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callbacks.tracker.html
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---
title: callbacks.tracker
keywords: fastai
sidebar: home_sidebar
summary: "Callbacks that take decisions depending on the evolution of metrics during training"
---
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<h2 id="Tracking-Callbacks">Tracking Callbacks<a class="anchor-link" href="#Tracking-Callbacks">¶</a></h2>
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<p>This module regroups the callbacks that track one of the metrics computed at the end of each epoch to take some decision about training. To show examples of use, we'll use our sample of MNIST and a simple cnn model.</p>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">path</span> <span class="o">=</span> <span class="n">untar_data</span><span class="p">(</span><span class="n">URLs</span><span class="o">.</span><span class="n">MNIST_SAMPLE</span><span class="p">)</span>
<span class="n">data</span> <span class="o">=</span> <span class="n">ImageDataBunch</span><span class="o">.</span><span class="n">from_folder</span><span class="p">(</span><span class="n">path</span><span class="p">)</span>
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<h2 id="TerminateOnNaNCallback" class="doc_header"><code>class</code> <code>TerminateOnNaNCallback</code><a href="https://github.com/fastai/fastai/blob/master/fastai/callbacks/tracker.py#L10" class="source_link" style="float:right">[source]</a><a class="source_link" data-toggle="collapse" data-target="#TerminateOnNaNCallback-pytest" style="float:right; padding-right:10px">[test]</a></h2><blockquote><p><code>TerminateOnNaNCallback</code>() :: <a href="/callback.html#Callback"><code>Callback</code></a></p>
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<div class="collapse" id="TerminateOnNaNCallback-pytest"><div class="card card-body pytest_card"><a type="button" data-toggle="collapse" data-target="#TerminateOnNaNCallback-pytest" class="close" aria-label="Close"><span aria-hidden="true">×</span></a><p>No tests found for <code>TerminateOnNaNCallback</code>. To contribute a test please refer to <a href="/dev/test.html">this guide</a> and <a href="https://forums.fast.ai/t/improving-expanding-functional-tests/32929">this discussion</a>.</p></div></div><p>A <a href="/callback.html#Callback"><code>Callback</code></a> that terminates training if loss is NaN.</p>
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<p>Sometimes, training diverges and the loss goes to nan. In that case, there's no point continuing, so this callback stops the training.</p>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">model</span> <span class="o">=</span> <span class="n">simple_cnn</span><span class="p">((</span><span class="mi">3</span><span class="p">,</span><span class="mi">16</span><span class="p">,</span><span class="mi">16</span><span class="p">,</span><span class="mi">2</span><span class="p">))</span>
<span class="n">learn</span> <span class="o">=</span> <span class="n">Learner</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">model</span><span class="p">,</span> <span class="n">metrics</span><span class="o">=</span><span class="p">[</span><span class="n">accuracy</span><span class="p">])</span>
<span class="n">learn</span><span class="o">.</span><span class="n">fit_one_cycle</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span><span class="mf">1e4</span><span class="p">)</span>
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<th>epoch</th>
<th>train_loss</th>
<th>valid_loss</th>
<th>accuracy</th>
<th>time</th>
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<td>1</td>
<td>nan</td>
<td>nan</td>
<td>0.495584</td>
<td>00:02</td>
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<p>Using it prevents that situation to happen.</p>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">model</span> <span class="o">=</span> <span class="n">simple_cnn</span><span class="p">((</span><span class="mi">3</span><span class="p">,</span><span class="mi">16</span><span class="p">,</span><span class="mi">16</span><span class="p">,</span><span class="mi">2</span><span class="p">))</span>
<span class="n">learn</span> <span class="o">=</span> <span class="n">Learner</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">model</span><span class="p">,</span> <span class="n">metrics</span><span class="o">=</span><span class="p">[</span><span class="n">accuracy</span><span class="p">],</span> <span class="n">callbacks</span><span class="o">=</span><span class="p">[</span><span class="n">TerminateOnNaNCallback</span><span class="p">()])</span>
<span class="n">learn</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span><span class="mf">1e4</span><span class="p">)</span>
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<th>epoch</th>
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<th>valid_loss</th>
<th>accuracy</th>
<th>time</th>
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<pre>Epoch/Batch (0/5): Invalid loss, terminating training.
Epoch/Batch (0/6): Invalid loss, terminating training.
