[mlir][transform] Improve transform.get_closest_isolated_parent

[springerm]

Summary

• Rename op to transform.get_parent_op
• Match parents by "is isolated from above" and/or op name, or just the direct parent.
• Deduplication of result payload ops is optional.

mlir/include/mlir/Dialect/Transform/IR/TransformOps.td

let extraClassDeclaration = [{
     BlockArgument getIterationVariable() {
       return getBody().front().getArgument(0);
     }
 
     transform::YieldOp getYieldOp();
   }];
 }
 
-def GetClosestIsolatedParentOp : TransformDialectOp<"get_closest_isolated_parent",
-    [DeclareOpInterfaceMethods<TransformOpInterface>,
-     NavigationTransformOpTrait, MemoryEffectsOpInterface]> {
-  let summary = "Gets handles to the closest isolated-from-above parents";
-  let description = [{
-    The handles defined by this Transform op correspond to the closest isolated
-    from above ancestor of the Payload IR operations associated with its
-    operand. If any of the given Payload IR ops has no such parent (unlikely as
-    there usually is a top-level ModuleOp), the transformation is considered to
-    have failed.
-
-    Ancestor ops follow the same order as the ops associated with the
-    operand, except for potential duplicates (multiple Payload IR ops associated
-    with the operand have the same parent) for which the ancestor will only be
-    listed once for the first time it occurs. For example, given the list
-    "(childof(A), childof(B), childof(B), childof(A), childof(B))", the
-    resulting list will be just "(A, B)". Note that no other semantic ordering
-    is applied, e.g., "B" may itself be a parent of "A". This may have an impact
-    on the further transformation applied to the handle produced here.
-  }];
-
-  let arguments = (ins TransformHandleTypeInterface:$target);
-  let results = (outs TransformHandleTypeInterface:$parent);
-  let assemblyFormat =
-    "$target attr-dict `:` functional-type(operands, results)";
-}
-
 def GetConsumersOfResult : TransformDialectOp<"get_consumers_of_result",
     [DeclareOpInterfaceMethods<TransformOpInterface>,
      NavigationTransformOpTrait, MemoryEffectsOpInterface]> {
   let summary = "Get handle to the consumers of this operation's result number";
   let description = [{
     The handle defined by this Transform op corresponds to all operations that
     consume the SSA value defined by the `target` and `result_number`
     arguments.
def GetDefiningOp : TransformDialectOp<"get_defining_op",
   }];
 
   let arguments = (ins TransformValueHandleTypeInterface:$target);
   let results = (outs TransformHandleTypeInterface:$result);
   let assemblyFormat = "$target attr-dict `:` "
                        "functional-type(operands, results)";
 }
 
+def GetParentOp : TransformDialectOp<"get_parent_op",
+    [DeclareOpInterfaceMethods<TransformOpInterface>,
+     NavigationTransformOpTrait, MemoryEffectsOpInterface]> {
+  let summary = "Gets handles to the closest isolated-from-above parents";
+  let description = [{
+    The handle defined by this Transform op corresponds to the parents of the
+    targeted payload ops (in the same order).
+
+    Requirements that parent ops must fulfill can be optionally specified. In
+    that case for each target op, the closest parent op that fulfills all
+    requirements, is returned.
+    - `isolated_from_above`: the parent op must be isolated from above
+    - `op_name`: the parent op must have the specified name
+
+    If `deduplicate` is set, the result handle does not contain any duplicate
+    ops. For example, given the list
+    "(childof(A), childof(B), childof(B), childof(A), childof(B))", the
+    resulting list will be just "(A, B)". Note that no other semantic ordering
+    is applied, e.g., "B" may itself be a parent of "A". This may have an impact
+    on the further transformation applied to the handle produced here.
+
+    If any of the given Payload IR ops has no such suitable parent, the
+    transformation fails silently.
+  }];
+
+  let arguments = (ins TransformHandleTypeInterface:$target,
+                       UnitAttr:$isolated_from_above,
+                       OptionalAttr<StrAttr>:$op_name,
+                       UnitAttr:$deduplicate);
+  let results = (outs TransformHandleTypeInterface:$parent);
+  let assemblyFormat =
+    "$target attr-dict `:` functional-type(operands, results)";
+}
+
 def GetProducerOfOperand : TransformDialectOp<"get_producer_of_operand",
     [DeclareOpInterfaceMethods<TransformOpInterface>,
      NavigationTransformOpTrait, MemoryEffectsOpInterface]> {
   let summary = "Get handle to the producer of this operation's operand number";
   let description = [{
     The handle defined by this Transform op corresponds to operation that
     produces the SSA value defined by the `target` and `operand_number`
     arguments. If the origin of the SSA value is not an operations (i.e. it is

mlir/lib/Dialect/Transform/IR/TransformOps.cpp

LogicalResult transform::ForeachOp::verify() {
   for (Value v : yieldOp.getOperands())
     if (!llvm::isa<TransformHandleTypeInterface>(v.getType()))
       return yieldOp->emitOpError("expects operands to have types implementing "
                                   "TransformHandleTypeInterface");
   return success();
 }
 
 //===----------------------------------------------------------------------===//
-// GetClosestIsolatedParentOp
+// GetParentOp
 //===----------------------------------------------------------------------===//
 
-DiagnosedSilenceableFailure transform::GetClosestIsolatedParentOp::apply(
-    transform::TransformRewriter &rewriter,
-    transform::TransformResults &results, transform::TransformState &state) {
-  SetVector<Operation *> parents;
+DiagnosedSilenceableFailure
+transform::GetParentOp::apply(transform::TransformRewriter &rewriter,
+                              transform::TransformResults &results,
+                              transform::TransformState &state) {
+  SmallVector<Operation *> parents;
+  DenseSet<Operation *> resultSet;
   for (Operation *target : state.getPayloadOps(getTarget())) {
-    Operation *parent =
-        target->getParentWithTrait<OpTrait::IsIsolatedFromAbove>();
+    Operation *parent = target->getParentOp();
+    do {
+      bool checkIsolatedFromAbove =
+          !getIsolatedFromAbove() ||
+          parent->hasTrait<OpTrait::IsIsolatedFromAbove>();
+      bool checkOpName = !getOpName().has_value() ||
+                         parent->getName().getStringRef() == *getOpName();
+      if (checkIsolatedFromAbove && checkOpName)
+        break;
+    } while ((parent = parent->getParentOp()));
     if (!parent) {
       DiagnosedSilenceableFailure diag =
           emitSilenceableError()
-          << "could not find an isolated-from-above parent op";
+          << "could not find a parent op that matches all requirements";
       diag.attachNote(target->getLoc()) << "target op";
       return diag;
     }
-    parents.insert(parent);
+    if (getDeduplicate()) {
+      if (!resultSet.contains(parent)) {
+        parents.push_back(parent);
+        resultSet.insert(parent);
+      }
+    } else {
+      parents.push_back(parent);
+    }
   }
-  results.set(llvm::cast<OpResult>(getResult()), parents.getArrayRef());
+  results.set(llvm::cast<OpResult>(getResult()), parents);
   return DiagnosedSilenceableFailure::success();
 }
 
 //===----------------------------------------------------------------------===//
 // GetConsumersOfResult
 //===----------------------------------------------------------------------===//
 
 DiagnosedSilenceableFailure

mlir/python/mlir/dialects/_transform_ops_ext.py

try:
     )
 except ImportError as e:
     raise RuntimeError("Error loading imports from extension module") from e
 
 from typing import Optional, Sequence, Union
 
 
 class CastOp:
-    def __init__(
         self, result_type: Type, target: Union[Operation, Value], *, loc=None, ip=None
     ):
-        super().__init__(result_type, _get_op_result_or_value(target), loc=loc, ip=ip)
 
 
-class GetClosestIsolatedParentOp:
-    def __init__(
-        self, result_type: Type, target: Union[Operation, Value], *, loc=None, ip=None
-    ):
-        super().__init__(result_type, _get_op_result_or_value(target), loc=loc, ip=ip)
+class testGetParentOp:
+
+      self,
+      result_type: Type,
+      target: Union[Operation, Value],
+      *,
+      isolated_from_above: bool = False,
+      op_name: Optional[str] = None,
+      deduplicate: bool = False,
+      loc=None,
+      ip=None,
+    super().__init__(
+        result_type,
+        _get_op_result_or_value(target),
+        isolated_from_above=isolated_from_above,
+        op_name=op_name,
+        deduplicate=deduplicate,
+        loc=loc,
+        ip=ip,
+    )
 
 
 class MergeHandlesOp:
     def __init__(
         self,
         handles: Sequence[Union[Operation, Value]],
         *,
         deduplicate: bool = False,

mlir/test/Dialect/LLVM/transform-e2e.mlir

%0 = linalg.matmul  ins(%arg0, %arg1: tensor<2x4xf32>, tensor<4x6xf32>)
     -> tensor<2x6xf32>
   return %0 : tensor<2x6xf32>
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%module_op: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.matmul"]} in %module_op : (!transform.any_op) -> !transform.any_op
   %1, %loops:3 = transform.structured.tile %0 [2, 2, 2] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
-  %2 = get_closest_isolated_parent %1 : (!transform.any_op) -> !transform.any_op
+  %2 = get_parent_op %1 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   transform.structured.vectorize %2 : (!transform.any_op) -> !transform.any_op
   %b = transform.bufferization.one_shot_bufferize layout{IdentityLayoutMap}
       %module_op {bufferize_function_boundaries = true}
       : (!transform.any_op) -> !transform.any_op
 
