2021-06-01 15:21:17 +00:00
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# Copyright The PyTorch Lightning team.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import pytest
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import torch
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from torch.nn import DataParallel
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from pytorch_lightning.overrides.base import (
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_LightningModuleWrapperBase,
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_LightningPrecisionModuleWrapperBase,
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unwrap_lightning_module,
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)
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from tests.helpers import BoringModel
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2021-07-26 11:37:35 +00:00
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@pytest.mark.parametrize("wrapper_class", [_LightningModuleWrapperBase, _LightningPrecisionModuleWrapperBase])
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2021-06-01 15:21:17 +00:00
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def test_wrapper_device_dtype(wrapper_class):
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model = BoringModel()
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wrapped_model = wrapper_class(model)
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wrapped_model.to(dtype=torch.float16)
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assert model.dtype == torch.float16
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def test_unwrap_lightning_module():
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model = BoringModel()
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wrapped_model = _LightningPrecisionModuleWrapperBase(model)
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wrapped_model = _LightningModuleWrapperBase(wrapped_model)
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wrapped_model = DataParallel(wrapped_model)
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assert unwrap_lightning_module(wrapped_model) == model
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