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<h3 id="Callback-methods">Callback methods<a class="anchor-link" href="#Callback-methods">¶</a></h3>
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<p>You don't call these yourself - they're called by fastai's <a href="/callback.html#Callback"><code>Callback</code></a> system automatically to enable the class's functionality.</p>
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<h4 id="TerminateOnNaNCallback.on_batch_end" class="doc_header"><code>on_batch_end</code><a href="https://github.com/fastai/fastai/blob/master/fastai/callbacks/tracker.py#L16" class="source_link" style="float:right">[source]</a><a class="source_link" data-toggle="collapse" data-target="#TerminateOnNaNCallback-on_batch_end-pytest" style="float:right; padding-right:10px">[test]</a></h4><blockquote><p><code>on_batch_end</code>(<strong><code>last_loss</code></strong>, <strong><code>epoch</code></strong>, <strong><code>num_batch</code></strong>, <strong>**<code>kwargs</code></strong>:<code>Any</code>)</p>
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<div class="collapse" id="TerminateOnNaNCallback-on_batch_end-pytest"><div class="card card-body pytest_card"><a type="button" data-toggle="collapse" data-target="#TerminateOnNaNCallback-on_batch_end-pytest" class="close" aria-label="Close"><span aria-hidden="true">×</span></a><p>No tests found for <code>on_batch_end</code>. To contribute a test please refer to <a href="/dev/test.html">this guide</a> and <a href="https://forums.fast.ai/t/improving-expanding-functional-tests/32929">this discussion</a>.</p></div></div><p>Test if <code>last_loss</code> is NaN and interrupts training.</p>
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<h4 id="Callback.on_epoch_end" class="doc_header"><code>on_epoch_end</code><a href="https://github.com/fastai/fastai/blob/master/fastai/callback.py#L161" class="source_link" style="float:right">[source]</a><a class="source_link" data-toggle="collapse" data-target="#Callback-on_epoch_end-pytest" style="float:right; padding-right:10px">[test]</a></h4><blockquote><p><code>on_epoch_end</code>(<strong>**<code>kwargs</code></strong>:<code>Any</code>)</p>
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<div class="collapse" id="Callback-on_epoch_end-pytest"><div class="card card-body pytest_card"><a type="button" data-toggle="collapse" data-target="#Callback-on_epoch_end-pytest" class="close" aria-label="Close"><span aria-hidden="true">×</span></a><p>No tests found for <code>on_epoch_end</code>. To contribute a test please refer to <a href="/dev/test.html">this guide</a> and <a href="https://forums.fast.ai/t/improving-expanding-functional-tests/32929">this discussion</a>.</p></div></div><p>Called at the end of an epoch.</p>
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<h2 id="EarlyStoppingCallback" class="doc_header"><code>class</code> <code>EarlyStoppingCallback</code><a href="https://github.com/fastai/fastai/blob/master/fastai/callbacks/tracker.py#L52" class="source_link" style="float:right">[source]</a><a class="source_link" data-toggle="collapse" data-target="#EarlyStoppingCallback-pytest" style="float:right; padding-right:10px">[test]</a></h2><blockquote><p><code>EarlyStoppingCallback</code>(<strong><code>learn</code></strong>:<a href="/basic_train.html#Learner"><code>Learner</code></a>, <strong><code>monitor</code></strong>:<code>str</code>=<strong><em><code>'val_loss'</code></em></strong>, <strong><code>mode</code></strong>:<code>str</code>=<strong><em><code>'auto'</code></em></strong>, <strong><code>min_delta</code></strong>:<code>int</code>=<strong><em><code>0</code></em></strong>, <strong><code>patience</code></strong>:<code>int</code>=<strong><em><code>0</code></em></strong>) :: <a href="/callbacks.tracker.html#TrackerCallback"><code>TrackerCallback</code></a></p>
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<div class="collapse" id="EarlyStoppingCallback-pytest"><div class="card card-body pytest_card"><a type="button" data-toggle="collapse" data-target="#EarlyStoppingCallback-pytest" class="close" aria-label="Close"><span aria-hidden="true">×</span></a><p>No tests found for <code>EarlyStoppingCallback</code>. To contribute a test please refer to <a href="/dev/test.html">this guide</a> and <a href="https://forums.fast.ai/t/improving-expanding-functional-tests/32929">this discussion</a>.</p></div></div><p>A <a href="/callbacks.tracker.html#TrackerCallback"><code>TrackerCallback</code></a> that terminates training when monitored quantity stops improving.</p>
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<p>This callback tracks the quantity in <code>monitor</code> during the training of <code>learn</code>. <code>mode</code> can be forced to 'min' or 'max' but will automatically try to determine if the quantity should be the lowest possible (validation loss) or the highest possible (accuracy). Will stop training after <code>patience</code> epochs if the quantity hasn't improved by <code>min_delta</code>.</p>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">model</span> <span class="o">=</span> <span class="n">simple_cnn</span><span class="p">((</span><span class="mi">3</span><span class="p">,</span><span class="mi">16</span><span class="p">,</span><span class="mi">16</span><span class="p">,</span><span class="mi">2</span><span class="p">))</span>
