Skip to content

[mlir][linalg] Fix neutral elt for softmax #118952

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 1 commit into from
Jan 13, 2025
Merged

[mlir][linalg] Fix neutral elt for softmax #118952

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -2892,7 +2892,7 @@ FailureOr<SmallVector<Value>> SoftmaxOp::decomposeOperation(OpBuilder &b) {
dims.erase(dims.begin() + reductionDim);
// Step 1: Compute max along dim.
Value outputReduce = b.create<tensor::EmptyOp>(loc, dims, elementType);
Value neutralForMaxF = arith::getIdentityValue(arith::AtomicRMWKind::maximumf,
Value neutralForMaxF = arith::getIdentityValue(arith::AtomicRMWKind::maxnumf,
elementType, b, loc,
/*useOnlyFiniteValue=*/true);
Value neutralForMaxFInit =
Expand Down
2 changes: 1 addition & 1 deletion mlir/test/Dialect/Linalg/transform-op-decompose.mlir
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -210,7 +210,7 @@ func.func @softmax(%arg0: tensor<2x16x32xf32>, %dst: tensor<2x16x32xf32>) -> ten
// CHECK-LABEL: func.func @softmax(
// CHECK-SAME: %[[ARG0:[a-zA-Z0-9_]+]]: tensor<2x16x32xf32>, %[[DST:[a-zA-Z0-9_]+]]: tensor<2x16x32xf32>) -> tensor<2x16x32xf32> {
// CHECK-DAG: %[[D1:.+]] = tensor.empty() : tensor<2x16xf32>
// CHECK-DAG: %[[CST:.+]] = arith.constant -3.40282347E+38 : f32
// CHECK-DAG: %[[CST:.+]] = arith.constant 0xFFC00000 : f32
// CHECK: %[[D2:.+]] = linalg.fill ins(%[[CST]] : f32) outs(%[[D1]] : tensor<2x16xf32>) -> tensor<2x16xf32>
// CHECK: %[[D3:.+]] = linalg.generic {indexing_maps = [#[[$MAP]], #[[$MAP1]]], iterator_types = ["parallel",
// CHECK-SAME: "parallel", "reduction"]} ins(%[[ARG0]] : tensor<2x16x32xf32>) outs(%[[D2]] : tensor<2x16xf32>) {
Expand Down
Loading