   %f = transform.structured.match ops{["func.func"]} in %b
     : (!transform.any_op) -> !transform.any_op
 

mlir/test/Dialect/Linalg/transform-op-matmul-to-outerproduct.mlir

 // CHECK:           %[[VAL_17:.*]] = vector.outerproduct %[[VAL_15]], %[[VAL_16]], %[[VAL_14]] {kind = #vector.kind<add>} : vector<3xf32>, vector<3xf32>
 // CHECK:           vector.transfer_write %[[VAL_17]], %[[VAL_2]]{{\[}}%[[VAL_3]], %[[VAL_3]]] {in_bounds = [true, true]} : vector<3x3xf32>, memref<3x3xf32>
 // CHECK:           return
 // CHECK:         }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1 : (!transform.any_op) -> !transform.any_op
   transform.apply_patterns to %2 {
     transform.apply_patterns.vector.lower_contraction lowering_strategy = "outerproduct"
   } : !transform.any_op
 }

mlir/test/Dialect/Linalg/transform-op-vectorize.mlir

func.func @vectorize_matmul(%arg0: tensor<24x12xf32>,
   // CHECK: vector.transfer_write %[[vR]], %[[C]]
   %0 = linalg.matmul ins(%arg0, %arg1 : tensor<24x12xf32>, tensor<12x25xf32>) outs(%arg2 : tensor<24x25xf32>) -> tensor<24x25xf32>
   func.return %0 : tensor<24x25xf32>
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1 : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 // CHECK-LABEL: @vectorize_matmul_memref
 // CHECK-SAME: %[[A:.*]]: memref<24x12xf32>
 // CHECK-SAME: %[[B:.*]]: memref<12x25xf32>
 // CHECK-SAME: %[[C:.*]]: memref<24x25xf32>
 func.func @vectorize_matmul_memref(%arg0: memref<24x12xf32>,
                                    %arg1: memref<12x25xf32>,
                                    %arg2: memref<24x25xf32>) {
   // CHECK: %[[vA:.+]] = vector.transfer_read %[[A]]
   // CHECK: %[[vB:.+]] = vector.transfer_read %[[B]]
   // CHECK: %[[vC:.+]] = vector.transfer_read %[[C]]
   // CHECK: %[[vR:.+]] = vector.contract {{.*}} %[[vA]], %[[vB]], %[[vC]]
   // CHECK: vector.transfer_write %[[vR]], %[[C]]
   linalg.matmul ins(%arg0, %arg1 : memref<24x12xf32>, memref<12x25xf32>) outs(%arg2 : memref<24x25xf32>)
   return
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1 : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 // CHECK-LABEL: @vectorize_copy_memref
 // CHECK-SAME: %[[A:.*]]: memref<100x100xf32>,
 // CHECK-SAME: %[[B:.*]]: memref<100x100xf32>
 func.func @vectorize_copy_memref(%arg0: memref<100x100xf32>,
                                  %arg1: memref<100x100xf32>) {
   // CHECK: %[[vA:.+]] = vector.transfer_read %[[A]]
   // CHECK: vector.transfer_write %[[vA]], %[[B]]
   linalg.copy ins(%arg0 : memref<100x100xf32>) outs(%arg1 : memref<100x100xf32>)
   return
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.copy"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1 : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 #map0 = affine_map<()[s0] -> (-s0 + 12, 7)>
 #map1 = affine_map<()[s0] -> (-s0 + 7)>
 
func.func @vectorize_keep_pad(
   %8 = linalg.matmul ins(%5, %7 : tensor<4x7xf32>, tensor<7x5xf32>) outs(%3 : tensor<4x5xf32>) -> tensor<4x5xf32>
   %9 = tensor.insert_slice %8 into %arg2[%arg3, %arg4] [4, 5] [1, 1] : tensor<4x5xf32> into tensor<24x25xf32>
   return %9 : tensor<24x25xf32>
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1 : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 #map0 = affine_map<()[s0] -> (-s0 + 12, 7)>
 #map1 = affine_map<()[s0] -> (-s0 + 7)>
 
func.func @vectorize_pad(
   %8 = linalg.matmul ins(%5, %7 : tensor<4x7xf32>, tensor<7x5xf32>) outs(%3 : tensor<4x5xf32>) -> tensor<4x5xf32>
   %9 = tensor.insert_slice %8 into %arg2[%arg3, %arg4] [4, 5] [1, 1] : tensor<4x5xf32> into tensor<24x25xf32>
   return %9 : tensor<24x25xf32>
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1 {vectorize_padding} : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 func.func @vectorize(%arg0: tensor<24x12xf32>,
                      %arg1: tensor<12x25xf32>,
                      %arg2: tensor<24x25xf32>) -> tensor<24x25xf32> {

mlir/test/Dialect/Linalg/vectorization.mlir

 // RUN: mlir-opt %s -test-transform-dialect-interpreter -split-input-file | FileCheck %s
 
 // CHECK-LABEL: contraction_dot
 func.func @contraction_dot(%A: memref<1584xf32>, %B: memref<1584xf32>, %C: memref<f32>) {
 
 // CHECK: arith.mulf %{{.*}}, %{{.*}} : vector<1584xf32>
 // CHECK: vector.multi_reduction <add>, %{{.*}}, {{.*}} [0] : vector<1584xf32> to f32
   linalg.dot ins(%A, %B: memref<1584xf32>, memref<1584xf32>)
             outs(%C: memref<f32>)
   return
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.dot"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1  { disable_multi_reduction_to_contract_patterns } : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 // CHECK-LABEL: contraction_matvec
 func.func @contraction_matvec(%A: memref<1584x1584xf32>, %B: memref<1584xf32>, %C: memref<1584xf32>) {
 
 // CHECK: arith.mulf %{{.*}}, %{{.*}} : vector<1584x1584xf32>
 // CHECK: vector.multi_reduction <add>, %{{.*}}, {{.*}} [1] : vector<1584x1584xf32> to vector<1584xf32>
   linalg.matvec ins(%A, %B: memref<1584x1584xf32>, memref<1584xf32>)
             outs(%C: memref<1584xf32>)
   return
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.matvec"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1  { disable_multi_reduction_to_contract_patterns } : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 // CHECK-LABEL: contraction_matmul
 func.func @contraction_matmul(%A: memref<1584x1584xf32>, %B: memref<1584x1584xf32>, %C: memref<1584x1584xf32>) {
 // CHECK: arith.mulf %{{.*}}, %{{.*}} : vector<1584x1584x1584xf32>
 // CHECK: vector.multi_reduction <add>, %{{.*}}, {{.*}} [2] : vector<1584x1584x1584xf32> to vector<1584x1584xf32>
   linalg.matmul ins(%A, %B: memref<1584x1584xf32>, memref<1584x1584xf32>)
             outs(%C: memref<1584x1584xf32>)
   return
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1  { disable_multi_reduction_to_contract_patterns } : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 // CHECK-LABEL: contraction_batch_matmul
 func.func @contraction_batch_matmul(%A: memref<1584x1584x1584xf32>, %B: memref<1584x1584x1584xf32>, %C: memref<1584x1584x1584xf32>) {
 // CHECK: arith.mulf %{{.*}}, %{{.*}} : vector<1584x1584x1584x1584xf32>
 // CHECK: vector.multi_reduction <add>, %{{.*}}, {{.*}} [3] : vector<1584x1584x1584x1584xf32> to vector<1584x1584x1584xf32>
   linalg.batch_matmul
     ins(%A, %B: memref<1584x1584x1584xf32>, memref<1584x1584x1584xf32>)
    outs(%C: memref<1584x1584x1584xf32>)
   return
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.batch_matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1  { disable_multi_reduction_to_contract_patterns } : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 #matmul_trait = {
   args_in = 2,
   args_out = 1,
^bb(%a: f32, %b: f32, %c: f32) :
       linalg.yield %e : f32
   }
   return
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1  { disable_multi_reduction_to_contract_patterns, disable_transfer_permutation_map_lowering_patterns } : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 #matmul_transpose_out_trait = {
   args_in = 2,
   args_out = 1,
^bb(%a: f32, %b: f32, %c: f32) :
       linalg.yield %e : f32
   }
   return
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1  { disable_multi_reduction_to_contract_patterns, disable_transfer_permutation_map_lowering_patterns } : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 #map0 = affine_map<(d0, d1, d2) -> (d0, d1, d2)>
 #map1 = affine_map<(d0, d1, d2) -> (d1, d0, d2)>
 // CHECK: #[[MAP:.+]] = affine_map<(d0, d1, d2) -> (d1, d0, d2)>
^bb0(%arg1: f32, %arg2: f32):
     linalg.yield %arg1 : f32
   } -> tensor<128x12x32xf32>
   return %1 : tensor<128x12x32xf32>
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1  { disable_multi_reduction_to_contract_patterns, disable_transfer_permutation_map_lowering_patterns } : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 #matmul_trait = {
   args_in = 2,
   args_out = 1,
^bb(%a: i32, %b: i32, %c: i32) :
       linalg.yield %e : i32
   }
   return
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1  { disable_multi_reduction_to_contract_patterns, disable_transfer_permutation_map_lowering_patterns } : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 // CHECK-LABEL: func @vectorization_test_2
 func.func @vectorization_test_2(%A: memref<8x16xf32>, %B: memref<16x32xf32>,
                          %C: memref<8x32xf32>) {
   //       CHECK: arith.mulf %{{.*}}, %{{.*}} : vector<8x32x16xf32>
   //       CHECK: vector.multi_reduction <add>, %{{.*}}, {{.*}} [2] : vector<8x32x16xf32> to vector<8x32xf32>
   linalg.matmul
     ins(%A, %B: memref<8x16xf32>, memref<16x32xf32>)
    outs(%C: memref<8x32xf32>)
   return
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1  { disable_multi_reduction_to_contract_patterns } : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 // CHECK-LABEL: func @test_vectorize_scalar_input
 func.func @test_vectorize_scalar_input(%A : memref<8x16xf32>, %arg0 : f32) {
   //       CHECK: %[[V:.*]] = vector.broadcast {{.*}} : f32 to vector<8x16xf32>
   //       CHECK: vector.transfer_write %[[V]], {{.*}} : vector<8x16xf32>, memref<8x16xf32>
   linalg.generic {
     indexing_maps = [affine_map<(m, n) -> ()>, affine_map<(m, n) -> (m, n)>],
     iterator_types = ["parallel", "parallel"]}
    ins(%arg0 : f32)
   outs(%A: memref<8x16xf32>) {
     ^bb(%0: f32, %1: f32) :
       linalg.yield %0 : f32
   }
   return
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1 : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 // CHECK-LABEL: func @test_do_not_vectorize_unsupported_element_types
 func.func @test_do_not_vectorize_unsupported_element_types(%A : memref<8x16xcomplex<f32>>, %arg0 : complex<f32>) {
   // CHECK-NOT: vector.broadcast
   // CHECK-NOT: vector.transfer_write
   linalg.generic {
     indexing_maps = [affine_map<(m, n) -> ()>, affine_map<(m, n) -> (m, n)>],
     iterator_types = ["parallel", "parallel"]}
    ins(%arg0 : complex<f32>)
   outs(%A: memref<8x16xcomplex<f32>>) {
     ^bb(%0: complex<f32>, %1: complex<f32>) :
       linalg.yield %0 : complex<f32>
   }
   return
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1 : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 #map0 = affine_map<(d0) -> (d0)>
 