<span class="n">learn</span> <span class="o">=</span> <span class="n">Learner</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">model</span><span class="p">,</span> <span class="n">metrics</span><span class="o">=</span><span class="p">[</span><span class="n">accuracy</span><span class="p">],</span>
<span class="n">callback_fns</span><span class="o">=</span><span class="p">[</span><span class="n">partial</span><span class="p">(</span><span class="n">EarlyStoppingCallback</span><span class="p">,</span> <span class="n">monitor</span><span class="o">=</span><span class="s1">'accuracy'</span><span class="p">,</span> <span class="n">min_delta</span><span class="o">=</span><span class="mf">0.01</span><span class="p">,</span> <span class="n">patience</span><span class="o">=</span><span class="mi">3</span><span class="p">)])</span>
<span class="n">learn</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="mi">50</span><span class="p">,</span><span class="mf">1e-42</span><span class="p">)</span>
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<th>epoch</th>
<th>train_loss</th>
<th>valid_loss</th>
<th>accuracy</th>
<th>time</th>
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<td>1</td>
<td>0.677729</td>
<td>0.677514</td>
<td>0.560353</td>
<td>00:02</td>
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<td>2</td>
<td>0.679820</td>
<td>0.677514</td>
<td>0.560353</td>
<td>00:02</td>
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<tr>
<td>3</td>
<td>0.679434</td>
<td>0.677514</td>
<td>0.560353</td>
<td>00:02</td>
</tr>
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<td>4</td>
<td>0.679893</td>
<td>0.677514</td>
<td>0.560353</td>
<td>00:02</td>
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<pre>Epoch 5: early stopping
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<pre>
<span class="ansi-red-fg">---------------------------------------------------------------------------</span>
<span class="ansi-red-fg">AttributeError</span> Traceback (most recent call last)
<span class="ansi-green-fg"><ipython-input-9-4384b4e1abc4></span> in <span class="ansi-cyan-fg"><module></span>
<span class="ansi-green-intense-fg ansi-bold"> 2</span> learn = Learner(data, model, metrics=[accuracy],
<span class="ansi-green-intense-fg ansi-bold"> 3</span> callback_fns=[partial(EarlyStoppingCallback, monitor='accuracy', min_delta=0.01, patience=3)])
<span class="ansi-green-fg">----> 4</span><span class="ansi-red-fg"> </span>learn<span class="ansi-blue-fg">.</span>fit<span class="ansi-blue-fg">(</span><span class="ansi-cyan-fg">50</span><span class="ansi-blue-fg">,</span><span class="ansi-cyan-fg">1e-42</span><span class="ansi-blue-fg">)</span>
<span class="ansi-green-fg">~/fastai/fastai/basic_train.py</span> in <span class="ansi-cyan-fg">fit</span><span class="ansi-blue-fg">(self, epochs, lr, wd, callbacks)</span>
<span class="ansi-green-intense-fg ansi-bold"> 180</span> <span class="ansi-green-fg">if</span> defaults<span class="ansi-blue-fg">.</span>extra_callbacks <span class="ansi-green-fg">is</span> <span class="ansi-green-fg">not</span> <span class="ansi-green-fg">None</span><span class="ansi-blue-fg">:</span> callbacks <span class="ansi-blue-fg">+=</span> defaults<span class="ansi-blue-fg">.</span>extra_callbacks
<span class="ansi-green-intense-fg ansi-bold"> 181</span> fit(epochs, self.model, self.loss_func, opt=self.opt, data=self.data, metrics=self.metrics,
<span class="ansi-green-fg">--> 182</span><span class="ansi-red-fg"> callbacks=self.callbacks+callbacks)
</span><span class="ansi-green-intense-fg ansi-bold"> 183</span>
<span class="ansi-green-intense-fg ansi-bold"> 184</span> <span class="ansi-green-fg">def</span> create_opt<span class="ansi-blue-fg">(</span>self<span class="ansi-blue-fg">,</span> lr<span class="ansi-blue-fg">:</span>Floats<span class="ansi-blue-fg">,</span> wd<span class="ansi-blue-fg">:</span>Floats<span class="ansi-blue-fg">=</span><span class="ansi-cyan-fg">0.</span><span class="ansi-blue-fg">)</span><span class="ansi-blue-fg">-></span><span class="ansi-green-fg">None</span><span class="ansi-blue-fg">:</span>
<span class="ansi-green-fg">~/fastai/fastai/basic_train.py</span> in <span class="ansi-cyan-fg">fit</span><span class="ansi-blue-fg">(epochs, model, loss_func, opt, data, callbacks, metrics)</span>
<span class="ansi-green-intense-fg ansi-bold"> 97</span> cb_handler=cb_handler, pbar=pbar)
<span class="ansi-green-intense-fg ansi-bold"> 98</span> <span class="ansi-green-fg">else</span><span class="ansi-blue-fg">:</span> val_loss<span class="ansi-blue-fg">=</span><span class="ansi-green-fg">None</span>
<span class="ansi-green-fg">---> 99</span><span class="ansi-red-fg"> </span><span class="ansi-green-fg">if</span> cb_handler<span class="ansi-blue-fg">.</span>on_epoch_end<span class="ansi-blue-fg">(</span>val_loss<span class="ansi-blue-fg">)</span><span class="ansi-blue-fg">:</span> <span class="ansi-green-fg">break</span>
