mirror of https://github.com/llvm/torch-mlir
fix typos
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39de4d6265
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@ -146,7 +146,7 @@ object as the second argument. The `TestUtils` has some methods, such as
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and
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[`tu.randint`](https://github.com/llvm/torch-mlir/blob/8e880a2d009b67d45fb07434ab62ec2066a11185/python/torch_mlir_e2e_test/torchscript/framework.py#L185),
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that allow the creation of random tensors in a way that makes sure the compiled
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module and the golden trace recieve the same tensors as input. Therefore, all
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module and the golden trace receive the same tensors as input. Therefore, all
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random inputs should be generated through the `TestUtils` object.
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@ -325,7 +325,7 @@ blend of the benefits of the other two.
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All the backends are implemented using the MLIR [Dialect Conversion
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infrastructure](https://mlir.llvm.org/docs/DialectConversion/). This involves
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converting the `torch` dialect types to other types, so we closely follow the
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principes from the "Type Conversions the Not-So-Hard Way" talk
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principles from the "Type Conversions the Not-So-Hard Way" talk
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([slides](https://drive.google.com/file/d/1FVbzCXxZzS9LBLuvpPNLWJD-XDkt54ky/view?usp=sharing),
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[recording](https://drive.google.com/file/d/1VfVajitgf8ZPnd-HRkJvaJiFLhBsluXN/view?usp=sharing)).
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We follow the standard `{include,lib}/Conversion/TorchTo*` convention used in
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@ -396,7 +396,7 @@ Because of this, many Torch-MLIR patches adding support for new ops have no
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`.mlir` unit tests, and only include end-to-end test(s). We generally make sure
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that our end-to-end tests are as targeted as possible. As a result, when
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debugging end-to-end test failures, the resulting reproducers (which our test
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framework automaticaly produces for failures) are usually already fully reduced
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framework automatically produces for failures) are usually already fully reduced
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test cases.
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### Do's and Don'ts for unit vs end-to-end testing.
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@ -273,7 +273,7 @@ docker build -t your-name/torch-mlir-ci --no-cache .
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### Other configurable environmental variables
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The following additional environmental variables can be used to customie your docker build:
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The following additional environmental variables can be used to customize your docker build:
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* Custom Release Docker image:
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Defaults to `stellaraccident/manylinux2014_x86_64-bazel-5.1.0:latest`
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