return VerifyUnsortedSegmentReduction(*this);
}

//===----------------------------------------------------------------------===//
// VarHandleOp
//===----------------------------------------------------------------------===//

LogicalResult VarHandleOp::verify() {
  // VarHandleOp requires the resource handle supply a single subtype from
  // which to derive the dtype and shape attributes.

  %outputs_8  =  "tf.Const"() {device = "/job:localhost/replica:0/task:0/device:CPU:0", value = dense<1> : tensor<i32>} : () -> tensor<i32>
  // CHECK: [[elems:%.*]] = "tf.VarHandleOp"
  %outputs_10  =  "tf.VarHandleOp"() {_xla_inferred_shapes = [#tf_type.shape<>], allowed_devices = [], container = "", device = "/job:localhost/replica:0/task:0/device:CPU:0", shared_name = "w"} : () -> tensor<!tf_type.resource<tensor<3x1xf32>>>

  func.return %0 : tensor<*xf32>
}

// CHECK-LABEL: @erase_tf_var_is_initialized
func.func @erase_tf_var_is_initialized(%arg0 : tensor<!tf_type.resource<tensor<f32>>>) -> tensor<i1> {
  %vh = "tf.VarHandleOp"() {container = "", shape = "tfshape$", shared_name = "x"} : () -> tensor<!tf_type.resource<tensor<f32>>>
  %is = "tf.VarIsInitializedOp"(%vh) : (tensor<!tf_type.resource<tensor<f32>>>) -> tensor<i1>

    if (std::optional<absl::string_view> cluster_name =
            GetXlaClusterForNode(*n)) {
      n->set_name(absl::StrCat(*cluster_name, "/", n->name()));
    } else if (n->type_string() == "VarHandleOp") {
      n->set_name(absl::StrCat("varhandle/", n->name()));
    } else {
      // There is room for improvement here.  In particular, it may help to

  Args:
    node_def: `NodeDef` to test whether it is a variable or not.

  Returns:
    Returns True if it is a variable.
  """
  return node_def.op == 'VarHandleOp'


def _find_variables(
    graph_def: graph_pb2.GraphDef,
) -> Mapping[str, node_def_pb2.NodeDef]:
  """Finds all variables within `graph_def`.

See `tf.scatter_nd` for more details about how to make updates to
slices.
  }];

  let arguments = (ins
    Arg<TF_ResourceTensor, [{A resource handle. Must be from a VarHandleOp.}], [TF_VariableRead, TF_VariableWrite]>:$ref,
    Arg<TF_I32OrI64Tensor, [{A Tensor. Must be one of the following types: int32, int64.
A tensor of indices into ref.}]>:$indices,