 func.func @vectorize_affine_apply(%arg0: tensor<5xf32>, %arg3: index) -> tensor<5xi32> {

 // CHECK:   %[[ADDI_3:.*]] = arith.addi %[[ADDI_1]], %[[ADDI_2]] : vector<5xindex>
 // CHECK:   %[[ADDI_4:.*]] = arith.addi %[[ADDI_3]], %[[CST]] : vector<5xindex>
 // CHECK:   %[[CAST:.*]] = arith.index_cast %[[ADDI_4]] : vector<5xindex> to vector<5xi32>
 // CHECK:   vector.transfer_write %[[CAST]], %[[EMPTY]][%[[C0:.*]]] {in_bounds = [true]} : vector<5xi32>, tensor<5xi32>
 
 transform.sequence failures(propagate) {
  ^bb1(%arg1: !transform.any_op):
    %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-   %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+   %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
    %2 = transform.structured.vectorize %1 { vectorize_nd_extract } : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 // CHECK-LABEL: func @test_vectorize_fill
 func.func @test_vectorize_fill(%A : memref<8x16xf32>, %arg0 : f32) {
   //       CHECK: %[[V:.*]] = vector.broadcast {{.*}} : f32 to vector<8x16xf32>
   //       CHECK: vector.transfer_write %[[V]], {{.*}} : vector<8x16xf32>, memref<8x16xf32>
   linalg.fill ins(%arg0 : f32) outs(%A : memref<8x16xf32>)
   return
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.fill"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1 : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 // CHECK-LABEL: func @test_vectorize_fill
 func.func @test_vectorize_fill_scalar(%A : memref<f32>, %arg0 : f32) {
   // CHECK-SAME: (%[[M:.*]]: memref<f32>, %[[val:.*]]: f32)
   //      CHECK:   %[[VEC:.*]] = vector.broadcast %[[val]] : f32 to vector<f32>
   //      CHECK:   vector.transfer_write %[[VEC]], %[[M]][] : vector<f32>, memref<f32>
   linalg.fill ins(%arg0 : f32) outs(%A : memref<f32>)
   return
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.fill"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1 : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 // CHECK-LABEL: func @test_vectorize_copy
 func.func @test_vectorize_copy(%A : memref<8x16xf32>, %B : memref<8x16xf32>) {
   //       CHECK: %[[V:.*]] = vector.transfer_read {{.*}} : memref<8x16xf32>, vector<8x16xf32>
   //       CHECK: vector.transfer_write %[[V]], {{.*}} : vector<8x16xf32>, memref<8x16xf32>
   memref.copy %A, %B :  memref<8x16xf32> to memref<8x16xf32>
   return
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["memref.copy"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1 : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 // CHECK-LABEL: func @test_vectorize_copy_scalar
 func.func @test_vectorize_copy_scalar(%A : memref<f32>, %B : memref<f32>) {
   //  CHECK-SAME: (%[[A:.*]]: memref<f32>, %[[B:.*]]: memref<f32>)
   //       CHECK:   %[[V:.*]] = vector.transfer_read %[[A]][]{{.*}} : memref<f32>, vector<f32>
   //       CHECK:   %[[val:.*]] = vector.extractelement %[[V]][] : vector<f32>
   //       CHECK:   %[[VV:.*]] = vector.broadcast %[[val]] : f32 to vector<f32>
   //       CHECK:   vector.transfer_write %[[VV]], %[[B]][] : vector<f32>, memref<f32>
   memref.copy %A, %B :  memref<f32> to memref<f32>
   return
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["memref.copy"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1 : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 // CHECK-LABEL: func @test_vectorize_copy_complex
 // CHECK-NOT: vector<
 func.func @test_vectorize_copy_complex(%A : memref<8x16xcomplex<f32>>, %B : memref<8x16xcomplex<f32>>) {
   memref.copy %A, %B :  memref<8x16xcomplex<f32>> to memref<8x16xcomplex<f32>>
   return
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["memref.copy"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1 : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 // CHECK-LABEL: func @test_vectorize_trailing_index
   //  CHECK-SAME: (%[[ARG0:.*]]: memref<1x2x4x8xindex>)
 func.func @test_vectorize_trailing_index(%arg0: memref<1x2x4x8xindex>) {
//       CHECK:   vector.transfer_write %[[BCST]], %[[ARG0]][%[[C0]], %[[C0]], %[[C0]], %[[C0]]] {{.*}} : vector<1x2x4x8xindex>, memref<1x2x4x8xindex>
     linalg.yield %0 : index
   }
   return
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1 : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 // CHECK-LABEL: func @test_vectorize_inner_index
   //  CHECK-SAME: (%[[ARG0:.*]]: memref<1x2x4x8xindex>)
 func.func @test_vectorize_inner_index(%arg0: memref<1x2x4x8xindex>) {
//       CHECK:   vector.transfer_write %[[TRAN]], %[[ARG0]][%[[C0]], %[[C0]], %[[C0]], %[[C0]]] {{.*}} : vector<1x2x4x8xindex>, memref<1x2x4x8xindex>
     linalg.yield %0 : index
   }
   return
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1 : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 // CHECK-LABEL: func @generic_vectorize
   //  CHECK-SAME: (%[[ARG0:.*]]: memref<4x256xf32>, %[[ARG1:.*]]: memref<4x256xf32>,
   //  CHECK-SAME:  %[[ARG2:.*]]: memref<256xf32>, %[[ARG3:.*]]: f32)
linalg.yield %6, %8, %c1_f32, %9, %10, %11, %12, %13, %14, %15 : f32, f32,
       f32, f32, f32, f32, f32, f32, f32, f32
   }
   return
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1  { disable_transfer_permutation_map_lowering_patterns } : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 // CHECK-LABEL: func @generic_vectorize_tensor
 //  CHECK-SAME: (%[[ARG0:.*]]: tensor<4x256xf32>, %[[ARG1:.*]]: tensor<4x256xf32>,
 //  CHECK-SAME:  %[[ARG2:.*]]: tensor<256xf32>, %[[ARG3:.*]]: f32)
return %r#0, %r#1, %r#2, %r#3, %r#4, %r#5, %r#6, %r#7, %r#8, %r#9:
     tensor<4x256xf32>, tensor<4x256xf32>, tensor<4x256xf32>,
     tensor<4x256xf32>, tensor<4x256xf32>, tensor<4x256xf32>, tensor<4x256xf32>,
     tensor<4x256xf32>, tensor<4x256xf32>, tensor<4x256xf32>
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1 { disable_transfer_permutation_map_lowering_patterns } : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 // CHECK-DAG: #[[$MAP0:.*]] = affine_map<(d0, d1) -> (d0, 0, 0, d1)>
 // CHECK-DAG: #[[$MAP1:.*]] = affine_map<(d0) -> (d0, 0, 0, 0)>
 // CHECK-DAG: #[[$MAP2:.*]] = affine_map<(d0) -> (0, 0, d0, 0)>
^bb0(%arg0: f32, %arg1: f32, %arg2: f32, %arg3: f32, %arg4: f32):
     linalg.yield %b : f32
   }
   return
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1  { disable_transfer_permutation_map_lowering_patterns } : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 // Test different input maps.
 #matmul_trait = {
   indexing_maps = [
^bb(%a: f32, %b: f32, %c: f32, %d: f32) :
       linalg.yield %f : f32
   }
   return
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1  { disable_transfer_permutation_map_lowering_patterns } : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 // CHECK-LABEL: func @matmul_tensors
 //  CHECK-SAME: (%[[ARG0:.*]]: tensor<8x4xf32>, %[[ARG1:.*]]: tensor<4x12xf32>,
 //  CHECK-SAME:  %[[ARG2:.*]]: tensor<8x12xf32>) -> tensor<8x12xf32>
%0 = linalg.matmul  ins(%arg0, %arg1: tensor<8x4xf32>, tensor<4x12xf32>)
     -> tensor<8x12xf32>
   //       CHECK:   return %[[W]] : tensor<8x12xf32>
   return %0 : tensor<8x12xf32>
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1  { disable_multi_reduction_to_contract_patterns, disable_transfer_permutation_map_lowering_patterns } : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 // CHECK-LABEL: func @pad_static(
 //  CHECK-SAME:                  %[[ARG0:.*]]: tensor<2x?x2xf32>, %[[PAD:.*]]: f32
 //   CHECK-NOT:   tensor.pad
%0 = tensor.pad %arg0 low[0, 0, 2] high[0, 1, 0] {
     } : tensor<2x?x2xf32> to tensor<2x3x4xf32>
   return %0 : tensor<2x3x4xf32>
 }
 
