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[docs] Add changes to e2e testing to long-term roadmap

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Sean Silva 2023-03-20 10:41:21 -07:00
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@ -246,3 +246,16 @@ for current LTC-based toolchains onto TorchDynamo. This migration will improve
the end-user experience since TorchDynamo is more seamless, but it is a
end-user-impacting migration nonetheless and we will want to phase it
appropriately with the community.
### End-to-end (E2E) testing
Torch-MLIR currently maintains its own test suite with
[hundreds of end-to-end tests](https://github.com/llvm/torch-mlir/tree/main/python/torch_mlir_e2e_test/test_suite)
that verify the correctness and completeness of our op lowerings.
These tests are tedious to write, and also sometimes hit corners
of PyTorch's API that aren't usually reachable by user code.
PyTorch already has an [end-to-end op test suite](https://github.com/pytorch/pytorch/blob/ead51864622467acd6835b6da86a166c1a32aa55/torch/testing/_internal/common_methods_invocations.py#L1)
and we should just plug into it. Here is [an example](https://github.com/pytorch/pytorch/blob/ead51864622467acd6835b6da86a166c1a32aa55/test/test_proxy_tensor.py#L1573) of doing so.
Even better, it would be great if TorchDynamo/PyTorch 2.0
directly provided a way to plug into this.