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Enable precision autocast for LightningModule step methods in Fabric #17439

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merged 4 commits into from
Apr 24, 2023
Merged

Enable precision autocast for LightningModule step methods in Fabric #17439

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41f3f49
fix
awaelchli Apr 22, 2023
09247fc
chlog
Borda Apr 24, 2023
150fe8a
Merge branch 'master' into bugfix/fabric-lm-autocast
awaelchli Apr 24, 2023
fb3c150
Merge branch 'master' into bugfix/fabric-lm-autocast
awaelchli Apr 24, 2023
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4 changes: 4 additions & 0 deletions src/lightning/fabric/CHANGELOG.md
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Expand Up @@ -40,6 +40,10 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).

- Increased the minimum XLA requirement to 1.13 ([#17368](https://github.com/Lightning-AI/lightning/pull/17368))


- Enable precision autocast for LightningModule step methods in Fabric ([#17439](https://github.com/Lightning-AI/lightning/pull/17439))


### Deprecated

-
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2 changes: 1 addition & 1 deletion src/lightning/fabric/wrappers.py
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Expand Up @@ -154,7 +154,7 @@ def wrapped_forward(*args: Any, **kwargs: Any) -> Any:
def call_forward_module(*args: Any, **kwargs: Any) -> Any:
# Patch the original_module's forward so we can redirect the arguments back to the real method
self._original_module.forward = wrapped_forward
return self._forward_module(*args, **kwargs)
return self.forward(*args, **kwargs)

return call_forward_module

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5 changes: 4 additions & 1 deletion tests/tests_fabric/test_wrappers.py
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Expand Up @@ -21,6 +21,7 @@
from torch.utils.data.dataloader import DataLoader

from lightning.fabric.fabric import Fabric
from lightning.fabric.plugins import Precision
from lightning.fabric.utilities.device_dtype_mixin import _DeviceDtypeModuleMixin
from lightning.fabric.wrappers import _FabricDataLoader, _FabricModule, _FabricOptimizer, is_wrapped
from tests_fabric.helpers.runif import RunIf
Expand Down Expand Up @@ -417,9 +418,10 @@ def validation_step(self, arg, kwarg=None):
def normal_method(self):
pass

precision = Mock(wraps=Precision())
original_module = LightningModule()
forward_module = DDP(original_module)
fabric_module = _FabricModule(forward_module=forward_module, precision=Mock(), original_module=original_module)
fabric_module = _FabricModule(forward_module=forward_module, precision=precision, original_module=original_module)

# Regular methods on the original_module are visible and identical on the fabric_module ...
assert fabric_module.normal_method == original_module.normal_method
Expand All @@ -441,6 +443,7 @@ def normal_method(self):
assert fabric_module.training_step("train_arg", kwarg="train_kwarg") == "training_step_return"
assert fabric_module.training_step("train_arg", kwarg="train_kwarg") == "training_step_return" # call 2nd time
assert fabric_module.validation_step("val_arg", kwarg="val_kwarg") == "validation_step_return"
precision.forward_context.assert_called()

# The forward method remains untouched/unpatched after the special methods have been called
assert original_module.forward.__name__ == "forward"
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