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Fix tuner.scale_batch_size not finding batch size attribute when usin…
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,65 @@ | ||
| # Copyright The PyTorch Lightning team. | ||
| # | ||
| # Licensed under the Apache License, Version 2.0 (the "License"); | ||
| # you may not use this file except in compliance with the License. | ||
| # You may obtain a copy of the License at | ||
| # | ||
| # http://www.apache.org/licenses/LICENSE-2.0 | ||
| # | ||
| # Unless required by applicable law or agreed to in writing, software | ||
| # distributed under the License is distributed on an "AS IS" BASIS, | ||
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| # See the License for the specific language governing permissions and | ||
| # limitations under the License. | ||
| import pytest | ||
| from torch.utils.data import DataLoader | ||
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| from pytorch_lightning import Trainer | ||
| from pytorch_lightning.tuner.tuning import Tuner | ||
| from tests.helpers import BoringDataModule, BoringModel | ||
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| class BatchSizeDataModule(BoringDataModule): | ||
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| def __init__(self, batch_size=None): | ||
| super().__init__() | ||
| if batch_size is not None: | ||
| self.batch_size = batch_size | ||
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| def train_dataloader(self): | ||
| return DataLoader(self.random_train, batch_size=getattr(self, "batch_size", 1)) | ||
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| class BatchSizeModel(BoringModel): | ||
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| def __init__(self, batch_size=None): | ||
| super().__init__() | ||
| if batch_size is not None: | ||
| self.batch_size = batch_size | ||
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| @pytest.mark.parametrize( | ||
| "model,datamodule", [ | ||
| (BatchSizeModel(2), None), | ||
| (BatchSizeModel(2), BatchSizeDataModule(2)), | ||
| (BatchSizeModel(2), BatchSizeDataModule(None)), | ||
| (BatchSizeModel(None), BatchSizeDataModule(2)), | ||
| ] | ||
| ) | ||
| def test_scale_batch_size_method_with_model_or_datamodule(tmpdir, model, datamodule): | ||
| """ Test the tuner method `Tuner.scale_batch_size` with a datamodule. """ | ||
| trainer = Trainer( | ||
| default_root_dir=tmpdir, | ||
| limit_train_batches=1, | ||
| limit_val_batches=0, | ||
| max_epochs=1, | ||
| ) | ||
| tuner = Tuner(trainer) | ||
| new_batch_size = tuner.scale_batch_size( | ||
| model=model, mode="binsearch", init_val=4, max_trials=2, datamodule=datamodule | ||
| ) | ||
| assert new_batch_size == 16 | ||
| if hasattr(model, "batch_size"): | ||
| assert model.batch_size == 16 | ||
| if datamodule is not None and hasattr(datamodule, "batch_size"): | ||
| assert datamodule.batch_size == 16 |