mirror of https://github.com/llvm/torch-mlir
[cleanup] Use `"` instead of `'` for string literals
This is the more predominant style in the codebase. I'm sure there are more in other parts of the codebase but it's hard to search/replace.pull/1715/head snapshot-20221212.685
parent
d4862ec611
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a595942033
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@ -34,37 +34,37 @@ from torch_mlir_e2e_test.test_suite import register_all_tests
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register_all_tests()
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def _get_argparse():
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config_choices = ['native_torch', 'torchscript', 'linalg', 'mhlo', 'tosa', 'lazy_tensor_core', 'torchdynamo']
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parser = argparse.ArgumentParser(description='Run torchscript e2e tests.')
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parser.add_argument('-c', '--config',
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config_choices = ["native_torch", "torchscript", "linalg", "mhlo", "tosa", "lazy_tensor_core", "torchdynamo"]
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parser = argparse.ArgumentParser(description="Run torchscript e2e tests.")
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parser.add_argument("-c", "--config",
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choices=config_choices,
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default='linalg',
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help=f'''
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default="linalg",
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help=f"""
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Meaning of options:
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"linalg": run through torch-mlir's default Linalg-on-Tensors backend.
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"mhlo": run through torch-mlir's default MHLO backend.
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"tosa": run through torch-mlir's default TOSA backend.
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"linalg": run through torch-mlir"s default Linalg-on-Tensors backend.
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"mhlo": run through torch-mlir"s default MHLO backend.
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"tosa": run through torch-mlir"s default TOSA backend.
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"native_torch": run the torch.nn.Module as-is without compiling (useful for verifying model is deterministic; ALL tests should pass in this configuration).
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"torchscript": compile the model to a torch.jit.ScriptModule, and then run that as-is (useful for verifying TorchScript is modeling the program correctly).
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"lazy_tensor_core": run the model through the Lazy Tensor Core frontend and execute the traced graph.
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"torchdynamo": run the model through the TorchDynamo frontend and execute the graph using Linalg-on-Tensors.
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''')
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parser.add_argument('-f', '--filter', default='.*', help='''
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""")
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parser.add_argument("-f", "--filter", default=".*", help="""
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Regular expression specifying which tests to include in this run.
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''')
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parser.add_argument('-v', '--verbose',
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""")
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parser.add_argument("-v", "--verbose",
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default=False,
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action='store_true',
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help='report test results with additional detail')
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parser.add_argument('-s', '--sequential',
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action="store_true",
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help="report test results with additional detail")
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parser.add_argument("-s", "--sequential",
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default=False,
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action='store_true',
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help='''Run tests sequentially rather than in parallel.
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action="store_true",
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help="""Run tests sequentially rather than in parallel.
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This can be useful for debugging, since it runs the tests in the same process,
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which make it easier to attach a debugger or get a stack trace.''')
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parser.add_argument('--crashing_tests_to_not_attempt_to_run_and_a_bug_is_filed',
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metavar="TEST", type=str, nargs='+',
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help='A set of tests to not attempt to run, since they crash and cannot be XFAILed.')
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which make it easier to attach a debugger or get a stack trace.""")
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parser.add_argument("--crashing_tests_to_not_attempt_to_run_and_a_bug_is_filed",
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metavar="TEST", type=str, nargs="+",
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help="A set of tests to not attempt to run, since they crash and cannot be XFAILed.")
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return parser
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def main():
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@ -74,25 +74,25 @@ def main():
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test.unique_name for test in GLOBAL_TEST_REGISTRY)
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# Find the selected config.
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if args.config == 'linalg':
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if args.config == "linalg":
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config = LinalgOnTensorsBackendTestConfig(RefBackendLinalgOnTensorsBackend())
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xfail_set = LINALG_XFAIL_SET
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if args.config == 'tosa':
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if args.config == "tosa":
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config = TosaBackendTestConfig(LinalgOnTensorsTosaBackend())
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xfail_set = all_test_unique_names - TOSA_PASS_SET
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if args.config == 'mhlo':
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if args.config == "mhlo":
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config = MhloBackendTestConfig(LinalgOnTensorsMhloBackend())
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xfail_set = all_test_unique_names - MHLO_PASS_SET
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elif args.config == 'native_torch':
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elif args.config == "native_torch":
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config = NativeTorchTestConfig()
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xfail_set = {}
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elif args.config == 'torchscript':
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elif args.config == "torchscript":
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config = TorchScriptTestConfig()
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xfail_set = {}
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elif args.config == 'lazy_tensor_core':
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elif args.config == "lazy_tensor_core":
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config = LazyTensorCoreTestConfig()
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xfail_set = LTC_XFAIL_SET
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elif args.config == 'torchdynamo':
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elif args.config == "torchdynamo":
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config = TorchDynamoTestConfig()
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xfail_set = TORCHDYNAMO_XFAIL_SET
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@ -101,7 +101,7 @@ def main():
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if args.crashing_tests_to_not_attempt_to_run_and_a_bug_is_filed is not None:
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for arg in args.crashing_tests_to_not_attempt_to_run_and_a_bug_is_filed:
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if arg not in all_test_unique_names:
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print(f'ERROR: --crashing_tests_to_not_attempt_to_run_and_a_bug_is_filed argument "{arg}" is not a valid test name')
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print(f"ERROR: --crashing_tests_to_not_attempt_to_run_and_a_bug_is_filed argument '{arg}' is not a valid test name")
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sys.exit(1)
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# Find the selected tests, and emit a diagnostic if none are found.
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@ -111,9 +111,9 @@ def main():
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]
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if len(tests) == 0:
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print(
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f'ERROR: the provided filter {args.filter!r} does not match any tests'
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f"ERROR: the provided filter {args.filter!r} does not match any tests"
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)
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print('The available tests are:')
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print("The available tests are:")
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for test in available_tests:
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print(test.unique_name)
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sys.exit(1)
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@ -132,6 +132,6 @@ def _suppress_warnings():
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warnings.filterwarnings("ignore",
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message="A builtin ctypes object gave a PEP3118 format string that does not match its itemsize")
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if __name__ == '__main__':
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if __name__ == "__main__":
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_suppress_warnings()
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main()
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