[Mlir-commits] [mlir] [mlir][linalg] Fix numerical issue with softmax (PR #96090)
Prashant Kumar
llvmlistbot at llvm.org
Wed Jun 19 09:42:10 PDT 2024
https://github.com/pashu123 created https://github.com/llvm/llvm-project/pull/96090
For more info:
https://github.com/iree-org/iree/issues/17670#issuecomment-2167591878
>From 23221b96bec2dd96248ad85f9bd2ed8089864490 Mon Sep 17 00:00:00 2001
From: Prashant Kumar <pk5561 at gmail.com>
Date: Fri, 14 Jun 2024 14:59:04 +0530
Subject: [PATCH] [mlir][linalg] Fix numerical issue with softmax
For more info:
https://github.com/iree-org/iree/issues/17670#issuecomment-2167591878
---
mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp | 4 ++--
mlir/test/Dialect/Linalg/transform-op-decompose.mlir | 2 +-
2 files changed, 3 insertions(+), 3 deletions(-)
diff --git a/mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp b/mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp
index 7b6256050e772..57d126603ebd7 100644
--- a/mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp
+++ b/mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp
@@ -2714,8 +2714,8 @@ FailureOr<SmallVector<Value>> SoftmaxOp::decomposeOperation(OpBuilder &b) {
Value neutralForMaxFInit =
b.create<linalg::FillOp>(loc, Value{neutralForMaxF}, outputReduce)
.result();
- Value max = reduce<arith::MaximumFOp>(b, loc, input, neutralForMaxFInit,
- reductionDim);
+ Value max =
+ reduce<arith::MaxNumFOp>(b, loc, input, neutralForMaxFInit, reductionDim);
// Step 2: Subtract max from input and exponentiate.
Value numerator = buildSubAndExpOp(b, loc, input, max, output, reductionDim);
diff --git a/mlir/test/Dialect/Linalg/transform-op-decompose.mlir b/mlir/test/Dialect/Linalg/transform-op-decompose.mlir
index ef0aca2cc366f..2e211d2fa7dbe 100644
--- a/mlir/test/Dialect/Linalg/transform-op-decompose.mlir
+++ b/mlir/test/Dialect/Linalg/transform-op-decompose.mlir
@@ -215,7 +215,7 @@ func.func @softmax(%arg0: tensor<2x16x32xf32>, %dst: tensor<2x16x32xf32>) -> ten
// CHECK: %[[D3:.+]] = linalg.generic {indexing_maps = [#[[$MAP]], #[[$MAP1]]], iterator_types = ["parallel",
// CHECK-SAME: "parallel", "reduction"]} ins(%[[ARG0]] : tensor<2x16x32xf32>) outs(%[[D2]] : tensor<2x16xf32>) {
// CHECK: ^bb0(%[[IN:.+]]: f32, %[[OUT:.+]]: f32):
-// CHECK: %[[D8:.+]] = arith.maximumf %[[IN]], %[[OUT]] : f32
+// CHECK: %[[D8:.+]] = arith.maxnumf %[[IN]], %[[OUT]] : f32
// CHECK: linalg.yield %[[D8]] : f32
// CHECK: } -> tensor<2x16xf32>
// CHECK: %[[D4:.+]] = linalg.generic {indexing_maps = [#[[$MAP]], #[[$MAP1]], #[[$MAP]]], iterator_types =
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