<span class="ansi-green-intense-fg ansi-bold"> 100</span> <span class="ansi-green-fg">except</span> Exception <span class="ansi-green-fg">as</span> e<span class="ansi-blue-fg">:</span>
<span class="ansi-green-intense-fg ansi-bold"> 101</span> exception <span class="ansi-blue-fg">=</span> e
<span class="ansi-green-fg">~/fastai/fastai/callback.py</span> in <span class="ansi-cyan-fg">on_epoch_end</span><span class="ansi-blue-fg">(self, val_loss)</span>
<span class="ansi-green-intense-fg ansi-bold"> 287</span> self<span class="ansi-blue-fg">.</span>state_dict<span class="ansi-blue-fg">[</span><span class="ansi-blue-fg">'last_metrics'</span><span class="ansi-blue-fg">]</span> <span class="ansi-blue-fg">=</span> <span class="ansi-blue-fg">[</span>val_loss<span class="ansi-blue-fg">]</span> <span class="ansi-green-fg">if</span> val_loss <span class="ansi-green-fg">is</span> <span class="ansi-green-fg">not</span> <span class="ansi-green-fg">None</span> <span class="ansi-green-fg">else</span> <span class="ansi-green-fg">None</span>
<span class="ansi-green-intense-fg ansi-bold"> 288</span> self<span class="ansi-blue-fg">.</span>state_dict<span class="ansi-blue-fg">[</span><span class="ansi-blue-fg">'epoch'</span><span class="ansi-blue-fg">]</span> <span class="ansi-blue-fg">+=</span> <span class="ansi-cyan-fg">1</span>
<span class="ansi-green-fg">--> 289</span><span class="ansi-red-fg"> </span>self<span class="ansi-blue-fg">(</span><span class="ansi-blue-fg">'epoch_end'</span><span class="ansi-blue-fg">,</span> call_mets <span class="ansi-blue-fg">=</span> val_loss <span class="ansi-green-fg">is</span> <span class="ansi-green-fg">not</span> <span class="ansi-green-fg">None</span><span class="ansi-blue-fg">)</span>
<span class="ansi-green-intense-fg ansi-bold"> 290</span> <span class="ansi-green-fg">return</span> self<span class="ansi-blue-fg">.</span>state_dict<span class="ansi-blue-fg">[</span><span class="ansi-blue-fg">'stop_training'</span><span class="ansi-blue-fg">]</span>
<span class="ansi-green-intense-fg ansi-bold"> 291</span>
<span class="ansi-green-fg">~/fastai/fastai/callback.py</span> in <span class="ansi-cyan-fg">__call__</span><span class="ansi-blue-fg">(self, cb_name, call_mets, **kwargs)</span>
<span class="ansi-green-intense-fg ansi-bold"> 222</span> <span class="ansi-green-fg">if</span> call_mets<span class="ansi-blue-fg">:</span>
<span class="ansi-green-intense-fg ansi-bold"> 223</span> <span class="ansi-green-fg">for</span> met <span class="ansi-green-fg">in</span> self<span class="ansi-blue-fg">.</span>metrics<span class="ansi-blue-fg">:</span> self<span class="ansi-blue-fg">.</span>_call_and_update<span class="ansi-blue-fg">(</span>met<span class="ansi-blue-fg">,</span> cb_name<span class="ansi-blue-fg">,</span> <span class="ansi-blue-fg">**</span>kwargs<span class="ansi-blue-fg">)</span>
<span class="ansi-green-fg">--> 224</span><span class="ansi-red-fg"> </span><span class="ansi-green-fg">for</span> cb <span class="ansi-green-fg">in</span> self<span class="ansi-blue-fg">.</span>callbacks<span class="ansi-blue-fg">:</span> self<span class="ansi-blue-fg">.</span>_call_and_update<span class="ansi-blue-fg">(</span>cb<span class="ansi-blue-fg">,</span> cb_name<span class="ansi-blue-fg">,</span> <span class="ansi-blue-fg">**</span>kwargs<span class="ansi-blue-fg">)</span>
<span class="ansi-green-intense-fg ansi-bold"> 225</span>
<span class="ansi-green-intense-fg ansi-bold"> 226</span> <span class="ansi-green-fg">def</span> set_dl<span class="ansi-blue-fg">(</span>self<span class="ansi-blue-fg">,</span> dl<span class="ansi-blue-fg">:</span>DataLoader<span class="ansi-blue-fg">)</span><span class="ansi-blue-fg">:</span>
<span class="ansi-green-fg">~/fastai/fastai/callback.py</span> in <span class="ansi-cyan-fg">_call_and_update</span><span class="ansi-blue-fg">(self, cb, cb_name, **kwargs)</span>
<span class="ansi-green-intense-fg ansi-bold"> 213</span> <span class="ansi-blue-fg">"Call `cb_name` on `cb` and update the inner state."</span>
<span class="ansi-green-intense-fg ansi-bold"> 214</span> new <span class="ansi-blue-fg">=</span> ifnone<span class="ansi-blue-fg">(</span>getattr<span class="ansi-blue-fg">(</span>cb<span class="ansi-blue-fg">,</span> <span class="ansi-blue-fg">f'on_{cb_name}'</span><span class="ansi-blue-fg">)</span><span class="ansi-blue-fg">(</span><span class="ansi-blue-fg">**</span>self<span class="ansi-blue-fg">.</span>state_dict<span class="ansi-blue-fg">,</span> <span class="ansi-blue-fg">**</span>kwargs<span class="ansi-blue-fg">)</span><span class="ansi-blue-fg">,</span> dict<span class="ansi-blue-fg">(</span><span class="ansi-blue-fg">)</span><span class="ansi-blue-fg">)</span>
<span class="ansi-green-fg">--> 215</span><span class="ansi-red-fg"> </span><span class="ansi-green-fg">for</span> k<span class="ansi-blue-fg">,</span>v <span class="ansi-green-fg">in</span> new<span class="ansi-blue-fg">.</span>items<span class="ansi-blue-fg">(</span><span class="ansi-blue-fg">)</span><span class="ansi-blue-fg">:</span>
