43 lines
1.5 KiB
Python
43 lines
1.5 KiB
Python
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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 torch
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from pytorch_lightning import Trainer
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from pytorch_lightning.plugins import DDPSpawnPlugin
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from tests.helpers.boring_model import BoringModel
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from tests.helpers.runif import RunIf
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class BoringModelDDPCPU(BoringModel):
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def on_train_start(self) -> None:
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# make sure that the model is on CPU when training
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assert self.device == torch.device("cpu")
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@RunIf(skip_windows=True)
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def test_ddp_cpu():
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"""Tests if device is set correctely when training for DDPSpawnPlugin."""
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trainer = Trainer(num_processes=2, fast_dev_run=True)
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# assert training type plugin attributes for device setting
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assert isinstance(trainer.training_type_plugin, DDPSpawnPlugin)
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assert not trainer.training_type_plugin.on_gpu
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assert not trainer.training_type_plugin.on_tpu
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assert trainer.training_type_plugin.root_device == torch.device("cpu")
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model = BoringModelDDPCPU()
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trainer.fit(model)
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