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When only all-dense "sparse" tensors occur in a function prototype, the
assembler would skip the method conversion purely based on input/output
counts. It should rewrite based on the presence of any annotation,
however.
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instead use "sparsifier" (#71875)
The changes in this p.r. mostly center around the tests that use the
flag sparse_compiler (also: sparse-compiler).
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When the Powers That Be decided that the name "sparse compiler" should
be changed to "sparsifier", we negected to change some of the comments
in the code; this pull request completes the name change.
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also typo fix
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Rationale:
This was actually just a pure "string based" test
with very little actual python usage. The output
sparse tensor was handled via the deprecated
convertFromMLIRSparseTensor method.
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This is an ongoing series of commits that are reformatting our
Python code.
Reformatting is done with `black`.
If you end up having problems merging this commit because you
have made changes to a python file, the best way to handle that
is to run git checkout --ours <yourfile> and then reformat it
with black.
If you run into any problems, post to discourse about it and
we will try to help.
RFC Thread below:
https://discourse.llvm.org/t/rfc-document-and-standardize-python-code-style
Differential Revision: https://reviews.llvm.org/D150782
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`PassManager.run` is currently restricted to running on `builtin.module`
ops, but this restriction doesn't exist on the C++ side. This updates it
to take `ir.Operation/OpView` instead of `ir.Module`.
Depends on D143354
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D143356
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The pipeline string must now include the pass manager's anchor op. This
makes the parse API properly roundtrip the printed form of a pass
manager.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D136405
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After https://reviews.llvm.org/D128593 this is not needed (and not available). Was missed in original landing because integration tests do not run on pre-merge.
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Reviewed By: bixia
Differential Revision: https://reviews.llvm.org/D123419
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Reviewed By: bixia
Differential Revision: https://reviews.llvm.org/D120347
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These routines will need to be specialized a lot more based on value types,
index types, pointer types, and permutation/dimension ordering. This is a
careful first step, providing some functionality needed in PyTACO bridge.
Reviewed By: bixia
Differential Revision: https://reviews.llvm.org/D120154
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Add convertFromMLIRSparseTensor to the supporting C shared library to convert
SparseTensorStorage to COO-flavor format.
Add Python routine sparse_tensor_to_coo_tensor to convert sparse tensor storage
pointer to numpy values for COO-flavor format tensor.
Add a Python test for sparse tensor output.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D115557
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