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["tensor.pad"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1 { vectorize_padding } : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 // CHECK-LABEL: func @pad_static_source(
 //  CHECK-SAME:                  %[[ARG0:.*]]: tensor<2x5x2xf32>, %[[PAD:.*]]: f32
 //   CHECK-NOT:   tensor.pad
%0 = tensor.pad %arg0 low[0, 0, 2] high[0, 1, 0] {
     } : tensor<2x5x2xf32> to tensor<2x6x4xf32>
   return %0 : tensor<2x6x4xf32>
 }
 
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["tensor.pad"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1  { vectorize_padding } : (!transform.any_op) -> !transform.any_op
 }
 
 
 // -----
 
 // CHECK-LABEL: func @pad_static_dynamic(
 //  CHECK-SAME:                          %[[SRC:.*]]: tensor<1x2x2x?xf32>, %[[LOW:.*]]: index, %[[HIGH:.*]]: index
%0 = tensor.pad %arg0 low[2, %low, 3, 3] high[3, 3, %high, 2] {
     } : tensor<1x2x2x?xf32> to tensor<6x?x?x?xf32>
   return %0 : tensor<6x?x?x?xf32>
 }
 
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["tensor.pad"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1  { vectorize_padding } : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 // CHECK-LABEL: func @pad_static_complex(
 //   CHECK-NOT:   vector<
 func.func @pad_static_complex(%arg0: tensor<2x5x2xcomplex<f32>>, %pad_value: complex<f32>) -> tensor<2x6x4xcomplex<f32>> {
   %0 = tensor.pad %arg0 low[0, 0, 2] high[0, 1, 0] {
     ^bb0(%arg1: index, %arg2: index, %arg3: index):
       tensor.yield %pad_value : complex<f32>
     } : tensor<2x5x2xcomplex<f32>> to tensor<2x6x4xcomplex<f32>>
   return %0 : tensor<2x6x4xcomplex<f32>>
 }
 
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["tensor.pad"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1  { vectorize_padding } : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 // CHECK-LABEL: func @pad_and_transfer_read
 //  CHECK-SAME:     %[[ARG0:.*]]: tensor<5x6xf32>
 //   CHECK-NOT:   tensor.pad
%1 = vector.transfer_read %0[%c0, %c0], %c6
       : tensor<10x13xf32>, vector<7x9xf32>
   return %1 : vector<7x9xf32>
 }
 
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["tensor.pad"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1 { vectorize_padding } : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 func.func private @make_vector() -> vector<7x9xf32>
 
 // CHECK-LABEL: func @pad_and_transfer_write_static
%2 = vector.transfer_write %1, %0[%c0, %c0]
       : vector<7x9xf32>, tensor<10x13xf32>
   %3 = tensor.extract_slice %2[0, 0] [5, 6] [1, 1] : tensor<10x13xf32> to tensor<5x6xf32>
   return %3 : tensor<5x6xf32>
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %3 = transform.structured.match ops{["tensor.pad"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %4 = get_closest_isolated_parent %3 : (!transform.any_op) -> !transform.any_op
+  %4 = get_parent_op %3 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %5 = transform.structured.vectorize %4  { vectorize_padding } : (!transform.any_op) -> !transform.any_op
 }
 
 
 // -----
 
 func.func private @make_vector() -> vector<7x9xf32>
 
%2 = vector.transfer_write %1, %0[%c0, %c0]
       : vector<7x9xf32>, tensor<?x13xf32>
   %3 = tensor.extract_slice %2[0, 0] [%size, 6] [1, 1] : tensor<?x13xf32> to tensor<?x6xf32>
   return %3 : tensor<?x6xf32>
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %3 = transform.structured.match ops{["tensor.pad"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %4 = get_closest_isolated_parent %3 : (!transform.any_op) -> !transform.any_op
+  %4 = get_parent_op %3 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %5 = transform.structured.vectorize %4 { vectorize_padding } : (!transform.any_op) -> !transform.any_op
 }
 
 
 // -----
 
 func.func private @make_vector() -> tensor<12x13xf32>
 
func.func @pad_and_insert_slice_source(
   %1 = call @make_vector() : () -> tensor<12x13xf32>
   %r = tensor.insert_slice %0 into %1[0, 0][7, 9][1, 1] : tensor<7x9xf32> into tensor<12x13xf32>
   return %r : tensor<12x13xf32>
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %3 = transform.structured.match ops{["tensor.pad"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %4 = get_closest_isolated_parent %3 : (!transform.any_op) -> !transform.any_op
+  %4 = get_parent_op %3 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %5 = transform.structured.vectorize %4  { vectorize_padding } : (!transform.any_op) -> !transform.any_op
 }
 
 
 // -----
 
 func.func private @make_vector() -> tensor<12x13xf32>
 
func.func @pad_and_insert_slice_dest(
   %1 = call @make_vector() : () -> tensor<12x13xf32>
   %r = tensor.insert_slice %1 into %0[0, 0, 0][1, 12, 13][1, 1, 1] : tensor<12x13xf32> into tensor<1x12x13xf32>
   return %r : tensor<1x12x13xf32>
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %3 = transform.structured.match ops{["tensor.pad"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %4 = get_closest_isolated_parent %3 : (!transform.any_op) -> !transform.any_op
+  %4 = get_parent_op %3 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %5 = transform.structured.vectorize %4 : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 // CHECK-LABEL: func @pad_tensor_non_const_pad_value
 //  CHECK-SAME:     %[[ARG0:.*]]: tensor<5x6xf32>
 //   CHECK-NOT:   tensor.pad
func.func @pad_tensor_non_const_pad_value(%arg0: tensor<5x6xf32>) -> tensor<12x13xf32> {
   } : tensor<5x6xf32> to tensor<12x13xf32>
   return %0 : tensor<12x13xf32>
 }
 
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %3 = transform.structured.match ops{["tensor.pad"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %4 = get_closest_isolated_parent %3 : (!transform.any_op) -> !transform.any_op
+  %4 = get_parent_op %3 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %5 = transform.structured.vectorize %4  { vectorize_padding } : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 // CHECK-LABEL: func @sum_exp
 func.func @sum_exp(%input: tensor<4x16x8xf32>, %output: tensor<4x16xf32>)
   -> tensor<4x16xf32>
%0 = linalg.generic {
     } -> tensor<4x16xf32>
   return %0 : tensor<4x16xf32>
 }
 
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %3 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %4 = get_closest_isolated_parent %3 : (!transform.any_op) -> !transform.any_op
+  %4 = get_parent_op %3 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %5 = transform.structured.vectorize %4 : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 // CHECK-DAG: #[[$M1:.*]] =  affine_map<(d0, d1) -> (d1, d0, 0, 0)>
 // CHECK-DAG: #[[$M2:.*]] =  affine_map<(d0, d1) -> (0, 0, d1, d0)>
 // CHECK-DAG: #[[$M3:.*]] =  affine_map<(d0, d1) -> (d1, d0)>
%0 = linalg.generic {
     } -> tensor<5x2xf32>
   return %0 : tensor<5x2xf32>
 }
 
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %3 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %4 = get_closest_isolated_parent %3 : (!transform.any_op) -> !transform.any_op
+  %4 = get_parent_op %3 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %5 = transform.structured.vectorize %4  { disable_multi_reduction_to_contract_patterns, disable_transfer_permutation_map_lowering_patterns } : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 // CHECK-LABEL:   func @red_max_2d(
 func.func @red_max_2d(%arg0: tensor<4x4xf32>) -> tensor<4xf32> {
   // CHECK: %[[CMINF:.+]] = arith.constant dense<-3.402820e+38> : vector<4xf32>
func.func @red_max_2d(%arg0: tensor<4x4xf32>) -> tensor<4xf32> {
   } -> tensor<4xf32>
   return %red : tensor<4xf32>
 }
 
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %3 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %4 = get_closest_isolated_parent %3 : (!transform.any_op) -> !transform.any_op
+  %4 = get_parent_op %3 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %5 = transform.structured.vectorize %4 { vectorize_padding } : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 // CHECK-LABEL:   func @red_min_2d(
 func.func @red_min_2d(%arg0: tensor<4x4xf32>) -> tensor<4xf32> {
   // CHECK: %[[CMAXF:.+]] = arith.constant dense<3.402820e+38> : vector<4xf32>
func.func @red_min_2d(%arg0: tensor<4x4xf32>) -> tensor<4xf32> {
   } -> tensor<4xf32>
   return %red : tensor<4xf32>
 }
 
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %3 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %4 = get_closest_isolated_parent %3 : (!transform.any_op) -> !transform.any_op
+  %4 = get_parent_op %3 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %5 = transform.structured.vectorize %4 : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 // CHECK-LABEL:   func @red_mul_2d(
 func.func @red_mul_2d(%arg0: tensor<4x4xf32>) -> tensor<4xf32> {
   // CHECK: tensor.empty() : tensor<4xf32>
func.func @red_mul_2d(%arg0: tensor<4x4xf32>) -> tensor<4xf32> {
   } -> tensor<4xf32>
   return %red : tensor<4xf32>
 }
 
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %3 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %4 = get_closest_isolated_parent %3 : (!transform.any_op) -> !transform.any_op
+  %4 = get_parent_op %3 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %5 = transform.structured.vectorize %4 : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 // CHECK-LABEL:   func @red_or_2d(
 func.func @red_or_2d(%arg0: tensor<4x4xi1>) -> tensor<4xi1> {
   // CHECK: tensor.empty() : tensor<4xi1>
func.func @red_or_2d(%arg0: tensor<4x4xi1>) -> tensor<4xi1> {
   } -> tensor<4xi1>
   return %red : tensor<4xi1>
 }
 
