mirror of https://github.com/llvm/torch-mlir
Document requirements for `torch_mlir_e2e_test` (#3722)
This documents which CMake options must be set to be able to use `torch_mlir_e2e_test`, required e.g. for `projects/pt1/tools/e2e_test.sh`. Makes progress on #3696. Closes #3719.pull/3730/head
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@ -109,6 +109,15 @@ cmake -GNinja -Bbuild \
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-DLLVM_ENABLE_ASSERTIONS=ON \
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```
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#### Flags to run end-to-end tests:
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Running the end-to-end execution tests locally requires enabling the native PyTorch extension features and the JIT IR importer, which depends on the
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former and defaults to `ON` if not changed:
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```shell
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-DTORCH_MLIR_ENABLE_PYTORCH_EXTENSIONS=ON \
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-DTORCH_MLIR_ENABLE_JIT_IR_IMPORTER=ON \
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```
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### Building against a pre-built LLVM
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If you have built llvm-project separately in the directory `$LLVM_INSTALL_DIR`, you can also build the project *out-of-tree* using the following command as template:
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@ -396,6 +405,8 @@ Torch-MLIR has two types of tests:
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a homegrown testing framework (see
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`projects/pt1/python/torch_mlir_e2e_test/framework.py`) and the test suite
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lives at `projects/pt1/python/torch_mlir_e2e_test/test_suite/__init__.py`.
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The tests require to build with `TORCH_MLIR_ENABLE_PYTORCH_EXTENSIONS` (and
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the dependent option `TORCH_MLIR_ENABLE_JIT_IR_IMPORTER`) set to `ON`.
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2. Compiler and Python API unit tests. These use LLVM's `lit` testing framework.
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For example, these might involve using `torch-mlir-opt` to run a pass and
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