<span class="ansi-green-intense-fg ansi-bold"> 216</span> <span class="ansi-green-fg">if</span> k <span class="ansi-green-fg">not</span> <span class="ansi-green-fg">in</span> self<span class="ansi-blue-fg">.</span>state_dict<span class="ansi-blue-fg">:</span>
<span class="ansi-green-intense-fg ansi-bold"> 217</span> <span class="ansi-green-fg">raise</span> Exception<span class="ansi-blue-fg">(</span><span class="ansi-blue-fg">f"{k} isn't a valid key in the state of the callbacks."</span><span class="ansi-blue-fg">)</span>
<span class="ansi-red-fg">AttributeError</span>: 'bool' object has no attribute 'items'</pre>
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<h3 id="Callback-methods">Callback methods<a class="anchor-link" href="#Callback-methods">¶</a></h3>
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<p>You don't call these yourself - they're called by fastai's <a href="/callback.html#Callback"><code>Callback</code></a> system automatically to enable the class's functionality.</p>
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<h4 id="EarlyStoppingCallback.on_train_begin" class="doc_header"><code>on_train_begin</code><a href="https://github.com/fastai/fastai/blob/master/fastai/callbacks/tracker.py#L59" class="source_link" style="float:right">[source]</a><a class="source_link" data-toggle="collapse" data-target="#EarlyStoppingCallback-on_train_begin-pytest" style="float:right; padding-right:10px">[test]</a></h4><blockquote><p><code>on_train_begin</code>(<strong>**<code>kwargs</code></strong>:<code>Any</code>)</p>
</blockquote>
<div class="collapse" id="EarlyStoppingCallback-on_train_begin-pytest"><div class="card card-body pytest_card"><a type="button" data-toggle="collapse" data-target="#EarlyStoppingCallback-on_train_begin-pytest" class="close" aria-label="Close"><span aria-hidden="true">×</span></a><p>No tests found for <code>on_train_begin</code>. To contribute a test please refer to <a href="/dev/test.html">this guide</a> and <a href="https://forums.fast.ai/t/improving-expanding-functional-tests/32929">this discussion</a>.</p></div></div><p>Initialize inner arguments.</p>
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<h4 id="EarlyStoppingCallback.on_epoch_end" class="doc_header"><code>on_epoch_end</code><a href="https://github.com/fastai/fastai/blob/master/fastai/callbacks/tracker.py#L64" class="source_link" style="float:right">[source]</a><a class="source_link" data-toggle="collapse" data-target="#EarlyStoppingCallback-on_epoch_end-pytest" style="float:right; padding-right:10px">[test]</a></h4><blockquote><p><code>on_epoch_end</code>(<strong><code>epoch</code></strong>, <strong>**<code>kwargs</code></strong>:<code>Any</code>)</p>
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<div class="collapse" id="EarlyStoppingCallback-on_epoch_end-pytest"><div class="card card-body pytest_card"><a type="button" data-toggle="collapse" data-target="#EarlyStoppingCallback-on_epoch_end-pytest" class="close" aria-label="Close"><span aria-hidden="true">×</span></a><p>No tests found for <code>on_epoch_end</code>. To contribute a test please refer to <a href="/dev/test.html">this guide</a> and <a href="https://forums.fast.ai/t/improving-expanding-functional-tests/32929">this discussion</a>.</p></div></div><p>Compare the value monitored to its best score and maybe stop training.</p>
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<h2 id="SaveModelCallback" class="doc_header"><code>class</code> <code>SaveModelCallback</code><a href="https://github.com/fastai/fastai/blob/master/fastai/callbacks/tracker.py#L76" class="source_link" style="float:right">[source]</a><a class="source_link" data-toggle="collapse" data-target="#SaveModelCallback-pytest" style="float:right; padding-right:10px">[test]</a></h2><blockquote><p><code>SaveModelCallback</code>(<strong><code>learn</code></strong>:<a href="/basic_train.html#Learner"><code>Learner</code></a>, <strong><code>monitor</code></strong>:<code>str</code>=<strong><em><code>'val_loss'</code></em></strong>, <strong><code>mode</code></strong>:<code>str</code>=<strong><em><code>'auto'</code></em></strong>, <strong><code>every</code></strong>:<code>str</code>=<strong><em><code>'improvement'</code></em></strong>, <strong><code>name</code></strong>:<code>str</code>=<strong><em><code>'bestmodel'</code></em></strong>) :: <a href="/callbacks.tracker.html#TrackerCallback"><code>TrackerCallback</code></a></p>
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<div class="collapse" id="SaveModelCallback-pytest"><div class="card card-body pytest_card"><a type="button" data-toggle="collapse" data-target="#SaveModelCallback-pytest" class="close" aria-label="Close"><span aria-hidden="true">×</span></a><p>No tests found for <code>SaveModelCallback</code>. To contribute a test please refer to <a href="/dev/test.html">this guide</a> and <a href="https://forums.fast.ai/t/improving-expanding-functional-tests/32929">this discussion</a>.</p></div></div><p>A <a href="/callbacks.tracker.html#TrackerCallback"><code>TrackerCallback</code></a> that saves the model when monitored quantity is best.</p>