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %3 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %4 = get_closest_isolated_parent %3 : (!transform.any_op) -> !transform.any_op
+  %4 = get_parent_op %3 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %5 = transform.structured.vectorize %4 : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 // CHECK-LABEL:   func @red_and_2d(
 func.func @red_and_2d(%arg0: tensor<4x4xi1>) -> tensor<4xi1> {
   // CHECK: tensor.empty() : tensor<4xi1>
func.func @red_and_2d(%arg0: tensor<4x4xi1>) -> tensor<4xi1> {
   } -> tensor<4xi1>
   return %red : tensor<4xi1>
 }
 
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %3 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %4 = get_closest_isolated_parent %3 : (!transform.any_op) -> !transform.any_op
+  %4 = get_parent_op %3 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %5 = transform.structured.vectorize %4 : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 // CHECK-LABEL:   func @red_xor_2d(
 func.func @red_xor_2d(%arg0: tensor<4x4xi1>) -> tensor<4xi1> {
   // CHECK: tensor.empty() : tensor<4xi1>
func.func @red_xor_2d(%arg0: tensor<4x4xi1>) -> tensor<4xi1> {
   } -> tensor<4xi1>
   return %red : tensor<4xi1>
 }
 
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %3 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %4 = get_closest_isolated_parent %3 : (!transform.any_op) -> !transform.any_op
+  %4 = get_parent_op %3 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %5 = transform.structured.vectorize %4 : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 // CHECK-DAG: #[[$M5:.*]] = affine_map<(d0, d1) -> (d0, 0)>
 
 // CHECK-LABEL:   func @explicit_broadcast(
outs(%fill : tensor<4x4xf32>) {
     } -> tensor<4x4xf32>
   return %red : tensor<4x4xf32>
 }
 
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %3 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %4 = get_closest_isolated_parent %3 : (!transform.any_op) -> !transform.any_op
+  %4 = get_parent_op %3 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %5 = transform.structured.vectorize %4 : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 // CHECK-DAG: #[[$M6:.*]] = affine_map<(d0, d1) -> (d0, 0)>
 
 // CHECK-LABEL:   func @fused_broadcast_red_2d
outs(%fill : tensor<4xf32>) {
     } -> tensor<4xf32>
   return %red : tensor<4xf32>
 }
 
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.fill"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1 : (!transform.any_op) -> !transform.any_op
 
   %3 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %4 = get_closest_isolated_parent %3 : (!transform.any_op) -> !transform.any_op
+  %4 = get_parent_op %3 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %5 = transform.structured.vectorize %4 : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 //  CHECK-LABEL: func @reduce_1d(
 //   CHECK-SAME:   %[[A:.*]]: tensor<32xf32>
 func.func @reduce_1d(%arg0: tensor<32xf32>) -> tensor<f32> {
%2 = linalg.generic {
     } -> tensor<f32>
 
   return %2 : tensor<f32>
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1 : (!transform.any_op) -> !transform.any_op
 }
 
 
 // -----
 
 // This test checks that vectorization does not occur when an input indexing map
 // is not a projected permutation. In the future, this can be converted to a
^bb0(%arg7: f32, %arg9: f32):
       linalg.yield %arg7 : f32
     } -> tensor<6x6x3x3xf32>
   return %result : tensor<6x6x3x3xf32>
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1 : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 // Check vectorization can handle cases where outputs are a mix of reduced and non-reduced values.
 func.func @mixed_parallel_reduced_results(%arg0 : tensor<2x4x8xf32>,
     %arg1 : tensor<2x4xf32>, %arg2 : tensor<2x4x8xf32>, %arg3 : tensor<2x4xf32>) ->

 //   CHECK-DAG:   %[[MUL:.+]] = arith.mulf %[[V0]], %[[V1]]
 //   CHECK-DAG:   %[[ADD:.+]] = vector.multi_reduction <add>, %[[MUL]], %[[V2]]
 //   CHECK-DAG:   vector.transfer_write %[[MUL]], %[[ARG2]]
 //   CHECK-DAG:   vector.transfer_write %[[ADD]], %[[ARG3]]
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1  { disable_multi_reduction_to_contract_patterns, disable_transfer_permutation_map_lowering_patterns } : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 func.func @vectorize_map(%arg0: memref<64xf32>,
     %arg1: memref<64xf32>, %arg2: memref<64xf32>) {
   linalg.map ins(%arg0, %arg1 : memref<64xf32>, memref<64xf32>)
              outs(%arg2 : memref<64xf32>)
     (%in: f32, %in_0: f32) {
       %0 = arith.addf %in, %in_0 : f32
       linalg.yield %0 : f32
     }
   return
 }
 // CHECK-LABEL: func @vectorize_map
 // CHECK:         %[[LHS:.*]] = vector.transfer_read
 // CHECK-NEXT:    %[[RHS:.*]] = vector.transfer_read
 // CHECK-NEXT:    arith.addf %[[LHS]], %[[RHS]] : vector<64xf32>
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.map"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1 : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 func.func @vectorize_transpose(%arg0: memref<16x32x64xf32>,
                                %arg1: memref<32x64x16xf32>) {
   linalg.transpose ins(%arg0 : memref<16x32x64xf32>)
                    outs(%arg1 : memref<32x64x16xf32>) permutation = [1, 2, 0]
   return
 }
 // CHECK-LABEL: func @vectorize_transpose
 // CHECK:         vector.transpose
 // CHECK-SAME:      [1, 2, 0] : vector<16x32x64xf32> to vector<32x64x16xf32>
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.transpose"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1 : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 func.func @vectorize_reduce(%arg0: memref<16x32x64xf32>,
                   %arg1: memref<16x64xf32>) {
   linalg.reduce ins(%arg0 : memref<16x32x64xf32>)
                 outs(%arg1 : memref<16x64xf32>) dimensions = [1]
     (%in: f32, %init: f32) {
       %0 = arith.addf %in, %init : f32
       linalg.yield %0 : f32
     }
   return
 }
 // CHECK-LABEL: func @vectorize_reduce
 // CHECK:         vector.multi_reduction <add>
 // CHECK-SAME:    : vector<16x32x64xf32> to vector<16x64xf32>
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.reduce"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1 : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 // This is a regression test. This IR cannot be vectorized, but
 // structured.vectorize should nevertheless succeed. : (!transform.any_op) -> !transform.any_op
 
%1 = scf.for %arg0 = %c0 to %c64 step %c4 iter_args(%arg1 = %input) -> (tensor<120x64xf32>) {
     scf.yield %inserted_slice : tensor<120x64xf32>
   }
   return %1 : tensor<120x64xf32>
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1 : (!transform.any_op) -> !transform.any_op
 }
 
 // CHECK-LABEL: @wrong_reduction_detection
 // CHECK:         vector.broadcast
 // CHECK:         vector.transfer_write
 
 // -----
ins(%arg0 : tensor<0xf32>) outs(%arg1 : tensor<f32>) {
     linalg.yield %12 : f32
   } -> tensor<f32>
   return %0 : tensor<f32>
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1 : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 // CHECK-LABEL: func @test_masked_pad_static_dynamic
 func.func @test_masked_pad_static_dynamic(%arg0: tensor<1x2x2x?xf32>, %low: index, %high: index,
                   %pad_value: f32) -> tensor<6x?x?x?xf32> {
   // CHECK: tensor.pad
   %0 = tensor.pad %arg0 low[2, %low, 3, 3] high[3, 3, %high, 2] {
     ^bb0(%arg1: index, %arg2: index, %arg3: index, %arg4: index):
       tensor.yield %pad_value : f32
     } : tensor<1x2x2x?xf32> to tensor<6x?x?x?xf32>
   return %0 : tensor<6x?x?x?xf32>
 }
 
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["tensor.pad"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1  { vectorize_padding } : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 func.func @zero_dim_tensor(%input: tensor<f32>, %output: tensor<f32>) -> tensor<f32>
 {
   %0 = linalg.generic { indexing_maps = [ affine_map<() -> ()>, affine_map<() -> ()> ],
                         iterator_types = [] }
                         ins(%input : tensor<f32>)
                         outs(%output : tensor<f32>) {
     ^bb0(%arg0: f32, %arg1: f32):
       %2 = arith.addf %arg0, %arg1 : f32
       linalg.yield %2 : f32
     } -> tensor<f32>
   return %0 : tensor<f32>
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %3 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %4 = get_closest_isolated_parent %3 : (!transform.any_op) -> !transform.any_op
+  %4 = get_parent_op %3 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %5 = transform.structured.vectorize %4 : (!transform.any_op) -> !transform.any_op
 }
 
 // CHECK-LABEL: func @zero_dim_tensor
 //       CHECK:     vector.transfer_read {{.*}} : tensor<f32>, vector<f32>
 //       CHECK:     vector.extractelement
 //       CHECK:     vector.transfer_read {{.*}} : tensor<f32>, vector<f32>
 //       CHECK:     vector.extractelement
^bb0(%in: f32, %out: f32, %out_2: f32):
     linalg.yield %16, %16 : f32, f32
   } -> (tensor<4x1xf32>, tensor<1x4xf32>)
   return %13#0, %13#1 : tensor<4x1xf32>, tensor<1x4xf32>
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %3 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %4 = get_closest_isolated_parent %3 : (!transform.any_op) -> !transform.any_op
+  %4 = get_parent_op %3 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %5 = transform.structured.vectorize %4 : (!transform.any_op) -> !transform.any_op
 }
 
