span></code>([logs])</p></td>
<td><p>Called at the beginning of prediction.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">on_predict_end</span></code>([logs])</p></td>
<td><p>Called at the end of prediction.</p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">on_test_batch_begin</span></code>(batch[, logs])</p></td>
<td><p>Called at the beginning of a batch in <cite>evaluate</cite> methods.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">on_test_batch_end</span></code>(batch[, logs])</p></td>
<td><p>Called at the end of a batch in <cite>evaluate</cite> methods.</p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">on_test_begin</span></code>([logs])</p></td>
<td><p>Called at the beginning of evaluation or validation.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">on_test_end</span></code>([logs])</p></td>
<td><p>Called at the end of evaluation or validation.</p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">on_train_batch_begin</span></code>(batch[, logs])</p></td>
<td><p>Called at the beginning of a training batch in <cite>fit</cite> methods.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">on_train_batch_end</span></code>(batch[, logs])</p></td>
<td><p>Called at the end of a training batch in <cite>fit</cite> methods.</p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">on_train_begin</span></code>([logs])</p></td>
<td><p>Called at the beginning of training.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">on_train_end</span></code>([logs])</p></td>
<td><p>Called at the end of training.</p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">set_model</span></code>(model)</p></td>
<td><p></p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">set_params</span></code>(params)</p></td>
<td><p></p></td>
</tr>
</tbody>
</table>
<dl class="py method">
<dt class="sig sig-object py" id="id0">
<span class="sig-name descname"><span class="pre">__init__</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">factor</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id0" title="Permalink to this definition"></a></dt>
<dd><p>Initialize the exponential learning rate callback.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>factor</strong> (<em>float</em>) – factor by which to multiply the learning rate</p>
</dd>
</dl>
</dd></dl>
</dd></dl>
</section>
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