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<p>This callback tracks the quantity in <code>monitor</code> during the training of <code>learn</code>. <code>mode</code> can be forced to 'min' or 'max' but will automatically try to determine if the quantity should be the lowest possible (validation loss) or the highest possible (accuracy). Will save the model in <code>name</code> whenever determined by <code>every</code> ('improvement' or 'epoch'). Loads the best model at the end of training is <code>every='improvement'</code>.</p>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">model</span> <span class="o">=</span> <span class="n">simple_cnn</span><span class="p">((</span><span class="mi">3</span><span class="p">,</span><span class="mi">16</span><span class="p">,</span><span class="mi">16</span><span class="p">,</span><span class="mi">2</span><span class="p">))</span>
<span class="n">learn</span> <span class="o">=</span> <span class="n">Learner</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">model</span><span class="p">,</span> <span class="n">metrics</span><span class="o">=</span><span class="p">[</span><span class="n">accuracy</span><span class="p">])</span>
<span class="n">learn</span><span class="o">.</span><span class="n">fit_one_cycle</span><span class="p">(</span><span class="mi">5</span><span class="p">,</span><span class="mf">1e-4</span><span class="p">,</span> <span class="n">callbacks</span><span class="o">=</span><span class="p">[</span><span class="n">SaveModelCallback</span><span class="p">(</span><span class="n">learn</span><span class="p">,</span> <span class="n">every</span><span class="o">=</span><span class="s1">'epoch'</span><span class="p">,</span> <span class="n">monitor</span><span class="o">=</span><span class="s1">'accuracy'</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">'model'</span><span class="p">)])</span>
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<p>Choosing <code>every='epoch'</code> saves an individual model at the end of each epoch.</p>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="o">!</span>ls ~/.fastai/data/mnist_sample/models
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">learn</span><span class="o">.</span><span class="n">fit_one_cycle</span><span class="p">(</span><span class="mi">5</span><span class="p">,</span><span class="mf">1e-4</span><span class="p">,</span> <span class="n">callbacks</span><span class="o">=</span><span class="p">[</span><span class="n">SaveModelCallback</span><span class="p">(</span><span class="n">learn</span><span class="p">,</span> <span class="n">every</span><span class="o">=</span><span class="s1">'improvement'</span><span class="p">,</span> <span class="n">monitor</span><span class="o">=</span><span class="s1">'accuracy'</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">'best'</span><span class="p">)])</span>
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<p>Choosing <code>every='improvement'</code> saves the single best model out of all epochs during training.</p>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="o">!</span>ls ~/.fastai/data/mnist_sample/models
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<h3 id="Callback-methods">Callback methods<a class="anchor-link" href="#Callback-methods">¶</a></h3>
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<p>You don't call these yourself - they're called by fastai's <a href="/callback.html#Callback"><code>Callback</code></a> system automatically to enable the class's functionality.</p>
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<h4 id="SaveModelCallback.on_epoch_end" class="doc_header"><code>on_epoch_end</code><a href="https://github.com/fastai/fastai/blob/master/fastai/callbacks/tracker.py#L91" class="source_link" style="float:right">[source]</a><a class="source_link" data-toggle="collapse" data-target="#SaveModelCallback-on_epoch_end-pytest" style="float:right; padding-right:10px">[test]</a></h4><blockquote><p><code>on_epoch_end</code>(<strong><code>epoch</code></strong>:<code>int</code>, <strong>**<code>kwargs</code></strong>:<code>Any</code>)</p>
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<div class="collapse" id="SaveModelCallback-on_epoch_end-pytest"><div class="card card-body pytest_card"><a type="button" data-toggle="collapse" data-target="#SaveModelCallback-on_epoch_end-pytest" class="close" aria-label="Close"><span aria-hidden="true">×</span></a><p>No tests found for <code>on_epoch_end</code>. To contribute a test please refer to <a href="/dev/test.html">this guide</a> and <a href="https://forums.fast.ai/t/improving-expanding-functional-tests/32929">this discussion</a>.</p></div></div><p>Compare the value monitored to its best score and maybe save the model.</p>
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<h4 id="SaveModelCallback.on_train_end" class="doc_header"><code>on_train_end</code><a href="https://github.com/fastai/fastai/blob/master/fastai/callbacks/tracker.py#L101" class="source_link" style="float:right">[source]</a><a class="source_link" data-toggle="collapse" data-target="#SaveModelCallback-on_train_end-pytest" style="float:right; padding-right:10px">[test]</a></h4><blockquote><p><code>on_train_end</code>(<strong>**<code>kwargs</code></strong>)</p>
