52 lines
1.9 KiB
Python
52 lines
1.9 KiB
Python
# Copyright The Lightning AI 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 os
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from unittest import mock
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import torch
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from lightning.pytorch import Trainer
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from lightning.pytorch.accelerators import XLAAccelerator
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from lightning.pytorch.demos.boring_classes import BoringModel
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from lightning.pytorch.strategies import XLAStrategy
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from tests_pytorch.helpers.runif import RunIf
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class BoringModelTPU(BoringModel):
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def on_train_start(self) -> None:
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from torch_xla.experimental import pjrt
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index = 0 if pjrt.using_pjrt() else 1
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# assert strategy attributes for device setting
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assert self.device == torch.device("xla", index=index)
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assert os.environ.get("PT_XLA_DEBUG") == "1"
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@RunIf(tpu=True, standalone=True)
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@mock.patch.dict(os.environ, os.environ.copy(), clear=True)
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def test_xla_strategy_debug_state():
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"""Tests if device/debug flag is set correctly when training and after teardown for XLAStrategy."""
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model = BoringModelTPU()
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from torch_xla.experimental import pjrt
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trainer_kwargs = {}
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if not pjrt.using_pjrt():
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# only XRT supports XLA with a single process
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trainer_kwargs["devices"] = 1
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trainer = Trainer(fast_dev_run=True, strategy=XLAStrategy(debug=True), **trainer_kwargs)
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assert isinstance(trainer.accelerator, XLAAccelerator)
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assert isinstance(trainer.strategy, XLAStrategy)
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trainer.fit(model)
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assert "PT_XLA_DEBUG" not in os.environ
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