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William Falcon
2019-08-09 14:03:22 -05:00
parent d43f670f3c
commit caeca5da25
5 changed files with 22 additions and 18 deletions
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Trainer/Checkpointing/index.html
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<h1>Checkpointing</h1>
<p>Lightning can automate saving and loading checkpoints.</p>
<p>i Lightning can automate saving and loading checkpoints.</p>
<hr />
<h3 id="model-saving">Model saving</h3>
<p>To enable checkpointing, define the checkpoint callback and give it to the trainer.</p>
<pre><code class="python">from pytorch_lightning.utils.pt_callbacks import ModelCheckpoint
<pre><code class="python">from pytorch_lightning.callbacks import ModelCheckpoint
checkpoint_callback = ModelCheckpoint(
filepath='/path/to/store/weights.ckpt',
Trainer/Training Loop/index.html
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<hr />
<h4 id="gradient-clipping">Gradient Clipping</h4>
<p>Use this to turn off early stopping and run training to the <a href="#force-training-for-min-or-max-epochs">max_epoch</a></p>
<p>Gradient clipping may be enabled to avoid exploding gradients.
Specifically, this will <a href="https://pytorch.org/docs/stable/nn.html#torch.nn.utils.clip_grad_norm_">clip the gradient norm computed over all model parameters <em>together</em></a>.</p>
<pre><code class="python"># DEFAULT (ie: don't clip)
trainer = Trainer(gradient_clip=0)
# clip gradients with norm above 0.5
trainer = Trainer(gradient_clip=0.5)
</code></pre>
<hr />
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