[Mlir-commits] [mlir] 81d2892 - [mlir][sparse] Updating STEA documentation examples to use "lvlTypes"

wren romano llvmlistbot at llvm.org
Fri May 19 13:01:09 PDT 2023


Author: wren romano
Date: 2023-05-19T13:01:01-07:00
New Revision: 81d28921da8e7478689bdcd6da965138b01837bc

URL: https://github.com/llvm/llvm-project/commit/81d28921da8e7478689bdcd6da965138b01837bc
DIFF: https://github.com/llvm/llvm-project/commit/81d28921da8e7478689bdcd6da965138b01837bc.diff

LOG: [mlir][sparse] Updating STEA documentation examples to use "lvlTypes"

Followup to D150330.

Reviewed By: aartbik

Differential Revision: https://reviews.llvm.org/D150920

Added: 
    

Modified: 
    mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorAttrDefs.td

Removed: 
    


################################################################################
diff  --git a/mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorAttrDefs.td b/mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorAttrDefs.td
index 505231045aa8..f8a66b349874 100644
--- a/mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorAttrDefs.td
+++ b/mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorAttrDefs.td
@@ -144,11 +144,6 @@ def SparseTensorEncodingAttr : SparseTensor_Attr<"SparseTensorEncoding",
       properties, and split up how the level-format and properties are
       specified rather than using this suffix mechanism.
 
-      TODO: This field is called "dimLevelType" for historical reasons,
-      even though the types are per-level rather than per-dimension.
-      (This will be corrected in an upcoming change that completely
-      overhauls the syntax of this attribute.)
-
     - An optional permutation which maps (higher-ordering)-coordinates
       to level-coordinates; defaulting to the identity permutation.
       For example, given a 2-d tensor with the default higher-ordering,
@@ -213,19 +208,19 @@ def SparseTensorEncodingAttr : SparseTensor_Attr<"SparseTensorEncoding",
     ```mlir
     // Sparse vector.
     #SparseVector = #sparse_tensor.encoding<{
-      dimLevelType = [ "compressed" ]
+      lvlTypes = [ "compressed" ]
     }>
     ... tensor<?xf32, #SparseVector> ...
 
     // Sorted Coordinate Scheme.
     #SortedCOO = #sparse_tensor.encoding<{
-      dimLevelType = [ "compressed-nu", "singleton" ]
+      lvlTypes = [ "compressed-nu", "singleton" ]
     }>
     ... tensor<?x?xf64, #SortedCOO> ...
 
     // Doubly compressed sparse column storage with specific bitwidths.
     #DCSC = #sparse_tensor.encoding<{
-      dimLevelType = [ "compressed", "compressed" ],
+      lvlTypes = [ "compressed", "compressed" ],
       dimOrdering = affine_map<(i, j) -> (j, i)>,
       posWidth = 32,
       crdWidth = 8
@@ -234,7 +229,7 @@ def SparseTensorEncodingAttr : SparseTensor_Attr<"SparseTensorEncoding",
 
     // Block sparse row storage (2x3 blocks).
     #BCSR = #sparse_tensor.encoding<{
-      dimLevelType = [ "compressed", "compressed", "dense", "dense" ],
+      lvlTypes = [ "compressed", "compressed", "dense", "dense" ],
       dimOrdering  = affine_map<(ii, jj, i, j) -> (ii, jj, i, j)>,
       higherOrdering = affine_map<(i, j) -> (i floordiv 2, j floordiv 3, i mod 2, j mod 3)>
     }>
@@ -242,7 +237,7 @@ def SparseTensorEncodingAttr : SparseTensor_Attr<"SparseTensorEncoding",
 
     // ELL storage (4 jagged diagonals, i.e., at most 4 nonzeros per row).
     #ELL = #sparse_tensor.encoding<{
-      dimLevelType = [ "dense", "dense", "compressed" ],
+      lvlTypes = [ "dense", "dense", "compressed" ],
       dimOrdering  = affine_map<(ii, i, j) -> (ii, i, j)>,
       higherOrdering = affine_map<(i, j)[c] -> (c * 4 * i, i, j)>
     }>
@@ -251,7 +246,7 @@ def SparseTensorEncodingAttr : SparseTensor_Attr<"SparseTensorEncoding",
     // CSR slice (offset = 0, size = 4, stride = 1 on the first dimension;
     // offset = 0, size = 8, and a dynamic stride on the second dimension).
     #CSR_SLICE = #sparse_tensor.encoding<{
-      dimLevelType = [ "dense", "compressed" ],
+      lvlTypes = [ "dense", "compressed" ],
       slice = [ (0, 4, 1), (0, 8, ?) ]
     }>
     ... tensor<?x?xf64, #CSC_SLICE> ...


        


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