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<div class="collapse" id="SaveModelCallback-on_train_end-pytest"><div class="card card-body pytest_card"><a type="button" data-toggle="collapse" data-target="#SaveModelCallback-on_train_end-pytest" class="close" aria-label="Close"><span aria-hidden="true">×</span></a><p>No tests found for <code>on_train_end</code>. To contribute a test please refer to <a href="/dev/test.html">this guide</a> and <a href="https://forums.fast.ai/t/improving-expanding-functional-tests/32929">this discussion</a>.</p></div></div><p>Load the best model.</p>
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<h2 id="ReduceLROnPlateauCallback" class="doc_header"><code>class</code> <code>ReduceLROnPlateauCallback</code><a href="https://github.com/fastai/fastai/blob/master/fastai/callbacks/tracker.py#L106" class="source_link" style="float:right">[source]</a><a class="source_link" data-toggle="collapse" data-target="#ReduceLROnPlateauCallback-pytest" style="float:right; padding-right:10px">[test]</a></h2><blockquote><p><code>ReduceLROnPlateauCallback</code>(<strong><code>learn</code></strong>:<a href="/basic_train.html#Learner"><code>Learner</code></a>, <strong><code>monitor</code></strong>:<code>str</code>=<strong><em><code>'val_loss'</code></em></strong>, <strong><code>mode</code></strong>:<code>str</code>=<strong><em><code>'auto'</code></em></strong>, <strong><code>patience</code></strong>:<code>int</code>=<strong><em><code>0</code></em></strong>, <strong><code>factor</code></strong>:<code>float</code>=<strong><em><code>0.2</code></em></strong>, <strong><code>min_delta</code></strong>:<code>int</code>=<strong><em><code>0</code></em></strong>) :: <a href="/callbacks.tracker.html#TrackerCallback"><code>TrackerCallback</code></a></p>
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<div class="collapse" id="ReduceLROnPlateauCallback-pytest"><div class="card card-body pytest_card"><a type="button" data-toggle="collapse" data-target="#ReduceLROnPlateauCallback-pytest" class="close" aria-label="Close"><span aria-hidden="true">×</span></a><p>No tests found for <code>ReduceLROnPlateauCallback</code>. To contribute a test please refer to <a href="/dev/test.html">this guide</a> and <a href="https://forums.fast.ai/t/improving-expanding-functional-tests/32929">this discussion</a>.</p></div></div><p>A <a href="/callbacks.tracker.html#TrackerCallback"><code>TrackerCallback</code></a> that reduces learning rate when a metric has stopped improving.</p>
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<p>This callback tracks the quantity in <code>monitor</code> during the training of <code>learn</code>. <code>mode</code> can be forced to 'min' or 'max' but will automatically try to determine if the quantity should be the lowest possible (validation loss) or the highest possible (accuracy). Will reduce the learning rate by <code>factor</code> after <code>patience</code> epochs if the quantity hasn't improved by <code>min_delta</code>.</p>
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<h3 id="Callback-methods">Callback methods<a class="anchor-link" href="#Callback-methods">¶</a></h3>
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<p>You don't call these yourself - they're called by fastai's <a href="/callback.html#Callback"><code>Callback</code></a> system automatically to enable the class's functionality.</p>
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<h4 id="ReduceLROnPlateauCallback.on_train_begin" class="doc_header"><code>on_train_begin</code><a href="https://github.com/fastai/fastai/blob/master/fastai/callbacks/tracker.py#L114" class="source_link" style="float:right">[source]</a><a class="source_link" data-toggle="collapse" data-target="#ReduceLROnPlateauCallback-on_train_begin-pytest" style="float:right; padding-right:10px">[test]</a></h4><blockquote><p><code>on_train_begin</code>(<strong>**<code>kwargs</code></strong>:<code>Any</code>)</p>
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<div class="collapse" id="ReduceLROnPlateauCallback-on_train_begin-pytest"><div class="card card-body pytest_card"><a type="button" data-toggle="collapse" data-target="#ReduceLROnPlateauCallback-on_train_begin-pytest" class="close" aria-label="Close"><span aria-hidden="true">×</span></a><p>No tests found for <code>on_train_begin</code>. To contribute a test please refer to <a href="/dev/test.html">this guide</a> and <a href="https://forums.fast.ai/t/improving-expanding-functional-tests/32929">this discussion</a>.</p></div></div><p>Initialize inner arguments.</p>
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<h4 id="ReduceLROnPlateauCallback.on_epoch_end" class="doc_header"><code>on_epoch_end</code><a href="https://github.com/fastai/fastai/blob/master/fastai/callbacks/tracker.py#L119" class="source_link" style="float:right">[source]</a><a class="source_link" data-toggle="collapse" data-target="#ReduceLROnPlateauCallback-on_epoch_end-pytest" style="float:right; padding-right:10px">[test]</a></h4><blockquote><p><code>on_epoch_end</code>(<strong><code>epoch</code></strong>, <strong>**<code>kwargs</code></strong>:<code>Any</code>)</p>
