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William Falcon
2019-08-13 15:21:24 -05:00
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<p>[<a href="https://github.com/williamFalcon/pytorch-lightning/blob/master/pytorch_lightning/models/trainer.py">Github Code</a>]</p>
<p>The lightning trainer abstracts best practices for running a training, val, test routine. It calls parts of your model when it wants to hand over full control and otherwise makes training assumptions which are now standard practice in AI research.</p>
<p>This is the basic use of the trainer:</p>
<pre><code class="python">from pytorch_lightning import Trainer
<table class="codehilitetable"><tr><td class="linenos"><div class="linenodiv"><pre>1
2
3
4
5
6</pre></div></td><td class="code"><div class="codehilite"><pre><span></span><span class="kn">from</span> <span class="nn">pytorch_lightning</span> <span class="kn">import</span> <span class="n">Trainer</span>
model = LightningTemplate()
<span class="n">model</span> <span class="o">=</span> <span class="n">LightningTemplate</span><span class="p">()</span>
trainer = Trainer()
trainer.fit(model)
</code></pre>
<span class="n">trainer</span> <span class="o">=</span> <span class="n">Trainer</span><span class="p">()</span>
<span class="n">trainer</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">model</span><span class="p">)</span>
</pre></div>
</td></tr></table>
<p>But of course the fun is in all the advanced things it can do:</p>
<p><strong>Checkpointing</strong> </p>