[Mlir-commits] [mlir] f010725 - [mlir][linalg] Add folder for `linalg.index` (#136640)
llvmlistbot at llvm.org
llvmlistbot at llvm.org
Tue Apr 22 08:29:45 PDT 2025
Author: Jakub Kuderski
Date: 2025-04-22T11:29:41-04:00
New Revision: f010725e392c50700dec0dfe7ef3ff1ecfc517bd
URL: https://github.com/llvm/llvm-project/commit/f010725e392c50700dec0dfe7ef3ff1ecfc517bd
DIFF: https://github.com/llvm/llvm-project/commit/f010725e392c50700dec0dfe7ef3ff1ecfc517bd.diff
LOG: [mlir][linalg] Add folder for `linalg.index` (#136640)
We know that the index of unit dims is always 0.
Added:
Modified:
mlir/include/mlir/Dialect/Linalg/IR/LinalgOps.td
mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp
mlir/test/Dialect/Linalg/canonicalize.mlir
mlir/test/Dialect/Linalg/vectorize-tensor-extract.mlir
Removed:
################################################################################
diff --git a/mlir/include/mlir/Dialect/Linalg/IR/LinalgOps.td b/mlir/include/mlir/Dialect/Linalg/IR/LinalgOps.td
index f8df828f74851..1b48bf5fcb237 100644
--- a/mlir/include/mlir/Dialect/Linalg/IR/LinalgOps.td
+++ b/mlir/include/mlir/Dialect/Linalg/IR/LinalgOps.td
@@ -88,6 +88,7 @@ def Linalg_IndexOp : Linalg_Op<"index", [Pure]>,
let assemblyFormat = [{ $dim attr-dict `:` type($result) }];
let hasVerifier = 1;
+ let hasFolder = 1;
}
def Linalg_SoftmaxOp : Linalg_Op<"softmax",
diff --git a/mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp b/mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp
index 6c680498af2ad..72fb3308a2549 100644
--- a/mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp
+++ b/mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp
@@ -2283,6 +2283,19 @@ LogicalResult IndexOp::verify() {
return success();
}
+OpFoldResult IndexOp::fold(FoldAdaptor adaptor) {
+ auto linalgOp = cast<LinalgOp>((*this)->getParentOp());
+
+ // Index of unit dims is always 0.
+ SmallVector<int64_t, 4> loopBounds = linalgOp.getStaticLoopRanges();
+ uint64_t dim = getDim();
+ assert(dim < loopBounds.size() && "Dim is out of bounds");
+ if (loopBounds[dim] == 1)
+ return IntegerAttr::get(IndexType::get(getContext()), 0);
+
+ return OpFoldResult{};
+}
+
/////// Operations corresponding to library calls defined with Tablegen ////////
#include "mlir/Dialect/Linalg/IR/LinalgNamedStructuredOps.yamlgen.cpp.inc"
diff --git a/mlir/test/Dialect/Linalg/canonicalize.mlir b/mlir/test/Dialect/Linalg/canonicalize.mlir
index 86cb8f58abe02..3daf221f4402d 100644
--- a/mlir/test/Dialect/Linalg/canonicalize.mlir
+++ b/mlir/test/Dialect/Linalg/canonicalize.mlir
@@ -305,6 +305,86 @@ func.func @self_copy(%arg0 : memref<2x3x?x4xf32>) {
}
// -----
+
+// CHECK: func @fold_linalg_index_tensor_static
+func.func @fold_linalg_index_tensor_static(%0: tensor<4x16xi32>, %1: tensor<1x16xi32>,
+ %2: tensor<4x1xi32>) -> tensor<4x1xi32> {
+// CHECK-NEXT: linalg.generic
+// CHECK: %[[IDX_0:.+]] = linalg.index 0 : index
+// CHECK-NOT: linalg.index 1
+// CHECK: %[[IDX_2:.+]] = linalg.index 2 : index
+// CHECK: %[[ADD:.+]] = arith.addi %[[IDX_0]], %[[IDX_2]]
+// CHECK: %[[CAST:.+]] = arith.index_cast %[[ADD]]
+// CHECK: linalg.yield %[[CAST]]
+ %res = linalg.generic {indexing_maps = [affine_map<(d0, d1, d2) -> (d0, d2)>,
+ affine_map<(d0, d1, d2) -> (d1, d2)>,
+ affine_map<(d0, d1, d2) -> (d0, d1)>],
+ iterator_types = ["parallel", "parallel", "reduction"]}
+ ins(%0, %1 : tensor<4x16xi32>, tensor<1x16xi32>)
+ outs(%2 : tensor<4x1xi32>) {
+ ^bb0(%lhs: i32, %rhs: i32, %out: i32):
+ %idx0 = linalg.index 0 : index
+ %idx1 = linalg.index 1 : index
+ %idx2 = linalg.index 2 : index
+ %add0 = arith.addi %idx0, %idx1 : index
