Refactor common tosa functions into tosaUtils (#2035)

rocMLIR has copies of many tosa related functions across a few source files. Mainly MIGraphXToTosa, TosaToRock and rocmlir-gen.cpp. This PR removes those copies and put them into header file to be shared across all source files.

Author: umangyadav

mlir/include/mlir/Dialect/Rock/utility/tosaUtils.h

@@ -0,0 +1,69 @@
+//===- tosa Utility Functions -===//
+//
+// Copyright 2025 Advanced Micro Devices.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//   http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+// ============================================================
+#ifndef MLIR_DIALECT_ROCK_TOSA_UTILITY_H
+#define MLIR_DIALECT_ROCK_TOSA_UTILITY_H
+
+#include "mlir/Dialect/Tosa/IR/TosaOps.h"
+#include "mlir/IR/Builders.h"
+#include "mlir/IR/Value.h"
+#include "mlir/Interfaces/InferTypeOpInterface.h"
+
+namespace mlir {
+namespace rock {
+bool isSpecificValueAttribute(Attribute value, double target);
+bool isConstantValue(Value v, double target);
+bool isConstantZero(Value v);
+bool isConstantOne(Value v);
+bool isConstNegInf(Value v);
+bool isConstRange(Value v);
+
+namespace tosa {
+template <typename TosaOp, typename... Args>
+TosaOp createOpAndInfer(OpBuilder &rewriter, Location loc, Type elemType,
+                        Args &&...args) {
+  auto op =
+      TosaOp::create(rewriter, loc, UnrankedTensorType::get(elemType), args...);
+  InferShapedTypeOpInterface shapeInterface =
+      cast<InferShapedTypeOpInterface>(op.getOperation());
+  SmallVector<ShapedTypeComponents> returnShape;
+  LogicalResult shapeInferenceStatus = shapeInterface.inferReturnTypeComponents(
+      op.getContext(), op.getLoc(), op->getOperands(), op->getAttrDictionary(),
+      op->getPropertiesStorage(), op->getRegions(), returnShape);
+  assert(shapeInferenceStatus.succeeded());
+  Type newOutTy = RankedTensorType::get({returnShape[0].getDims()}, elemType);
+  auto result = op->getResult(0);
+  result.setType(newOutTy);
+  return op;
+}
+
+Value getOneTensor(OpBuilder &builder, Location loc, RankedTensorType type);
+
+Type getAccType(OpBuilder &builder, Type inputType);
+
+Value getZeroTensor(OpBuilder &builder, Location loc, RankedTensorType type);
+
+mlir::tosa::TransposeOp getTransposeOp(OpBuilder &builder, Location loc,
+                                       Value input,
+                                       ArrayRef<int32_t> permutation);
+
+mlir::tosa::MulOp getMulOp(OpBuilder &builder, Location loc, Value input1,
+                           Value input2, Type elemType);
+} // namespace tosa
+} // namespace rock
+} // namespace mlir
+
+#endif // MLIR_DIALECT_ROCK_TOSA_UTILITY_H