Comments (4)
Hi Stella,
Can you give a suggestion?
from torch-mlir.
Do you have a log you can share? That would help debug this. It seems like maybe CMake failed.
from torch-mlir.
@silvasean thanks. Let me re-produce locally and share whatever log I can find
from torch-mlir.
I figured out offline.
So for docker env I should use --build /build/npcomp
to which cmake_configure.sh writes build files. However I actually used --build build
which should be used in non-docker env.
Thanks @silvasean for your help anyway!
from torch-mlir.
Related Issues (20)
- [e2e testing] make e2e_testing/main.py print ir / more informative error messages
- Build failed on x86 MacOS
- `make_simple_dynamo_backend` does not work for single argument models. HOT 2
- Compilation of Quantized Model Failed HOT 1
- Missing dtype support for OnnxToTorch HOT 3
- Strange issue related to `pyproject.toml` when building release wheels HOT 4
- iree-compiler failed to compile gpt2
- `NotSupportedError` error when executing Readme example "TorchScript ResNet18"
- onnx.Transpose version 1 not lowered (but it's essentially the same as version 13)
- boolean indexing ops: AtenNonzeroOp, AtenIndexTensorOp, AtenMaskedSelectOp
- QuantizedMLP currently failing in CI
- migrate to from member `x.cast<T>()` to `mlir::cast<T>(x)` HOT 1
- Update version pin to onnx 1.16 HOT 4
- Include Shape Information Into DecomposeComplexOps Patterns HOT 4
- onnx.MatMul version 1 not lowered (but it's essentially the same as version 13)
- Crash with TorchBackendToLinalgOnTensorsBackendPipeline
- link out of date
- unsupported aten.meshgrid operator
- Trying to lower elided IR from torch onnx to torch causes crash HOT 2
- [ONNX] Systematically expand ONNX functions before conversion to Torch to avoid needing bespoke conversions HOT 10
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