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Summary: This PR adds a couple very simple tests which (as the code comment says) measure the time it takes to `import torch` and ask for the CUDA device count. Pull Request resolved: https://github.com/pytorch/pytorch/pull/56041 Test Plan: ``` $ rm -r /tmp/reports ; python3 test/test_import_time.py --save-xml=/tmp/reports Running tests... ---------------------------------------------------------------------- .. ---------------------------------------------------------------------- Ran 2 tests in 1.855s OK Generating XML reports... ``` ``` $ tools/print_test_stats.py /tmp/reports No scribe access token provided, skip sending report! class TestImportTime: tests: 2 failed: 0 skipped: 0 errored: 0 run_time: 1.85 seconds avg_time: 0.93 seconds median_time: 0.93 seconds 2 longest tests: test_time_cuda_device_count time: 1.10 seconds test_time_import_torch time: 0.75 seconds Total runtime is 0:00:01 2 longest tests of entire run: TestImportTime.test_time_cuda_device_count time: 1.10 seconds TestImportTime.test_time_import_torch time: 0.75 seconds ``` Reviewed By: driazati Differential Revision: D27770908 Pulled By: samestep fbshipit-source-id: 01bbf5a339f41d3a1f493e6fa8c946ff7567daec
20 lines
662 B
Python
20 lines
662 B
Python
from torch.testing._internal.common_utils import TestCase, run_tests
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# these tests could eventually be changed to fail if the import/init
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# time is greater than a certain threshold, but for now we just use them
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# as a way to track the duration of `import torch` in our ossci-metrics
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# S3 bucket (see tools/print_test_stats.py)
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class TestImportTime(TestCase):
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def test_time_import_torch(self):
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TestCase.runWithPytorchAPIUsageStderr('import torch')
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def test_time_cuda_device_count(self):
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TestCase.runWithPytorchAPIUsageStderr(
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'import torch; torch.cuda.device_count()',
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)
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if __name__ == '__main__':
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run_tests()
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