Add LightningLite documentation #10043
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tchaton
requested review from
awaelchli,
Borda,
carmocca,
edenlightning,
justusschock,
kaushikb11,
rohitgr7,
SeanNaren and
williamFalcon
as code owners
|
Build Error! No Linked Issue found. Please link an issue or mention it in the body using #<issue_id> |
tchaton
commented
Oct 20, 2021
tchaton
commented
Oct 21, 2021
|
Also, one more thing we could add to docs is How a User could power up their PyTorch Loops with DeepSpeed, Fairscale and XLA without dealing with their APIs. |
carmocca
reviewed
Oct 22, 2021
carmocca
reviewed
Oct 22, 2021
kaushikb11
reviewed
Oct 22, 2021
rohitgr7
approved these changes
Oct 22, 2021
Comment on lines
256
to
264
| def training_step(self, batch, batch_idx): | ||
| x = self.forward(batch) | ||
| self.log("train_loss", x) | ||
| return x | ||
|
|
||
| def validation_step(self, batch, batch_idx): | ||
| x = self.forward(batch) | ||
| self.log("val_loss", x) | ||
| return x |
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so trainer.predict will return losses? since it just return what forward returns by default.
rohitgr7
reviewed
Oct 22, 2021
|
Merging this now into POC. We can keep fine tuning it. |
|
Awesome!!! |
This was referenced Oct 25, 2021
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What does this PR do?
This PR adds documentation for
LightningLiteParts of #9987
Fixes #8620
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