[Mlir-commits] [mlir] a032b47 - [mlir][linalg] Fix neutral element value for minf/maxf

[Thomas Raoux]

Author: Thomas Raoux
Date: 2022-11-04T16:35:40Z
New Revision: a032b47e7e7792d57a26c0dcb38ecd12c28a0248

URL: https://github.com/llvm/llvm-project/commit/a032b47e7e7792d57a26c0dcb38ecd12c28a0248
DIFF: https://github.com/llvm/llvm-project/commit/a032b47e7e7792d57a26c0dcb38ecd12c28a0248.diff

LOG: [mlir][linalg] Fix neutral element value for minf/maxf

The neutral element got minf/maxf should be respectively +inf and -inf.

Bug reported by @Hardcode84.

Differential Revision: https://reviews.llvm.org/D137385

Added: 
    

Modified: 
    mlir/lib/Dialect/Linalg/Utils/Utils.cpp
    mlir/test/Dialect/Linalg/transform-op-split-reduction.mlir

Removed: 
    


################################################################################
diff  --git a/mlir/lib/Dialect/Linalg/Utils/Utils.cpp b/mlir/lib/Dialect/Linalg/Utils/Utils.cpp
index 04cbed0c4e13..ccf7cdc4aadb 100644
--- a/mlir/lib/Dialect/Linalg/Utils/Utils.cpp
+++ b/mlir/lib/Dialect/Linalg/Utils/Utils.cpp
@@ -1073,10 +1073,10 @@ Optional<Attribute> getNeutralElement(Operation *op) {
       return b.getFloatAttr(resultType, llvm::APFloat(semantic, 1));
     if (isa<arith::MaxFOp>(op))
       return b.getFloatAttr(resultType,
-                            llvm::APFloat::getLargest(semantic, true));
+                            llvm::APFloat::getInf(semantic, /*Negative=*/true));
     if (isa<arith::MinFOp>(op))
-      return b.getFloatAttr(resultType,
-                            llvm::APFloat::getLargest(semantic, true));
+      return b.getFloatAttr(
+          resultType, llvm::APFloat::getInf(semantic, /*Negative=*/false));
     return Attribute();
   }
   if (isa<arith::AddIOp, arith::OrIOp, arith::XOrIOp>(op))

diff  --git a/mlir/test/Dialect/Linalg/transform-op-split-reduction.mlir b/mlir/test/Dialect/Linalg/transform-op-split-reduction.mlir
index ee5f98bc2ce0..cb7a92198c04 100644
--- a/mlir/test/Dialect/Linalg/transform-op-split-reduction.mlir
+++ b/mlir/test/Dialect/Linalg/transform-op-split-reduction.mlir
@@ -112,7 +112,7 @@ func.func @generic_split_3d(%input: tensor<32x2xf32>, %input_2: tensor<5x32xf32>
 //  CHECK-DAG: #[[$MAP3:.*]] = affine_map<(d0, d1, d2) -> (d0, d1, d2)>
 //  CHECK-DAG: #[[$MAP4:.*]] = affine_map<(d0, d1, d2) -> (d0, d1)>
 // CHECK-LABEL:  func @generic_split_3d
-//  CHECK-DAG: %[[ID:.*]] = arith.constant -3.40282347E+38 : f32
+//  CHECK-DAG: %[[ID:.*]] = arith.constant 0xFF800000 : f32
 //  CHECK-DAG: %[[I1:.*]] = tensor.expand_shape %{{.*}}[0, 1], [2]] : tensor<32x2xf32> into tensor<4x8x2xf32>
 //  CHECK-DAG: %[[I2:.*]] = tensor.expand_shape %{{.*}}[0], [1, 2]] : tensor<5x32xf32> into tensor<5x4x8xf32>
 //  CHECK-DAG: %[[INI:.*]] = tensor.empty() : tensor<5x2x4xf32>
@@ -238,7 +238,7 @@ func.func @generic_split_3d(%input: tensor<32x2xf32>, %input_2: tensor<5x32xf32>
     } ins(%input, %input_2 : tensor<32x2xf32>, tensor<5x32xf32>) outs(%output : tensor<5x2xf32>) {
     ^bb0(%arg0: f32, %arg1: f32, %arg2: f32):
       %3 = arith.addf %arg0, %arg1 : f32
-      %4 = arith.maxf %3, %arg2 : f32
+      %4 = arith.minf %3, %arg2 : f32
       linalg.yield %4 : f32
     } -> tensor<5x2xf32>
   return %0 : tensor<5x2xf32>
@@ -250,7 +250,7 @@ func.func @generic_split_3d(%input: tensor<32x2xf32>, %input_2: tensor<5x32xf32>
 //  CHECK-DAG: #[[$MAP3:.*]] = affine_map<(d0, d1, d2) -> (d0, d1, d2)>	
 //  CHECK-DAG: #[[$MAP4:.*]] = affine_map<(d0, d1, d2) -> (d0, d1)>	
 // CHECK-LABEL:  func @generic_split_3d	
-//  CHECK-DAG: %[[ID:.*]] = arith.constant -3.40282347E+38 : f32	
+//  CHECK-DAG: %[[ID:.*]] = arith.constant 0x7F800000 : f32
 //  CHECK-DAG: %[[I1:.*]] = tensor.expand_shape %{{.*}}[0, 1], [2]] : tensor<32x2xf32> into tensor<8x4x2xf32>	
 //  CHECK-DAG: %[[I2:.*]] = tensor.expand_shape %{{.*}}[0], [1, 2]] : tensor<5x32xf32> into tensor<5x8x4xf32>	
 //  CHECK-DAG: %[[INI:.*]] = tensor.empty() : tensor<5x2x4xf32>	
@@ -258,12 +258,12 @@ func.func @generic_split_3d(%input: tensor<32x2xf32>, %input_2: tensor<5x32xf32>
 //      CHECK: %[[G:.*]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]], #[[$MAP2]]], iterator_types = ["parallel", "reduction", "parallel", "parallel"]}	
 // CHECK-SAME:   ins(%[[I1]], %[[I2]] : tensor<8x4x2xf32>, tensor<5x8x4xf32>) outs(%[[F]] : tensor<5x2x4xf32>) {	
 //      CHECK:   arith.addf	
-//      CHECK:   arith.maxf	
+//      CHECK:   arith.minf
 //      CHECK:   linalg.yield	
 //      CHECK: } -> tensor<5x2x4xf32>	
 //      CHECK: %[[R:.*]] = linalg.generic {indexing_maps = [#[[$MAP3]], #[[$MAP4]]], iterator_types = ["parallel", "parallel", "reduction"]}	
 // CHECK-SAME:   ins(%[[G]] : tensor<5x2x4xf32>) outs(%{{.*}} : tensor<5x2xf32>) {	
-//      CHECK:   arith.maxf	
+//      CHECK:   arith.minf
 //      CHECK:   linalg.yield	
 //      CHECK:  } -> tensor<5x2xf32>	
 //      CHECK: return %[[R]] : tensor<5x2xf32>