Strength the shape inference for aten.arange-like op by
1. registering aten.sub and aten.ceil.Scalar op and design folders for them.
2. register a new constant-like op: Torch::ConstantNumberOp and design canonicalizer for it.
This PR adds an `AllowedInModuleInitializer` trait to keep track of ops that are permitted in the module initializer. We have a handful of such ops that are produced by the IValue importer, and so this change avoids maintaining a list of ops in `TorchOps.cpp` that could lead to spurious merge conflicts, and help us integrate torch-mlir in our downstream compiler better. Please let me know if you'd prefer a better name for the trait itself. Feedback is welcome!
Previously we `sudo rm -f` the non-universal zstd installed in the GHA. The CI has this fix but it doesn't take effect in the Release builds without this change.
As @oroppas identified, literal strings that are over 16,380 characters
cause the MSVC compiler to throw an error (C2026), eventually causing
the Windows build of Torch-MLIR to fail because the length of the
generated MLIR for the shape library crosses the allowed threshold.
This patch fixes the problem by making the Python script generate one
literal string per line to satisfy the MSVC compiler.
Thanks to @oroppas for the bulk of the effort required to resolve this!
Addresses leftover comment from earlier PRs: #1254 , #1265 to remove `torch_dispatch` frontend. In addition, moves the main arch diagram into `docs/` directory for consistency.
Summary of changes:
- Updated emitAccessorPrefix since the default value has changed
(https://reviews.llvm.org/D133179)
- Updated RefineTypes pass since Lattice::isUninitialized() is removed
(https://reviews.llvm.org/D132800)
- Updated MHLO tag so that it builds with the updated LLVM tag
- Disabled two tests that cause segfaults in the TOSA backend (see Issue
#1361)
It seems as though an upstream change in PyTorch has caused the module
dump to include not just the module being tested, but also several
seemingly unrelated functions in the `torch._decom.decompositions`
namespace. The presence of these new functions caused lit to match
variables against incorrect statements (i.e. statements in the
unrelated functions instead of the module under test).
This patch inserts `CHECK-LABEL` statements in the failing tests so that
lit ignores these unrelated functions and only checks the statements at
or after the test module definition.
* Add aten.frobenius_norm.dim op and init its conversion pattern to linalg and MHLO,
* run symbolic-shape-optimization before hlo-legalize-to-linalg to fit more mhlo e2e tests.
Summary of changes:
- Update the dataflow analysis in RefineTypes.cpp
- Add tosa-to-arith pass after tosa-to-linalg pass, since
tosa-to-linalg (and canonicalizations) can produce tosa.const() ops
- Fixed warning about not making `matchAndRewrite` as override
This commit adds decomposition of `aten.linear` op. Due to limited
support at tosa backend in case of dynamic dimensions, this
decomposition is currently disabled for tosa backend.
Signed-Off-by: Gaurav Shukla <gaurav@nod-labs.com>
* Move CIs to use docker builds
Now that #1234 has landed and anyone can run CI / Release builds locally move GHA to use the same flow.
* update names
* Update comments
We added both ipc=host and explicit ulimits. This _may_ be causing slow downs on GHA. Remove the ulimit setting still passes all the CI tests locally. `--ipc=host` is still required.
The new logic has the following benefits:
1. It does not clobber the working tree state. We expect testing to not
change the work tree.
2. It correctly handles the case where a user has changes to the
generated files, but hasn't checked them in yet (this happens
frequently when adding new ops).
- Update MHLO commit to build with LLVM commit hash 00d648bd
- Update TorchToMhlo code to work with Stablehlo
- Re-enabled two failing TOSA tests, thus resolving Github Issue #1231
Caught in the wild here:
https://github.com/llvm/torch-mlir/runs/8046660640?check_suite_focus=true
It is common for a missing dependency to only surface as an issue on the
CI machines since they have fewer cores which prevents a "race" that
happens to cause the dependency to be built before the dependent.
Vivek Khandelwal
武家伟
Jae Hoon (Antonio) Kim
Sambhav Jain
Ashay Rane
powderluv
long.chen
Sean Silva
gpetters94
Tanyo Kwok
Sambhav Jain
Gaurav Shukla
Quinn Dawkins
JakopinA
Jacques Pienaar