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<div class="collapse" id="ReduceLROnPlateauCallback-on_epoch_end-pytest"><div class="card card-body pytest_card"><a type="button" data-toggle="collapse" data-target="#ReduceLROnPlateauCallback-on_epoch_end-pytest" class="close" aria-label="Close"><span aria-hidden="true">×</span></a><p>No tests found for <code>on_epoch_end</code>. To contribute a test please refer to <a href="/dev/test.html">this guide</a> and <a href="https://forums.fast.ai/t/improving-expanding-functional-tests/32929">this discussion</a>.</p></div></div><p>Compare the value monitored to its best and maybe reduce lr.</p>
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<h2 id="TrackerCallback" class="doc_header"><code>class</code> <code>TrackerCallback</code><a href="https://github.com/fastai/fastai/blob/master/fastai/callbacks/tracker.py#L23" class="source_link" style="float:right">[source]</a><a class="source_link" data-toggle="collapse" data-target="#TrackerCallback-pytest" style="float:right; padding-right:10px">[test]</a></h2><blockquote><p><code>TrackerCallback</code>(<strong><code>learn</code></strong>:<a href="/basic_train.html#Learner"><code>Learner</code></a>, <strong><code>monitor</code></strong>:<code>str</code>=<strong><em><code>'val_loss'</code></em></strong>, <strong><code>mode</code></strong>:<code>str</code>=<strong><em><code>'auto'</code></em></strong>) :: <a href="/basic_train.html#LearnerCallback"><code>LearnerCallback</code></a></p>
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<div class="collapse" id="TrackerCallback-pytest"><div class="card card-body pytest_card"><a type="button" data-toggle="collapse" data-target="#TrackerCallback-pytest" class="close" aria-label="Close"><span aria-hidden="true">×</span></a><p>No tests found for <code>TrackerCallback</code>. To contribute a test please refer to <a href="/dev/test.html">this guide</a> and <a href="https://forums.fast.ai/t/improving-expanding-functional-tests/32929">this discussion</a>.</p></div></div><p>A <a href="/basic_train.html#LearnerCallback"><code>LearnerCallback</code></a> that keeps track of the best value in <code>monitor</code>.</p>
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<h4 id="TrackerCallback.get_monitor_value" class="doc_header"><code>get_monitor_value</code><a href="https://github.com/fastai/fastai/blob/master/fastai/callbacks/tracker.py#L39" class="source_link" style="float:right">[source]</a><a class="source_link" data-toggle="collapse" data-target="#TrackerCallback-get_monitor_value-pytest" style="float:right; padding-right:10px">[test]</a></h4><blockquote><p><code>get_monitor_value</code>()</p>
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<div class="collapse" id="TrackerCallback-get_monitor_value-pytest"><div class="card card-body pytest_card"><a type="button" data-toggle="collapse" data-target="#TrackerCallback-get_monitor_value-pytest" class="close" aria-label="Close"><span aria-hidden="true">×</span></a><p>No tests found for <code>get_monitor_value</code>. To contribute a test please refer to <a href="/dev/test.html">this guide</a> and <a href="https://forums.fast.ai/t/improving-expanding-functional-tests/32929">this discussion</a>.</p></div></div><p>Pick the monitored value.</p>
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<h3 id="Callback-methods">Callback methods<a class="anchor-link" href="#Callback-methods">¶</a></h3>
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<p>You don't call these yourself - they're called by fastai's <a href="/callback.html#Callback"><code>Callback</code></a> system automatically to enable the class's functionality.</p>
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<h4 id="TrackerCallback.on_train_begin" class="doc_header"><code>on_train_begin</code><a href="https://github.com/fastai/fastai/blob/master/fastai/callbacks/tracker.py#L35" class="source_link" style="float:right">[source]</a><a class="source_link" data-toggle="collapse" data-target="#TrackerCallback-on_train_begin-pytest" style="float:right; padding-right:10px">[test]</a></h4><blockquote><p><code>on_train_begin</code>(<strong>**<code>kwargs</code></strong>:<code>Any</code>)</p>
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<div class="collapse" id="TrackerCallback-on_train_begin-pytest"><div class="card card-body pytest_card"><a type="button" data-toggle="collapse" data-target="#TrackerCallback-on_train_begin-pytest" class="close" aria-label="Close"><span aria-hidden="true">×</span></a><p>No tests found for <code>on_train_begin</code>. To contribute a test please refer to <a href="/dev/test.html">this guide</a> and <a href="https://forums.fast.ai/t/improving-expanding-functional-tests/32929">this discussion</a>.</p></div></div><p>Initializes the best value.</p>
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