mirror of https://github.com/llvm/torch-mlir
Sort tests before anything else.
In the sequential case we weren't sorting, which was confusing.pull/1314/head
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e16b43e20b
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079bff33f1
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@ -341,6 +341,9 @@ def run_tests(tests: List[Test], config: TestConfig, sequential=False, verbose=F
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if mp.cpu_count() == 2:
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num_processes = 1
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# Sort the tests to make output nicer.
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tests = list(sorted(tests, key=lambda t: t.unique_name))
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# TODO: If num_processes == 1, then run without any of the multiprocessing
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# machinery. In theory it should work, but any crash in the testing process
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# seems to cause a cascade of failures resulting in undecipherable error
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@ -348,9 +351,6 @@ def run_tests(tests: List[Test], config: TestConfig, sequential=False, verbose=F
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if num_processes == 1 or sequential:
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return [compile_and_run_test(test, config, verbose) for test in tests]
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# Sort the tests to make output nicer.
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tests = list(sorted(tests, key=lambda t: t.unique_name))
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# To run e2e tests in parallel:
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# The tests are put into a synchronized queue. Multiple worker processes are
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# created. Each worker takes one test at a time from the queue to compile
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