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Reset val_dataloader in tuner/batch_size_scaling for binsearch #9975

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Oct 18, 2021
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Reset val_dataloader in tuner/batch_size_scaling for binsearch #9975

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2 changes: 2 additions & 0 deletions CHANGELOG.md
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Expand Up @@ -546,6 +546,8 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).

- Fixed issue with non-init dataclass fields in `apply_to_collection` ([#9963](https://github.com/PyTorchLightning/pytorch-lightning/issues/9963))

- Reset `val_dataloader` in `tuner/batch_size_scaling` for binsearch ([#9975](https://github.com/PyTorchLightning/pytorch-lightning/pull/9975))


## [1.4.9] - 2021-09-30

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1 change: 1 addition & 0 deletions pytorch_lightning/tuner/batch_size_scaling.py
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Expand Up @@ -205,6 +205,7 @@ def _run_binsearch_scaling(
if changed:
# Force the train dataloader to reset as the batch size has changed
trainer.reset_train_dataloader(model)
trainer.reset_val_dataloader(model)
else:
break

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5 changes: 3 additions & 2 deletions tests/tuner/test_scale_batch_size.py
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Expand Up @@ -274,10 +274,11 @@ def __init__(self):
trainer.tuner.scale_batch_size(model, mode="ThisModeDoesNotExist")


def test_dataloader_reset_with_scale_batch_size(tmpdir):
@pytest.mark.parametrize("scale_method", ["power", "binsearch"])
def test_dataloader_reset_with_scale_batch_size(tmpdir, scale_method):
"""Test that train and val dataloaders are reset at every update in scale batch size."""
model = BatchSizeModel(batch_size=16)
scale_batch_size_kwargs = {"max_trials": 5, "init_val": 4}
scale_batch_size_kwargs = {"max_trials": 5, "init_val": 4, "mode": scale_method}

trainer = Trainer(max_epochs=2, auto_scale_batch_size=True)
new_batch_size = trainer.tune(model, scale_batch_size_kwargs=scale_batch_size_kwargs)["scale_batch_size"]
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