+ %add1 = arith.addi %add0, %idx2 : index
+ %int = arith.index_cast %add1 : index to i32
+ linalg.yield %int : i32
+ } -> tensor<4x1xi32>
+ return %res : tensor<4x1xi32>
+}
+
+// -----
+
+// CHECK: func @fold_linalg_index_tensor_dynamic
+func.func @fold_linalg_index_tensor_dynamic(%0: tensor<?x1xi32>,
+ %1: tensor<?x1xi32>) -> tensor<?x1xi32> {
+// CHECK-NEXT: linalg.generic
+// CHECK: %[[IDX_0:.+]] = linalg.index 0 : index
+// CHECK-NOT: linalg.index 1
+// CHECK: %[[CAST:.+]] = arith.index_cast %[[IDX_0]]
+// CHECK: linalg.yield %[[CAST]]
+ %res = linalg.generic {indexing_maps = [affine_map<(d0, d1) -> (d0, d1)>,
+ affine_map<(d0, d1) -> (d1, d1)>],
+ iterator_types = ["parallel", "parallel"]}
+ ins(%0 : tensor<?x1xi32>)
+ outs(%1 : tensor<?x1xi32>) {
+ ^bb0(%lhs: i32, %out: i32):
+ %idx0 = linalg.index 0 : index
+ %idx1 = linalg.index 1 : index
+ %add = arith.addi %idx0, %idx1 : index
+ %int = arith.index_cast %add : index to i32
+ linalg.yield %int : i32
+ } -> tensor<?x1xi32>
+ return %res : tensor<?x1xi32>
+}
+
+// -----
+
+// CHECK: func @fold_linalg_index_memref
+func.func @fold_linalg_index_memref(%0: memref<1x?xi32>, %1: memref<1x?xi32>) {
+// CHECK-NEXT: linalg.generic
+// CHECK-NOT: linalg.index 0
+// CHECK: %[[IDX_1:.+]] = linalg.index 1 : index
+// CHECK: %[[CAST:.+]] = arith.index_cast %[[IDX_1]]
+// CHECK: linalg.yield %[[CAST]]
+ linalg.generic {indexing_maps = [affine_map<(d0, d1) -> (d0, d1)>,
+ affine_map<(d0, d1) -> (d1, d1)>],
+ iterator_types = ["parallel", "parallel"]}
+ ins(%0 : memref<1x?xi32>)
+ outs(%1 : memref<1x?xi32>) {
+ ^bb0(%lhs: i32, %out: i32):
+ %idx0 = linalg.index 0 : index
+ %idx1 = linalg.index 1 : index
+ %add = arith.addi %idx0, %idx1 : index
+ %int = arith.index_cast %add : index to i32
+ linalg.yield %int : i32
+ }
+ return
+}
+
+// -----
+
// CHECK-LABEL: func @fold_fill_reshape()
func.func @fold_fill_reshape() -> tensor<6x4xf32> {
%zero = arith.constant 0.0 : f32
diff --git a/mlir/test/Dialect/Linalg/vectorize-tensor-extract.mlir b/mlir/test/Dialect/Linalg/vectorize-tensor-extract.mlir
index 375fa37bd84b0..01eafafc8ea29 100644
--- a/mlir/test/Dialect/Linalg/vectorize-tensor-extract.mlir
+++ b/mlir/test/Dialect/Linalg/vectorize-tensor-extract.mlir
@@ -278,12 +278,11 @@ func.func @vectorize_nd_tensor_extract_load_1d_column_vector_using_gather_load(%
// CHECK: %[[EMPTY:.*]] = tensor.empty() : tensor<8x1xf32>
// CHECK: %[[B1:.*]] = vector.broadcast %[[CST_3]] : vector<8xindex> to vector<1x8xindex>
// CHECK: %[[ADDI_ARG1:.*]] = arith.addi %[[ARG1]], %[[ARG1]] : index
-// CHECK: %[[B2:.*]] = vector.broadcast %[[ADDI_ARG1]] : index to vector<1xindex>
// CHECK: %[[MULI_1:.*]] = arith.muli %[[B1]], %[[CST_0]] : vector<1x8xindex>
// CHECK: %[[MULI_2:.*]] = arith.muli %[[MULI_1]], %[[CST]] : vector<1x8xindex>
// CHECK: %[[T:.*]] = vector.transpose %[[MULI_2]], [1, 0] : vector<1x8xindex> to vector<8x1xindex>
-// CHECK: %[[B3:.*]] = vector.broadcast %[[B2]] : vector<1xindex> to vector<8x1xindex>
-// CHECK: %[[ADDI:.*]] = arith.addi %[[B3]], %[[T]] : vector<8x1xindex>
+// CHECK: %[[B2:.*]] = vector.broadcast %[[ADDI_ARG1]] : index to vector<8x1xindex>
+// CHECK: %[[ADDI:.*]] = arith.addi %[[B2]], %[[T]] : vector<8x1xindex>
// CHECK: %[[GATHER:.*]] = vector.gather %[[ARG0]][%[[C0]], %[[C0]], %[[C0]]] [%[[ADDI]]], %[[CST_2]], %[[PASSTHRU]] : tensor<8x128x768xf32>, vector<8x1xindex>, vector<8x1xi1>, vector<8x1xf32> into vector<8x1xf32>
// CHECK: vector.transfer_write %[[GATHER]], %[[EMPTY]][%[[C0]], %[[C0]]] {in_bounds = [true, true]} : vector<8x1xf32>, tensor<8x1xf32>
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