45 lines
1.6 KiB
Python
45 lines
1.6 KiB
Python
# 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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from unittest import mock
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import pytest
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import torch
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from pl_examples import _DALI_AVAILABLE
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from pytorch_lightning.utilities.imports import _IS_WINDOWS
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ARGS_DEFAULT = (
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"--trainer.default_root_dir %(tmpdir)s "
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"--trainer.max_epochs 1 "
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"--trainer.limit_train_batches 2 "
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"--trainer.limit_val_batches 2 "
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"--trainer.limit_test_batches 2 "
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"--trainer.limit_predict_batches 2 "
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"--data.batch_size 32 "
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)
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ARGS_GPU = ARGS_DEFAULT + "--trainer.accelerator gpu --trainer.devices 1 "
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@pytest.mark.skipif(not _DALI_AVAILABLE, reason="Nvidia DALI required")
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@pytest.mark.skipif(not torch.cuda.is_available(), reason="CUDA required")
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@pytest.mark.skipif(_IS_WINDOWS, reason="Not supported on Windows")
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@pytest.mark.parametrize("cli_args", [ARGS_GPU])
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def test_examples_mnist_dali(tmpdir, cli_args):
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from pl_examples.integration_examples.dali_image_classifier import cli_main
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# update the temp dir
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cli_args = cli_args % {"tmpdir": tmpdir}
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with mock.patch("argparse._sys.argv", ["any.py"] + cli_args.strip().split()):
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cli_main()
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