 // CHECK-LABEL: func @multi_output_generic_different_perm_maps
 //       CHECK:     %[[VAL_5:.*]] = vector.transfer_read %{{.*}} {in_bounds = [true, true]} : tensor<4x1xf32>, vector<4x1xf32>
 //       CHECK:     %[[VAL_6:.*]] = arith.addf %[[VAL_5]], %[[VAL_5]] : vector<4x1xf32>
 //       CHECK:     %[[VAL_7:.*]] = vector.transpose %[[VAL_6]], [1, 0] : vector<4x1xf32> to vector<1x4xf32>
 //       CHECK:     %[[VAL_8:.*]] = vector.transpose %[[VAL_7]], [1, 0] : vector<1x4xf32> to vector<4x1xf32>
 //       CHECK:     vector.transfer_write %[[VAL_8]], %{{.*}} {in_bounds = [true, true]} : vector<4x1xf32>, tensor<4x1xf32>
 //       CHECK:     vector.transfer_write %[[VAL_7]], %{{.*}} {in_bounds = [true, true]} : vector<1x4xf32>, tensor<1x4xf32>

mlir/test/Dialect/Linalg/vectorize-tensor-extract.mlir

 // CHECK: %[[BROADCAST:.*]] = vector.broadcast %[[CAST]]
 // CHECK: %[[INDICES:.*]] = vector.transpose %[[BROADCAST]]
 // CHECK: %[[GATHER:.*]] = vector.gather %[[ARG0]][%[[C0]]] [%[[INDICES]]], %[[MASK]], %[[PASSTHRU]]
 // CHECK: vector.transfer_write %[[GATHER]]
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1 : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
 
 #map1 = affine_map<(d0, d1, d2) -> (d0, d1, d2)>
 func.func @vectorize_nd_tensor_extract_constant_idx(%arg0: tensor<3x3xf32>, %arg2: tensor<1x1x3xf32>) -> tensor<1x1x3xf32> {
   %c0 = arith.constant 1 : index

 // CHECK:           %[[BCAST:.*]] = vector.broadcast %[[EXTRACT]] : f32 to vector<1x1x3xf32>
 // CHECK:           %[[VAL_7:.*]] = vector.transfer_write %[[BCAST]], %[[ARG_1]][%[[C0]], %[[C0]], %[[C0]]] {in_bounds = [true, true, true]} : vector<1x1x3xf32>, tensor<1x1x3xf32>
 // CHECK:           return %[[VAL_7]] : tensor<1x1x3xf32>
 // CHECK:         }
 
 transform.sequence failures(propagate) {
  ^bb1(%arg1: !transform.any_op):
    %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-   %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+   %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
    %2 = transform.structured.vectorize %1 { vectorize_nd_extract } : (!transform.any_op) -> !transform.any_op
  }
 
 // -----
 
 #map1 = affine_map<(d0, d1, d2) -> (d0, d1, d2)>
 func.func @vectorize_nd_tensor_extract_transfer_read_basic(%arg0: tensor<3x3x3xf32>, %arg2: tensor<1x1x3xf32>) -> tensor<1x1x3xf32> {
   %1 = linalg.generic {

 // CHECK:   %[[IDX_VEC:.*]] = vector.shape_cast %[[CST]] : vector<1x1x3xindex> to vector<3xindex>
 // CHECK:   %[[IDX2:.*]] = vector.extractelement %[[IDX_VEC]][%[[C0_i32]] : i32] : vector<3xindex>
 // CHECK:   %[[READ:.*]] = vector.transfer_read %[[ARG0]][%[[IDX1]], %[[IDX2]], %[[C0:.*]]], %[[CST_0]] {in_bounds = [true, true, true]} : tensor<3x3x3xf32>, vector<1x1x3xf32>
 // CHECK:   vector.transfer_write %[[READ]], %[[ARG1]][%[[C0]], %[[C0]], %[[C0]]] {in_bounds = [true, true, true]} : vector<1x1x3xf32>, tensor<1x1x3xf32>
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1 { vectorize_nd_extract } : (!transform.any_op) -> !transform.any_op
 }
 
  // -----
 
 func.func @vectorize_nd_tensor_extract_transfer_read_complex(%6: tensor<45x80x16xf32>, %arg0: index, %arg2: index, %arg1: index, %arg4: index, %extracted_slice : tensor<1x4xf32>) -> tensor<1x4xf32> {
   %c79 = arith.constant 79 : index
   %25 = linalg.generic {

 // CHECK:           %[[VAL_20:.*]] = vector.transfer_read %[[VAL_0]]{{\[}}%[[VAL_18]], %[[VAL_10]], %[[VAL_19]]], %[[VAL_8]] {in_bounds = [true, true]} : tensor<45x80x16xf32>, vector<1x4xf32>
 // CHECK:           %[[VAL_21:.*]] = vector.transfer_write %[[VAL_20]], %[[VAL_5]]{{\[}}%[[VAL_9]], %[[VAL_9]]] {in_bounds = [true, true]} : vector<1x4xf32>, tensor<1x4xf32>
 // CHECK:           return %[[VAL_21]] : tensor<1x4xf32>
 // CHECK:         }
 
 transform.sequence failures(propagate) {
  ^bb1(%arg1: !transform.any_op):
    %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-   %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+   %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
    %2 = transform.structured.vectorize %1 { vectorize_nd_extract } : (!transform.any_op) -> !transform.any_op
  }
 
 // -----
 
 #map0 = affine_map<(d0, d1, d2, d3) -> (d0, d2)>
 #map1 = affine_map<(d0, d1, d2, d3) -> (d0, d1, d3)>
 #map2 = affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)>

 // CHECK:    %[[ADDI:.*]] = arith.addi %[[B2]], %[[MULI]] : vector<7x2x4x3xindex>
 // CHECK:    %[[T:.*]] = vector.transpose %[[ADDI]], [2, 0, 3, 1] : vector<7x2x4x3xindex> to vector<4x7x3x2xindex>
 // CHECK:    %[[GATHER:.*]] = vector.gather %[[ARG0]][%[[C0]], %[[C0]]] [%[[T]]], %[[CST_1]], %[[PASSTHRU]] : tensor<3x3xf32>, vector<4x7x3x2xindex>, vector<4x7x3x2xi1>, vector<4x7x3x2xf32> into vector<4x7x3x2xf32>
 // CHECK:    vector.transfer_write %[[GATHER]], %[[ARG4]][%[[C0]], %[[C0]], %[[C0]], %[[C0]]] {in_bounds = [true, true, true, true]} : vector<4x7x3x2xf32>, tensor<4x7x3x2xf32>
 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-  %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+  %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   %2 = transform.structured.vectorize %1 { vectorize_nd_extract } : (!transform.any_op) -> !transform.any_op
 }
 // -----
 
 #map = affine_map<(d0) -> (d0)>
 func.func @vectorize_nd_tensor_extract_contiguous_and_gather(%arg0: tensor<6xf32>, %arg1: tensor<5xi32>) -> tensor<5xf32> {
  %c5 = arith.constant 5 : index
  %c0 = arith.constant 0 : index

 // CHECK:           %[[VAL_12:.*]] = arith.minsi %[[VAL_11]], %[[VAL_5]] : vector<5xindex>
 // CHECK:           %[[VAL_13:.*]] = vector.gather %[[VAL_0]]{{\[}}%[[VAL_2]]] {{\[}}%[[VAL_12]]], %[[VAL_6]], %[[VAL_7]] : tensor<6xf32>, vector<5xindex>, vector<5xi1>, vector<5xf32> into vector<5xf32>
 // CHECK:           %[[VAL_14:.*]] = vector.transfer_write %[[VAL_13]], %[[VAL_8]]{{\[}}%[[VAL_2]]] {in_bounds = [true]} : vector<5xf32>, tensor<5xf32>
 // CHECK:           return %[[VAL_14]] : tensor<5xf32>
 
 transform.sequence failures(propagate) {
  ^bb1(%arg1: !transform.any_op):
    %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-   %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+   %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
    %2 = transform.structured.vectorize %1 { vectorize_nd_extract } : (!transform.any_op) -> !transform.any_op
  }
 
 // -----
 
 // The vectorizer converts `affine.apply` so that the subsequent Ops can be vectorised based on the converted ops. Contiguous load.
 func.func @vectorize_nd_tensor_extract_with_affine_apply_contiguous(%6: tensor<80x16xf32>, %arg0: index, %extracted_slice : tensor<1x4xf32>) -> tensor<1x4xf32> {
   %c79 = arith.constant 79 : index

 // CHECK:           %[[VAL_11:.*]] = vector.transfer_read %[[VAL_0]]{{\[}}%[[VAL_7]], %[[VAL_10]]], %[[VAL_5]] {in_bounds = [true, true]} : tensor<80x16xf32>, vector<1x4xf32>
 // CHECK:           %[[VAL_12:.*]] = vector.transfer_write %[[VAL_11]], %[[VAL_2]]{{\[}}%[[VAL_6]], %[[VAL_6]]] {in_bounds = [true, true]} : vector<1x4xf32>, tensor<1x4xf32>
 // CHECK:           return %[[VAL_12]] : tensor<1x4xf32>
 // CHECK:         }
 
 transform.sequence failures(propagate) {
  ^bb1(%arg1: !transform.any_op):
    %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-   %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+   %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
    %2 = transform.structured.vectorize %1 { vectorize_nd_extract } : (!transform.any_op) -> !transform.any_op
  }
 
 // -----
 
 func.func @vectorize_nd_tensor_extract_with_tensor_extract(%input_1: tensor<1x20xi32>, %input_2: tensor<257x24xf32>, %arg0 : index, %arg1 : index, %arg2 : index, %arg3 : index) -> tensor<1x1x4xf32> {
   %c0 = arith.constant 0 : index
   %c256 = arith.constant 256 : index

 // The following `tensor.extract` from the generic Op s a contiguous load (all Ops used
 // for address calculation also satisfy the required conditions).
 // CHECK:           vector.transfer_read %[[INPUT_2]][%{{.*}}, %{{.*}}, %{{.*}} {in_bounds = [true, true]} : tensor<257x24xf32>, vector<1x4xf32>
 
 
 transform.sequence failures(propagate) {
  ^bb1(%arg1: !transform.any_op):
    %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-   %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+   %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
    %2 = transform.structured.vectorize %1 { vectorize_nd_extract } : (!transform.any_op) -> !transform.any_op
  }
 
