[mlir][Linalg] NFC: Refactor fusion on tensors to enable extending

it to fusing different kinds of linalg operations on tensors.

The implementation of fusion on tensor was initially planned for just
GenericOps (and maybe IndexedGenericOps). With addition of
linalg.tensor_reshape, and potentially other such non-structured ops,
refactor the existing implementation to allow easier specification of
fusion between different linalg operations on tensors.

Differential Revision: https://reviews.llvm.org/D78463

mlir/include/mlir/Dialect/Linalg/Utils/Utils.h

@@ -19,6 +19,7 @@ namespace mlir {
 class AffineExpr;
 class AffineMap;
 class OperationFolder;
+class PatternRewriter;
 
 namespace linalg {
 class LinalgDependenceGraph;
@@ -71,11 +72,11 @@ Optional<FusionInfo> fuseProducerOf(OpBuilder &b, LinalgOp consumer,
                                     const LinalgDependenceGraph &graph,
                                     OperationFolder *folder = nullptr);
 
-/// Fuse linalg operation on tensors, where the result of the producer is used
-/// as the operand of the consumer at position `consumerIdx`.
-Optional<LinalgOp> fuseTensorOps(OpBuilder &b, LinalgOp producer,
-                                 LinalgOp consumer, unsigned consumerIdx,
-                                 OperationFolder *folder = nullptr);
+/// Fuse linalg operation on tensors, with the producer of the operand at
+/// position `consumerIdx` of the consumer.
+Operation *fuseTensorOps(PatternRewriter &rewriter, Operation *consumer,
+                         unsigned consumerIdx,
+                         OperationFolder *folder = nullptr);
 
 /// Returns the linearized list of all view dimensions in a linalgOp. Applying
 /// the inverse, concatenated loopToOperandRangeMaps to this list allows the