[mlir][tosa] Revert add-0 canonicalization for floating-point

[rsuderman]

Summary

Floating point optimization can produce incorrect numerical resutls for
-0.0 + 0.0 optimization as result needs to be -0.0.

[eric-k256]

Thanks for doing this, I think it's the right solution.

mlir/lib/Dialect/Tosa/IR/TosaOps.cpp

struct AddZeroOptimization : public OpRewritePattern<tosa::AddOp> {
   LogicalResult matchAndRewrite(tosa::AddOp op,
                                 PatternRewriter &rewriter) const override {
     auto input1 = op.input1();
     auto input2 = op.input2();
 
     DenseElementsAttr input1Attr;
     if (matchPattern(input1, m_Constant(&input1Attr)) && input1Attr.isSplat() &&
         input2.getType() == op.getType()) {
-      if (input1Attr.getType().getElementType().isa<FloatType>() &&
-          input1Attr.getSplatValue<APFloat>().isZero()) {
-        rewriter.replaceOp(op, op.input2());
-        return success();
-      }
-
       if (input1Attr.getType().getElementType().isa<IntegerType>() &&
           input1Attr.getSplatValue<APInt>().isZero()) {
         rewriter.replaceOp(op, op.input2());
         return success();
       }
     }
 
     DenseElementsAttr input2Attr;
     if (matchPattern(input2, m_Constant(&input2Attr)) && input2Attr.isSplat() &&
         input1.getType() == op.getType()) {
-      if (input2Attr.getType().getElementType().isa<FloatType>() &&
-          input2Attr.getSplatValue<APFloat>().isZero()) {
-        rewriter.replaceOp(op, op.input1());
-        return success();
-      }
-
       if (input2Attr.getType().getElementType().isa<IntegerType>() &&
           input2Attr.getSplatValue<APInt>().isZero()) {
         rewriter.replaceOp(op, op.input1());
         return success();
       }
     }
 
     return failure();

mlir/test/Dialect/Tosa/canonicalize.mlir

 // RUN: mlir-opt --split-input-file --canonicalize %s | FileCheck %s
 
 // CHECK-LABEL: @argmax_nofold
 func @argmax_nofold(%arg0: tensor<?x1xf32>) -> tensor<?x1xf32> {
   // CHECK: "tosa.argmax"
   %0 = "tosa.argmax"(%arg0) {axis = 0 : i64}: (tensor<?x1xf32>) -> tensor<?x1xf32>
   return %0 : tensor<?x1xf32>
 }
 
 // -----
 
 // CHECK-LABEL: @add_zero_different_shape
-func @add_zero_different_shape(%arg0: tensor<2x3xf32>) -> tensor<4x2x3xf32> {
+func @add_zero_different_shape(%arg0: tensor<2x3xi32>) -> tensor<4x2x3xi32> {
   // CHECK: tosa.add
-  %zeros = "tosa.const"() {value = dense<0.0> : tensor<4x2x3xf32>} : () -> tensor<4x2x3xf32>
-  %1 = "tosa.add"(%arg0, %zeros) : (tensor<2x3xf32>, tensor<4x2x3xf32>) -> tensor<4x2x3xf32>
-  return %1 : tensor<4x2x3xf32>
+  %zeros = "tosa.const"() {value = dense<0> : tensor<4x2x3xi32>} : () -> tensor<4x2x3xi32>
+  %1 = "tosa.add"(%arg0, %zeros) : (tensor<2x3xi32>, tensor<4x2x3xi32>) -> tensor<4x2x3xi32>
+  return %1 : tensor<4x2x3xi32>
 }
 
-// -----
-
-// CHECK-LABEL: @add_zero_float
-func @add_zero_float(%arg0: tensor<2x3xf32>) -> tensor<2x3xf32> {
-  // CHECK: return %arg0
-  // CHECK-NOT: tosa.add
-  %zeros = "tosa.const"() {value = dense<0.0> : tensor<2x3xf32>} : () -> tensor<2x3xf32>
-  %1 = "tosa.add"(%arg0, %zeros) : (tensor<2x3xf32>, tensor<2x3xf32>) -> tensor<2x3xf32>
-  return %1 : tensor<2x3xf32>
-}
 
 // -----
 
 // CHECK-LABEL: @add_zero_int
 func @add_zero_int(%arg0: tensor<2x3xi32>) -> tensor<2x3xi32> {
   // CHECK: return %arg0
   // CHECK-NOT: tosa.add
   %zeros = "tosa.const"() {value = dense<0> : tensor<2x3xi32>} : () -> tensor<2x3xi32>