[linalg] : Use -realmax instead of -inf for MaxPool init.

Author: sahas3

lib/Conversion/TorchToLinalg/Pooling.cpp

@@ -441,9 +441,9 @@ class ConvertAtenMaxPoolOp : public OpConversionPattern<OpTy> {
     Value self = adaptor.getSelf();
     Type elementType = cast<RankedTensorType>(self.getType()).getElementType();
     TypedAttr smallestFPValueAttr = rewriter.getFloatAttr(
-        elementType,
-        APFloat::getInf(cast<mlir::FloatType>(elementType).getFloatSemantics(),
-                        /*Negative=*/true));
+        elementType, APFloat::getLargest(
+                         cast<mlir::FloatType>(elementType).getFloatSemantics(),
+                         /*Negative=*/true));
     Value initValue =
         rewriter.create<arith::ConstantOp>(op->getLoc(), smallestFPValueAttr);
 
@@ -693,7 +693,7 @@ class ConvertAtenMaxPoolOp : public OpConversionPattern<OpTy> {
     if (auto fpty = dyn_cast<mlir::FloatType>(elementType)) {
       smallestValueAttr = rewriter.getFloatAttr(
           elementType,
-          APFloat::getInf(fpty.getFloatSemantics(), /*Negative=*/true));
+          APFloat::getLargest(fpty.getFloatSemantics(), /*Negative=*/true));
     } else if (auto intTy = dyn_cast<mlir::IntegerType>(elementType)) {
       int64_t bw = intTy.getIntOrFloatBitWidth();
       smallestValueAttr = rewriter.getIntegerAttr(
@@ -1379,9 +1379,9 @@ class AdaptiveMaxPoolingHelper : public AdaptivePoolingHelper {
         typeConverter->convertType(op.getResult1().getType()));
     Type auxTensorElementType = auxTensorType.getElementType();
     auto smallestFPValueAttr = rewriter.getFloatAttr(
-        elementType,
-        APFloat::getInf(cast<mlir::FloatType>(elementType).getFloatSemantics(),
-                        /*Negative=*/true));
+        elementType, APFloat::getLargest(
+                         cast<mlir::FloatType>(elementType).getFloatSemantics(),
+                         /*Negative=*/true));
     buffVal = rewriter.create<arith::ConstantOp>(loc, elementType,
                                                  smallestFPValueAttr);
     auxTensor = rewriter.create<tensor::EmptyOp>(

test/Conversion/TorchToLinalg/pooling.mlir

@@ -7,7 +7,7 @@ func.func @forward_max_pool1d(%arg0: !torch.vtensor<[?,?,?],f32>) -> !torch.vten
   %int3 = torch.constant.int 3
   %int4 = torch.constant.int 4
   %false = torch.constant.bool false
-  // CHECK: %[[NEUTRAL:.*]] = arith.constant 0xFF800000 : f32
+  // CHECK: %[[NEUTRAL:.*]] = arith.constant -3.40282347E+38 : f32
   // CHECK: %[[PADDED:.*]] = tensor.pad %{{.*}} low[0, 0, 3] high[0, 0, 3]
   // CHECK: %[[OUT:.*]] = linalg.fill ins(%[[NEUTRAL]] : f32) outs(%{{.*}} : tensor<?x?x?xf32>) -> tensor<?x?x?xf32>
   // CHECK: %[[INIT:.*]] = tensor.empty() : tensor<1xf32>
@@ -33,7 +33,7 @@ func.func @forward_max_pool2d(%arg0: !torch.vtensor<[?,?,?,?],f32>) -> !torch.vt
   %int7 = torch.constant.int 7
   %int8 = torch.constant.int 8
   %false = torch.constant.bool false
-  // CHECK: %[[NEUTRAL:.*]] = arith.constant 0xFF800000 : f32
+  // CHECK: %[[NEUTRAL:.*]] = arith.constant -3.40282347E+38 : f32
   // CHECK: %[[PADDED:.*]] = tensor.pad %{{.*}} low[0, 0, 5, 6] high[0, 0, 5, 6]
   // CHECK: %[[OUT:.*]] = linalg.fill ins(%[[NEUTRAL]] : f32) outs(%{{.*}} : tensor<?x?x?x?xf32>) -> tensor<?x?x?x?xf32>
   // CHECK: %[[INIT:.*]] = tensor.empty() : tensor<1x2xf32>
@@ -106,7 +106,7 @@ func.func @forward_max_pool3d(%arg0: !torch.vtensor<[?,?,?,?,?],f32>) -> !torch.
 
   %4 = torch.aten.max_pool3d %arg0, %kernel_size, %stride, %padding, %dilation, %false : !torch.vtensor<[?,?,?,?,?],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool -> !torch.vtensor<[?,?,?,?,?],f32>
 
-  // CHECK: %[[MIN_VALUE:.*]] = arith.constant 0xFF800000 : f32
+  // CHECK: %[[MIN_VALUE:.*]] = arith.constant -3.40282347E+38 : f32
   // CHECK: %[[PADDED_INPUT_TENSOR:.*]] = tensor.pad %{{.*}} low[0, 0, 4, 4, 4] high[0, 0, 4, 4, 4] {
   // CHECK-NEXT: ^bb0(%{{.*}}: index, %{{.*}}: index, %{{.*}}: index, %{{.*}}: index, %{{.*}}: index):
   // CHECK-NEXT:  tensor.yield %[[MIN_VALUE:.*]] : f32