[Mlir-commits] [mlir] fff0d1b - [mlir] Simplify a test for vectorizing tensor.extract
Andrzej Warzynski
llvmlistbot at llvm.org
Fri Dec 30 00:17:33 PST 2022
Author: Andrzej Warzynski
Date: 2022-12-30T08:16:35Z
New Revision: fff0d1b836d1ce043deb401e09ecc1c84bdfe11a
URL: https://github.com/llvm/llvm-project/commit/fff0d1b836d1ce043deb401e09ecc1c84bdfe11a
DIFF: https://github.com/llvm/llvm-project/commit/fff0d1b836d1ce043deb401e09ecc1c84bdfe11a.diff
LOG: [mlir] Simplify a test for vectorizing tensor.extract
Remove unused arguments and the corresponding logic (e.g. affine maps).
Differential Revision: https://reviews.llvm.org/D140755
Added:
Modified:
mlir/test/Dialect/Linalg/vectorization.mlir
Removed:
################################################################################
diff --git a/mlir/test/Dialect/Linalg/vectorization.mlir b/mlir/test/Dialect/Linalg/vectorization.mlir
index 74ef59e3ece05..9de78468f3e6e 100644
--- a/mlir/test/Dialect/Linalg/vectorization.mlir
+++ b/mlir/test/Dialect/Linalg/vectorization.mlir
@@ -1459,19 +1459,18 @@ transform.sequence failures(propagate) {
// -----
#map0 = affine_map<(d0, d1, d2, d3) -> (d0, d2)>
-#map1 = affine_map<(d0, d1, d2, d3) -> (d0, d1, d3)>
-#map2 = affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)>
-func.func @vectorize_1d_tensor_extract(%arg0: tensor<3xf32>, %arg1: tensor<4x3xi32>, %arg2: tensor<4x7x2xf32>, %arg3: tensor<4x7x3x2xf32>) -> tensor<4x7x3x2xf32> {
- %2 = linalg.generic {
- indexing_maps = [#map0, #map1, #map2],
+#map1 = affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)>
+func.func @vectorize_1d_tensor_extract(%arg0: tensor<3xf32>, %arg1: tensor<4x3xi32>, %arg2: tensor<4x7x3x2xf32>) -> tensor<4x7x3x2xf32> {
+ %1 = linalg.generic {
+ indexing_maps = [#map0, #map1],
iterator_types = ["parallel", "parallel", "parallel", "parallel"]
- } ins(%arg1, %arg2 : tensor<4x3xi32>, tensor<4x7x2xf32>) outs(%arg3 : tensor<4x7x3x2xf32>) {
- ^bb0(%arg4: i32, %arg5: f32, %arg6: f32):
- %3 = arith.index_cast %arg4 : i32 to index
- %7 = tensor.extract %arg0[%3] : tensor<3xf32>
- linalg.yield %7 : f32
+ } ins(%arg1 : tensor<4x3xi32>) outs(%arg2 : tensor<4x7x3x2xf32>) {
+ ^bb0(%arg3: i32, %arg4: f32):
+ %2 = arith.index_cast %arg3 : i32 to index
+ %3 = tensor.extract %arg0[%2] : tensor<3xf32>
+ linalg.yield %3 : f32
} -> tensor<4x7x3x2xf32>
- return %2 : tensor<4x7x3x2xf32>
+ return %1 : tensor<4x7x3x2xf32>
}
// CHECK-LABEL: func.func @vectorize_1d_tensor_extract
// CHECK-SAME: %[[ARG0:.*]]: tensor<3xf32>
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