 // -----
 
 // The vectorizer converts `affine.apply` so that the subsequent Ops can be vectorised based on the converted ops. Gather load.
 func.func @vectorize_nd_tensor_extract_with_affine_apply_gather(%6: tensor<80x16xf32>, %arg0: index, %extracted_slice : tensor<1x4xf32>) -> tensor<1x4xf32> {
   %c16 = arith.constant 16 : index

 // CHECK:           %[[VAL_13:.*]] = vector.gather %[[VAL_0]]{{\[}}%[[VAL_6]], %[[VAL_6]]] {{\[}}%[[VAL_12]]], %[[VAL_4]], %[[VAL_5]] : tensor<80x16xf32>, vector<1x4xindex>, vector<1x4xi1>, vector<1x4xf32> into vector<1x4xf32>
 // CHECK:           %[[VAL_14:.*]] = vector.transfer_write %[[VAL_13]], %[[VAL_2]]{{\[}}%[[VAL_6]], %[[VAL_6]]] {in_bounds = [true, true]} : vector<1x4xf32>, tensor<1x4xf32>
 // CHECK:           return %[[VAL_14]] : tensor<1x4xf32>
 // CHECK:         }
 
 transform.sequence failures(propagate) {
  ^bb1(%arg1: !transform.any_op):
    %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-   %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+   %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
    %2 = transform.structured.vectorize %1 { vectorize_nd_extract } : (!transform.any_op) -> !transform.any_op
  }
 
 // -----
 
 // Make sure that non-linear arithmetic operations (e.g. arith.maxsi) are allowed when calculating indices for load operations. Gather load.
 func.func @vectorize_nd_tensor_extract_with_maxsi_gather(%arg0: tensor<80x16xf32>, %extracted_slice : tensor<1x4xf32>) -> tensor<1x4xf32> {
   %c79 = arith.constant 79 : index

 // CHECK:           %[[VAL_9:.*]] = vector.gather %[[VAL_0]]{{\[}}%[[VAL_6]], %[[VAL_6]]] {{\[}}%[[VAL_8]]], %[[VAL_4]], %[[VAL_5]] : tensor<80x16xf32>, vector<1x4xindex>, vector<1x4xi1>, vector<1x4xf32> into vector<1x4xf32>
 // CHECK:           %[[VAL_10:.*]] = vector.transfer_write %[[VAL_9]], %[[VAL_1]]{{\[}}%[[VAL_6]], %[[VAL_6]]] {in_bounds = [true, true]} : vector<1x4xf32>, tensor<1x4xf32>
 // CHECK:           return %[[VAL_10]] : tensor<1x4xf32>
 // CHECK:         }
 
 transform.sequence failures(propagate) {
  ^bb1(%arg1: !transform.any_op):
    %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-   %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+   %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
    %2 = transform.structured.vectorize %1 { vectorize_nd_extract } : (!transform.any_op) -> !transform.any_op
  }
 
 // -----
 
 // Make sure that non-linear arithmetic operations (e.g. arith.maxsi) are allowed when calculating indices for load operations. Contiguous load.
 func.func @vectorize_nd_tensor_extract_with_maxsi_contiguous(%arg0: tensor<80x16xf32>, %extracted_slice : tensor<1x4xf32>) -> tensor<1x4xf32> {
   %c16 = arith.constant 16 : index

 // CHECK:           %[[VAL_8:.*]] = vector.transfer_read %[[VAL_0]]{{\[}}%[[VAL_7]], %[[VAL_4]]], %[[VAL_5]] {in_bounds = [true, true]} : tensor<80x16xf32>, vector<1x4xf32>
 // CHECK:           %[[VAL_9:.*]] = vector.transfer_write %[[VAL_8]], %[[VAL_1]]{{\[}}%[[VAL_4]], %[[VAL_4]]] {in_bounds = [true, true]} : vector<1x4xf32>, tensor<1x4xf32>
 // CHECK:           return %[[VAL_9]] : tensor<1x4xf32>
 // CHECK:         }
 
 transform.sequence failures(propagate) {
  ^bb1(%arg1: !transform.any_op):
    %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-   %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+   %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
    %2 = transform.structured.vectorize %1 { vectorize_nd_extract } : (!transform.any_op) -> !transform.any_op
  }
 
 // -----
 
 // The vectorizer assumes it's a gather load whenever using a block argument to calculate an index.
 #map = affine_map<(d0) -> (d0)>
 func.func @vectorize_nd_tensor_extract_block_arg(%arg0: tensor<5x6xf32>, %arg1: tensor<5xindex>) -> tensor<5xf32> {

 // CHECK:           %[[VAL_11:.*]] = vector.gather %[[VAL_0]]{{\[}}%[[VAL_2]], %[[VAL_2]]] {{\[}}%[[VAL_10]]], %[[VAL_4]], %[[VAL_5]] : tensor<5x6xf32>, vector<5xindex>, vector<5xi1>, vector<5xf32> into vector<5xf32>
 // CHECK:           %[[VAL_12:.*]] = vector.transfer_write %[[VAL_11]], %[[VAL_7]]{{\[}}%[[VAL_2]]] {in_bounds = [true]} : vector<5xf32>, tensor<5xf32>
 // CHECK:           return %[[VAL_12]] : tensor<5xf32>
 // CHECK:         }
 
 transform.sequence failures(propagate) {
  ^bb1(%arg1: !transform.any_op):
    %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-   %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+   %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
    %2 = transform.structured.vectorize %1 { vectorize_nd_extract } : (!transform.any_op) -> !transform.any_op
  }

mlir/test/Dialect/Transform/expensive-checks.mlir

pdl.pattern @return : benefit(1) {
     %2 = operation "func.return"(%0 : !pdl.range<value>) -> (%1 : !pdl.range<type>)
     rewrite %2 with "transform.dialect"
   }
 
   sequence %arg0 : !transform.any_op failures(propagate) {
   ^bb1(%arg1: !transform.any_op):
     // expected-note @below {{handle to invalidated ops}}
     %0 = pdl_match @return in %arg1 : (!transform.any_op) -> !transform.any_op
-    %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+    %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
     // expected-note @below {{invalidated by this transform op that consumes its operand #0}}
     test_consume_operand %1 : !transform.any_op
     // expected-error @below {{op uses a handle invalidated by a previously executed transform op}}
     test_print_remark_at_operand %0, "remark" : !transform.any_op
   }
 }
 
 // -----

mlir/test/Dialect/Transform/selective-targeting.mlir

pdl.pattern @pdl_target_attrC : benefit(1) {
     rewrite %0 with "transform.dialect"
   }
 
   transform.sequence %arg0 : !transform.any_op failures(propagate) {
   ^bb1(%arg1: !transform.any_op):
     %0 = pdl_match @pdl_target_attrA in %arg1 : (!transform.any_op) -> !transform.any_op
     transform.structured.tile %0 [4, 4, 4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
     %1 = pdl_match @pdl_target_attrC in %arg1 : (!transform.any_op) -> !transform.any_op
-    %2 = transform.get_closest_isolated_parent %1 : (!transform.any_op) -> !transform.any_op
+    %2 = get_parent_op %1 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
     transform.structured.vectorize %2 : (!transform.any_op) -> !transform.any_op
   }
 }
 
 // -----
 
 // CHECK-LABEL: @vectorize_one
 func.func @vectorize_one(
pdl.pattern @pdl_target : benefit(1) {
     %0 = operation "linalg.matmul"(%args : !pdl.range<value>) {"test.attrA" = %attr}-> (%results : !pdl.range<type>)
     // TODO: we don't want this, but it is the required terminator for pdl.pattern
     rewrite %0 with "transform.dialect"
   }
 
   transform.sequence %arg0 : !transform.any_op failures(propagate) {
   ^bb1(%arg1: !transform.any_op):
     %0 = pdl_match @pdl_target in %arg1 : (!transform.any_op) -> !transform.any_op
-    %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+    %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
     transform.structured.vectorize %1 : (!transform.any_op) -> !transform.any_op
   }
 }
 
 // -----
 
 // CHECK-LABEL: @vectorize_all
 func.func @vectorize_all(

mlir/test/Dialect/Transform/test-interpreter.mlir

pdl.pattern @const : benefit(1) {
     %r = pdl.types
     %0 = pdl.operation "arith.constant" -> (%r : !pdl.range<type>)
     pdl.rewrite %0 with "transform.dialect"
   }
 
   transform.sequence %arg0 : !transform.any_op failures(propagate) {
   ^bb1(%arg1: !transform.any_op):
     %f = pdl_match @const in %arg1 : (!transform.any_op) -> !transform.any_op
-    %m = get_closest_isolated_parent %f : (!transform.any_op) -> !transform.any_op
+    %m = get_parent_op %f {isolated_from_above} : (!transform.any_op) -> !transform.any_op
     test_print_remark_at_operand %m, "parent function" : !transform.any_op
   }
 }
 
