[pull] main from llvm:main #18
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* Update black version to support 3.11/3.12 * Reformat code
…3221) Signed-Off By: Vivek Khandelwal <[email protected]>
This scenario was uncovered in a downstream test that failed with a previous snapshot of torch-mlir. See https://github.com/cruise-automation/mlir-tcp/actions/runs/8605480116/job/23581829102?pr=65. ``` File "/home/runner/.cache/bazel/_bazel_runner/ce288f117ee4ca92dc028a6a28476a3d/sandbox/processwrapper-sandbox/2380/execroot/mlir-tcp/bazel-out/k8-opt-exec-2B5CBBC6/bin/test/AotCompile/broadcast_unit_dim_to_dynamic_with_unchanged_dim_dynamic_torch_exporter.runfiles/pip_deps_torch_mlir/site-packages/torch_mlir/extras/fx_importer.py", line 969, in value_info_to_type raise NotImplementedError( NotImplementedError: Could not deduce type from value info: tensor_meta=None, val=s1, sparsity=None ``` It seems to have resolved on current HEAD. Adding this test to ensure coverage in the future.
Set PyTorch and TorchVision version to nightly release 2024-04-28. Signed-Off By: Vivek Khandelwal <[email protected]>
The LTC Build was disabled in #3210 due to a regression in the packaging of the torch nightly wheels (pytorch/pytorch#124941) which is now resolved. So, re-enabling LTC build in this PR
iree tests `test_sinh` and `test_sinh_example` passed
iree tests `test_cosh` and `test_cosh_example` passed
iree tests `test_acosh` and `test_acosh_example` passed
iree tests `test_asinh` and `test_asinh_example` passed
iree tests `test_atanh` and `test_atanh_example` passed
1. Handle case stride == None 2. add avgpool3d maxpool1d maxpool3d lowering
I spent a little while debugging numerics issues with some tests similar to the ones in quantized_models.py, only to find that pytorch's quantized conv transpose is catastrophically inaccurate. I'll upstream the issue and only leave the tests here which are of the form quantize -> dequantize -> op.
…ailable (#3202) Co-authored-by: Xida Ren <[email protected]>
This is probably a decent PR for learning about blocks and regions. If you're here to learn about that, consider also looking at lib/Conversion/TorchToSCF/TorchToSCF.cpp While this doesn't include an e2e test, it is tested downstream in https://github.com/nod-ai/SHARK-TestSuite/blob/main/e2eshark/onnx/operators/If/model.py --------- Co-authored-by: Xida Ren <[email protected]>
The conversion of complex type wasn't supported or checked; the support and required tests were added. Fixes: iree-org/iree#17226 (comment)
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