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| author | wren romano <2998727+wrengr@users.noreply.github.com> | 2023-05-17 13:09:53 -0700 |
|---|---|---|
| committer | wren romano <2998727+wrengr@users.noreply.github.com> | 2023-05-17 14:24:09 -0700 |
| commit | a0615d020a02e252196383439e2c8143c6525e05 (patch) | |
| tree | aa308ef0e4c62d7dba3450f0eb4f8f1dffc0f57c /mlir/test/Integration/Dialect/SparseTensor/CPU/dense_output_f16.mlir | |
| parent | 4dc205f016e3dd2eb1182886a77676f24e39e329 (diff) | |
| download | llvm-a0615d020a02e252196383439e2c8143c6525e05.tar.gz | |
[mlir][sparse] Renaming the STEA field `dimLevelType` to `lvlTypes`
This commit is part of the migration of towards the new STEA syntax/design. In particular, this commit includes the following changes:
* Renaming compiler-internal functions/methods:
* `SparseTensorEncodingAttr::{getDimLevelType => getLvlTypes}`
* `Merger::{getDimLevelType => getLvlType}` (for consistency)
* `sparse_tensor::{getDimLevelType => buildLevelType}` (to help reduce confusion vs actual getter methods)
* Renaming external facets to match:
* the STEA parser and printer
* the C and Python bindings
* PyTACO
However, the actual renaming of the `DimLevelType` itself (along with all the "dlt" names) will be handled in a separate commit.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D150330
Diffstat (limited to 'mlir/test/Integration/Dialect/SparseTensor/CPU/dense_output_f16.mlir')
| -rw-r--r-- | mlir/test/Integration/Dialect/SparseTensor/CPU/dense_output_f16.mlir | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/dense_output_f16.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/dense_output_f16.mlir index 03b05b156418..411eca591c14 100644 --- a/mlir/test/Integration/Dialect/SparseTensor/CPU/dense_output_f16.mlir +++ b/mlir/test/Integration/Dialect/SparseTensor/CPU/dense_output_f16.mlir @@ -26,8 +26,8 @@ // REDEFINE: FileCheck %s // RUN: %{compile} | mlir-translate -mlir-to-llvmir | %{run} -#SparseVector = #sparse_tensor.encoding<{dimLevelType = ["compressed"]}> -#DenseVector = #sparse_tensor.encoding<{dimLevelType = ["dense"]}> +#SparseVector = #sparse_tensor.encoding<{lvlTypes = ["compressed"]}> +#DenseVector = #sparse_tensor.encoding<{lvlTypes = ["dense"]}> #trait_vec_op = { indexing_maps = [ |