[MLIR] Move `ConcatOp` to its lexicographic position

[frgossen]

Summary

Purely cosmetic change.
The operation implementations in Shape.cpp are now lexicographic order.

Depends On D80275

[frgossen]

@silvas, can I land this?

[frgossen]

This comment was removed by frgossen.

[frgossen]

Rebase

mlir/lib/Dialect/Shape/IR/Shape.cpp

OpFoldResult BroadcastOp::fold(ArrayRef<Attribute> operands) {
   // TODO: Fold to an "error".
   if (!OpTrait::util::getBroadcastedShape(lhsShape, rhsShape, resultShape))
     return nullptr;
   Builder builder(getContext());
   return builder.getIndexTensorAttr(resultShape);
 }
 
 //===----------------------------------------------------------------------===//
+// ConcatOp
+//===----------------------------------------------------------------------===//
+
+LogicalResult
+ConcatOp::inferReturnTypes(MLIRContext *context, Optional<Location> location,
+                           ValueRange operands, DictionaryAttr attributes,
+                           RegionRange regions,
+                           SmallVectorImpl<Type> &inferredReturnTypes) {
+  auto shapeType = ShapeType::get(context);
+  inferredReturnTypes.push_back(shapeType);
+  return success();
+}
+
+OpFoldResult ConcatOp::fold(ArrayRef<Attribute> operands) {
+  if (!operands[0] || !operands[1])
+    return nullptr;
+  auto lhsShape = llvm::to_vector<6>(
+      operands[0].cast<DenseIntElementsAttr>().getValues<int64_t>());
+  auto rhsShape = llvm::to_vector<6>(
+      operands[1].cast<DenseIntElementsAttr>().getValues<int64_t>());
+  SmallVector<int64_t, 6> resultShape;
+  resultShape.append(lhsShape.begin(), lhsShape.end());
+  resultShape.append(rhsShape.begin(), rhsShape.end());
+  Builder builder(getContext());
+  return builder.getIndexTensorAttr(resultShape);
+}
+
+//===----------------------------------------------------------------------===//
 // ConstShapeOp
 //===----------------------------------------------------------------------===//
 
 static void print(OpAsmPrinter &p, ConstShapeOp &op) {
   p << "shape.const_shape ";
   p.printOptionalAttrDict(op.getAttrs(), /*elidedAttrs=*/{"shape"});
   p << "[";
   interleaveComma(op.shape().getValues<int64_t>(), p,
if (splitPoint < 0)
     splitPoint += shape.size();
   Builder builder(operands[0].getContext());
   results.push_back(builder.getIndexTensorAttr(shape.take_front(splitPoint)));
   results.push_back(builder.getIndexTensorAttr(shape.drop_front(splitPoint)));
   return success();
 }
 
 //===----------------------------------------------------------------------===//
-// ConcatOp
-//===----------------------------------------------------------------------===//
-
-LogicalResult
-ConcatOp::inferReturnTypes(MLIRContext *context, Optional<Location> location,
-                           ValueRange operands, DictionaryAttr attributes,
-                           RegionRange regions,
-                           SmallVectorImpl<Type> &inferredReturnTypes) {
-  auto shapeType = ShapeType::get(context);
-  inferredReturnTypes.push_back(shapeType);
-  return success();
-}
-
-OpFoldResult ConcatOp::fold(ArrayRef<Attribute> operands) {
-  if (!operands[0] || !operands[1])
-    return nullptr;
-  auto lhsShape = llvm::to_vector<6>(
-      operands[0].cast<DenseIntElementsAttr>().getValues<int64_t>());
-  auto rhsShape = llvm::to_vector<6>(
-      operands[1].cast<DenseIntElementsAttr>().getValues<int64_t>());
-  SmallVector<int64_t, 6> resultShape;
-  resultShape.append(lhsShape.begin(), lhsShape.end());
-  resultShape.append(rhsShape.begin(), rhsShape.end());
-  Builder builder(getContext());
-  return builder.getIndexTensorAttr(resultShape);
-}
-
-//===----------------------------------------------------------------------===//
 // ToExtentTensorOp
 //===----------------------------------------------------------------------===//
 
 OpFoldResult ToExtentTensorOp::fold(ArrayRef<Attribute> operands) {
   if (!operands[0])
     return nullptr;
   Builder builder(getContext());
   auto shape = llvm::to_vector<6>(