Implementation of torch-to-linalg lowering of AtenOuterOp

[amemov]

An attempt to resolve #4093

Initial implementation:

• Defined the op in Linear.cpp

[amemov]

Hi, this is my first time contributing to the project - if you have any feedback or suggestions, I would really appreciate that.

[zjgarvey]

Thanks for picking this up.

There isn't any reason to include quantization logic for this op since it doesn't have any qdq fusion implemented in FuseQuantizedOps.cpp.

It would also be a bit better to implement this directly as a linalg.generic op, rather than unsqueezes and a matmul with a reduction dim size of 1. If you were to do the unsqueeze/matmul approach, it would be more appropriate to put this logic in DecomposeComplexOps.cpp.

Also, please do add e2e tests somewhere in ./projects/pt1/python/torch_mlir_e2e_test/test_suite/.

[zjgarvey]

After a change to the init tensor for the generic, I think this looks good!

Thanks for the changes.

[zjgarvey]

Also, be sure to run either pre-commit run --all (you will need to install it with pip install pre-commit) or git clang-format to auto format the files.

[amemov]

I changed it to the init tensor and ran pre-commit - everything looks good on my end.

[vivekkhandelwal1]

Hi @amemov, can you please take a look at the CI failure?

[amemov]

Hi @amemov, can you please take a look at the CI failure?

Hi @vivekkhandelwal1, I skimmed it briefly before - I didn't see any failures specifically related to torch.outer() lowering that I wrote and to my test case.

I will take a better look at it today, but so far I'm not really sure what exactly I need to modify / add here.

[vivekkhandelwal1]

Hi @amemov, can you please take a look at the CI failure?

Hi @vivekkhandelwal1, I skimmed it briefly before - I didn't see any failures specifically related to torch.outer() lowering that I wrote and to my test case.

I will take a better look at it today, but so far I'm not really sure what exactly I need to modify / add here.

Hi @amemov, some test(s) is/are crashing for the fx_importer config. Most probably, it will be the one that you have added. In order to find out which test is crashing you need to run the tests serially. You may use the following command:

python -m projects.pt1.e2e_testing.main --config=fx_importer -s

The above command will run all the tests one by one. And, the last test run will be the one that's crashing. Then, you can figure out the fix for that.

[amemov]

@vivekkhandelwal1
The problem was raised from the test file that I wrote:

torch-mlir/externals/llvm-project/llvm/include/llvm/Support/Casting.h:566: decltype(auto) llvm::cast(const From&) [with To = mlir::RankedTensorType; From = mlir::Type]: Assertion isa<To>(Val) && "cast<Ty>() argument of incompatible type!"' failed

I resolved it by changing the casting and dimensions for operands. On my machine, it now passes AttenOuter test.

[vivekkhandelwal1]

@amemov, a contributor has added the lowering for this same op through decomposition here: #4138.

Although your PR is old so in the case of conflict, you should get a chance to complete it, but their approach (via decomposition) is a better one. Can you and @ivanamitreski find a solution out of this?