95 lines
3.1 KiB
Python
95 lines
3.1 KiB
Python
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from unittest import mock
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import torch
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import pytest
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dp_16_args = """
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--max_epochs 1 \
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--batch_size 32 \
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--limit_train_batches 2 \
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--limit_val_batches 2 \
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--gpus 2 \
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--distributed_backend dp \
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--precision 16 \
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"""
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cpu_args = """
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--max_epochs 1 \
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--batch_size 32 \
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--limit_train_batches 2 \
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--limit_val_batches 2 \
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"""
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ddp_args = """
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--max_epochs 1 \
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--batch_size 32 \
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--limit_train_batches 2 \
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--limit_val_batches 2 \
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--gpus 2 \
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--precision 16 \
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"""
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# @pytest.mark.skipif(torch.cuda.device_count() < 2, reason="test requires multi-GPU machine")
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# @pytest.mark.parametrize('cli_args', [dp_16_args])
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# def test_examples_dp_mnist(cli_args):
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# from pl_examples.basic_examples.mnist import cli_main
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#
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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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# @pytest.mark.skipif(torch.cuda.device_count() < 2, reason="test requires multi-GPU machine")
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# @pytest.mark.parametrize('cli_args', [dp_16_args])
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# def test_examples_dp_image_classifier(cli_args):
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# from pl_examples.basic_examples.image_classifier import cli_main
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#
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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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#
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#
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# @pytest.mark.skipif(torch.cuda.device_count() < 2, reason="test requires multi-GPU machine")
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# @pytest.mark.parametrize('cli_args', [dp_16_args])
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# def test_examples_dp_autoencoder(cli_args):
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# from pl_examples.basic_examples.autoencoder import cli_main
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#
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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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# @pytest.mark.skipif(torch.cuda.device_count() < 2, reason="test requires multi-GPU machine")
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# @pytest.mark.parametrize('cli_args', [ddp_args])
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# def test_examples_ddp_mnist(cli_args):
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# from pl_examples.basic_examples.mnist import cli_main
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#
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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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#
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#
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# @pytest.mark.skipif(torch.cuda.device_count() < 2, reason="test requires multi-GPU machine")
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# @pytest.mark.parametrize('cli_args', [ddp_args])
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# def test_examples_ddp_image_classifier(cli_args):
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# from pl_examples.basic_examples.image_classifier import cli_main
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#
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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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#
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#
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# @pytest.mark.skipif(torch.cuda.device_count() < 2, reason="test requires multi-GPU machine")
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# @pytest.mark.parametrize('cli_args', [ddp_args])
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# def test_examples_ddp_autoencoder(cli_args):
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# from pl_examples.basic_examples.autoencoder import cli_main
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#
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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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#
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@pytest.mark.parametrize('cli_args', [cpu_args])
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def test_examples_cpu(cli_args):
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from pl_examples.basic_examples.mnist import cli_main as mnist_cli
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from pl_examples.basic_examples.image_classifier import cli_main as ic_cli
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from pl_examples.basic_examples.autoencoder import cli_main as ae_cli
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for cli_cmd in [mnist_cli, ic_cli, ae_cli]:
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with mock.patch("argparse._sys.argv", ["any.py"] + cli_args.strip().split()):
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cli_cmd()
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