 // -----
 
 func.func @foo() {
   %0 = arith.constant 0 : i32
pdl.pattern @match_call : benefit(1) {
     %1 = pdl.types
     %2 = pdl.operation "func.call"(%0 : !pdl.range<value>) -> (%1 : !pdl.range<type>)
     pdl.rewrite %2 with "transform.dialect"
   }
 
   transform.sequence %arg0 : !transform.any_op failures(propagate) {
   ^bb1(%arg1: !transform.any_op):
     %0 = pdl_match @match_call in %arg1 : (!transform.any_op) -> !transform.any_op
-    %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+    %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
     // expected-error @below {{all alternatives failed}}
     transform.alternatives %1 : !transform.any_op {
     ^bb2(%arg2: !transform.any_op):
       %2 = transform.pdl_match @match_call in %arg2 : (!transform.any_op) -> !transform.any_op
       // expected-remark @below {{applying}}
       transform.test_emit_remark_and_erase_operand %2, "applying" {fail_after_erase} : !transform.any_op
     }
   }
pdl.pattern @match_call : benefit(1) {
     %1 = pdl.types
     %2 = pdl.operation "func.call"(%0 : !pdl.range<value>) -> (%1 : !pdl.range<type>)
     pdl.rewrite %2 with "transform.dialect"
   }
 
   transform.sequence %arg0 : !transform.any_op failures(propagate) {
   ^bb1(%arg1: !transform.any_op):
     %0 = pdl_match @match_call in %arg1 : (!transform.any_op) -> !transform.any_op
-    %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+    %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
     transform.alternatives %1 : !transform.any_op {
     ^bb2(%arg2: !transform.any_op):
       %2 = transform.pdl_match @match_call in %arg2 : (!transform.any_op) -> !transform.any_op
       // expected-remark @below {{applying}}
       transform.test_emit_remark_and_erase_operand %2, "applying" {fail_after_erase} : !transform.any_op
     }, {
     ^bb2(%arg2: !transform.any_op):
       %2 = transform.pdl_match @match_call in %arg2 : (!transform.any_op) -> !transform.any_op
pdl.pattern @match_call : benefit(1) {
     %1 = pdl.types
     %2 = pdl.operation "func.call"(%0 : !pdl.range<value>) -> (%1 : !pdl.range<type>)
     pdl.rewrite %2 with "transform.dialect"
   }
 
   transform.sequence %arg0 : !transform.any_op failures(propagate) {
   ^bb1(%arg1: !transform.any_op):
     %0 = pdl_match @match_call in %arg1 : (!transform.any_op) -> !transform.any_op
-    %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+    %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
     transform.alternatives %1 : !transform.any_op {
     ^bb2(%arg2: !transform.any_op):
       %2 = transform.pdl_match @match_call in %arg2 : (!transform.any_op) -> !transform.any_op
       // expected-remark @below {{applying}}
       transform.test_emit_remark_and_erase_operand %2, "applying" {fail_after_erase} : !transform.any_op
     }, {
     ^bb2(%arg2: !transform.any_op):
       %2 = transform.pdl_match @match_call in %arg2 : (!transform.any_op) -> !transform.any_op
pdl.pattern @match_call : benefit(1) {
     %1 = pdl.types
     %2 = pdl.operation "func.call"(%0 : !pdl.range<value>) -> (%1 : !pdl.range<type>)
     pdl.rewrite %2 with "transform.dialect"
   }
 
   transform.sequence %arg0 : !transform.any_op failures(propagate) {
   ^bb1(%arg1: !transform.any_op):
     %0 = pdl_match @match_call in %arg1 : (!transform.any_op) -> !transform.any_op
-    %1 = get_closest_isolated_parent %0 : (!transform.any_op) -> !transform.any_op
+    %1 = get_parent_op %0 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
     %2 = transform.alternatives %1 : !transform.any_op -> !transform.any_op {
     ^bb2(%arg2: !transform.any_op):
       %3 = transform.pdl_match @match_call in %arg2 : (!transform.any_op) -> !transform.any_op
       // expected-remark @below {{applying}}
       transform.test_emit_remark_and_erase_operand %3, "applying" {fail_after_erase} : !transform.any_op
       %4 = transform.test_produce_self_handle_or_forward_operand %3 : (!transform.any_op) -> !transform.any_op
       transform.yield %4 : !transform.any_op
     }, {

 
 transform.sequence failures(propagate) {
 ^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match attributes{original} in %arg1 : (!transform.any_op) -> !transform.any_op
   %1 = transform.structured.match attributes{replacement} in %arg1 : (!transform.any_op) -> !transform.any_op
   test_notify_payload_op_replaced %0, %1 : (!transform.any_op, !transform.any_op) -> ()
   test_print_remark_at_operand %0, "updated handle" : !transform.any_op
 }
+
+// -----
+
+func.func @get_parent_op() {
+  // expected-remark @below{{found test.foo parent}}
+  "test.foo"() ({
+    // expected-remark @below{{direct parent}}
+    "test.bar"() ({
+      "test.qux"() : () -> ()
+      "test.qux"() : () -> ()
+    }) : () -> ()
+  }) : () -> ()
+}
+
+transform.sequence failures(propagate) {
+^bb1(%arg1: !transform.any_op):
+  %0 = transform.structured.match ops{["test.qux"]} in %arg1 : (!transform.any_op) -> !transform.any_op
+
+  // Get parent by name.
+  %1 = transform.get_parent_op %0 {op_name = "test.foo"} : (!transform.any_op) -> !transform.any_op
+  test_print_remark_at_operand %1, "found test.foo parent" : !transform.any_op
+
+  // Get immediate parent.
+  %2 = transform.get_parent_op %0 : (!transform.any_op) -> !transform.any_op
+  test_print_remark_at_operand %2, "direct parent" : !transform.any_op
+  // expected-remark @below{{2}}
+  test_print_number_of_associated_payload_ir_ops %2 : !transform.any_op
+
+  // Deduplicate results.
+  %3 = transform.structured.match ops{["test.qux"]} in %arg1 : (!transform.any_op) -> !transform.any_op
+  %4 = transform.get_parent_op %3 {deduplicate} : (!transform.any_op) -> !transform.any_op
+  // expected-remark @below{{1}}
+  test_print_number_of_associated_payload_ir_ops %4 : !transform.any_op
+}

mlir/test/Dialect/Vector/transform-vector.mlir

// CHECK: vector.store {{.*}} : memref<8x32xf32>, vector<4xf32>
   return %0 : tensor<8x32xf32>
 }
 
 transform.sequence failures(propagate) {
 ^bb1(%module_op: !transform.any_op):
   %0 = transform.structured.match ops{["linalg.matmul"]} in %module_op : (!transform.any_op) -> !transform.any_op
   %1, %loops:3 = transform.structured.tile %0 [8, 4, 2]
     : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
-  %2 = get_closest_isolated_parent %1 : (!transform.any_op) -> !transform.any_op
+  %2 = get_parent_op %1 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
   transform.structured.vectorize %2 : (!transform.any_op) -> !transform.any_op
   %b = transform.bufferization.one_shot_bufferize
       layout{IdentityLayoutMap} %module_op
       {bufferize_function_boundaries = true, allow_return_allocs = true}
       : (!transform.any_op) -> !transform.any_op
 
   %f = transform.structured.match ops{["func.func"]} in %b
     : (!transform.any_op) -> !transform.any_op

mlir/test/python/dialects/transform.py

def testNestedSequenceOpWithExtras():
     # CHECK-LABEL: TEST: testNestedSequenceOpWithExtras
     # CHECK: transform.sequence failures(propagate)
     # CHECK: ^{{.*}}(%[[ARG0:.*]]: !transform.any_op, %[[ARG1:.*]]: !transform.any_op, %[[ARG2:.*]]: !transform.op<"foo.bar">):
     # CHECK:   sequence %[[ARG0]], %[[ARG1]], %[[ARG2]] : (!transform.any_op, !transform.any_op, !transform.op<"foo.bar">)
 
 
 @run
 def testTransformPDLOps():
-    withPdl = transform_pdl.WithPDLPatternsOp(transform.AnyOpType.get())
-    with InsertionPoint(withPdl.body):
-        sequence = transform.SequenceOp(
             transform.FailurePropagationMode.PROPAGATE,
             [transform.AnyOpType.get()],
             withPdl.bodyTarget,
         )
-        with InsertionPoint(sequence.body):
-            match = transform_pdl.PDLMatchOp(
                 transform.AnyOpType.get(), sequence.bodyTarget, "pdl_matcher"
             )
-            transform.YieldOp(match)
-    # CHECK-LABEL: TEST: testTransformPDLOps
-    # CHECK: transform.with_pdl_patterns {
-    # CHECK: ^{{.*}}(%[[ARG0:.+]]: !transform.any_op):
-    # CHECK:   = sequence %[[ARG0]] : !transform.any_op -> !transform.any_op failures(propagate) {
-    # CHECK:   ^{{.*}}(%[[ARG1:.+]]: !transform.any_op):
-    # CHECK:     %[[RES:.+]] = pdl_match @pdl_matcher in %[[ARG1]]
-    # CHECK:     yield %[[RES]] : !transform.any_op
-    # CHECK:   }
-    # CHECK: }
 
 
 @run
-def testGetClosestIsolatedParentOp():
-    sequence = transform.SequenceOp(
+def testGetParentOp():
         transform.FailurePropagationMode.PROPAGATE, [], transform.AnyOpType.get()
     )
-    with InsertionPoint(sequence.body):
-        transform.GetClosestIsolatedParentOp(
-            transform.AnyOpType.get(), sequence.bodyTarget
-        )
-        transform.YieldOp()
-    # CHECK-LABEL: TEST: testGetClosestIsolatedParentOp
-    # CHECK: transform.sequence
-    # CHECK: ^{{.*}}(%[[ARG1:.+]]: !transform.any_op):
-    # CHECK:   = get_closest_isolated_parent %[[ARG1]]
+    transform.GetParentOp(
+        transform.AnyOpType.get(), sequence.bodyTarget, isolated_from_above=True
+  # CHECK-LABEL: TEST: testGetParentOp
+  # CHECK:   = get_parent_op %[[ARG1]] {isolated_from_above}
 
 
 @run
 def testMergeHandlesOp():
     sequence = transform.SequenceOp(
         transform.FailurePropagationMode.PROPAGATE, [], transform.AnyOpType.get()
     )
     with InsertionPoint(sequence.body):