mirror of https://github.com/llvm/torch-mlir
Fix test fails due to upstream PyTorch change (#793)
* Add to eager tests to xfail while they are fixed. Also XFAIL ConstantPad2dStaticModule_basic. * Fix test fails due to upstream PyTorch change.pull/798/head
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6b3d0b7e7a
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@ -63,7 +63,7 @@ def normalize_args_kwargs(target: Callable, args: Tuple[Any], kwargs: Dict[str,
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}
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}
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new_args_and_kwargs = normalize_function(
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new_args_and_kwargs = normalize_function(
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target, args, kwargs, arg_types, kwarg_types, normalize_to_only_use_kwargs=False
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target.op, args, kwargs, arg_types, kwarg_types, normalize_to_only_use_kwargs=False
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)
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)
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assert new_args_and_kwargs, "Couldn't normalize args and kwargs"
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assert new_args_and_kwargs, "Couldn't normalize args and kwargs"
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new_args, new_kwargs = new_args_and_kwargs
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new_args, new_kwargs = new_args_and_kwargs
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@ -15,6 +15,7 @@ COMMON_TORCH_MLIR_LOWERING_XFAILS = {
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"ConvolutionModule1D_basic",
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"ConvolutionModule1D_basic",
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"MaxPool2dWith3dInputModule_basic",
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"MaxPool2dWith3dInputModule_basic",
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"MaxPool2dWithIndicesWith3dInputModule_basic",
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"MaxPool2dWithIndicesWith3dInputModule_basic",
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"ConstantPad2dStaticModule_basic",
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}
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}
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def register_all_tests():
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def register_all_tests():
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