GPU and TPU usage guide #826
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gsamaras
requested review from
hrzn,
tomasvanpottelbergh,
dennisbader and
brunnedu
as code owners
docs/userguide/gpu_and_tpu_usage.md
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| Now the model is ready to start predicting, which won't be shown here since it's included in the example linked in the start of this guide. | ||
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| ## Use a GPU | ||
| GPUs can dramatically improve the performance of your model in terms of processing time. We only need to instruct our model to use our machine's GPU through PyTorch Lighnting Trainer parameters, which are expressed as the `pl_trainer_kwargs` dictionary, like this: |
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You could add a reference to the Pytorch Lightning doc (e.g. this page: https://pytorch-lightning.readthedocs.io/en/stable/common/trainer.html#accelerator) here.
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@hrzn yes, argh I knew I forgot sth, thanks! OK, so now I pushed the update in my cloned repo (gsamaras/darts). What I should do now? It seems like that change is already reflected in this pull request?
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Thanks! Basically there's nothing more to do on your side for now. We'll wait for the checks to finish and then merge your branch. Thanks for the contribution :)
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Fixes #808 .
Summary
As discussed, added a guide on how to use GPU and TPU with PyTorch Lightning. Also shows that a model uses CPU by default, based on an RNN example.
Other Information
[off-topic] The documentation has a typo in Timeseries here, which I corrected in this pull request.