// CHECK-SAME: 1x42
  %0 = "tf.AnonymousIterator"() {output_shapes = [
    #tf_type.shape<1x42>], output_types = [f32]} : () -> tensor<!tf_type.resource>
  // CHECK: "tf.Iterator"
  // CHECK-SAME: 2x42
  %1, %2 = "tf.AnonymousIteratorV2"() {output_shapes = [
    #tf_type.shape<2x42>], output_types = [f32]} : () -> (tensor<!tf_type.resource>, tensor<!tf_type.variant>)
  // CHECK: "tf.Iterator"
  // CHECK-SAME: 3x42

  REGISTER_KERNEL_BUILDER(Name("AnonymousIterator").Device(DEVICE),            \
                          data::AnonymousIteratorHandleOp);                    \
  REGISTER_KERNEL_BUILDER(Name("AnonymousIteratorV2").Device(DEVICE),          \
                          data::AnonymousIteratorHandleOp);                    \
  REGISTER_KERNEL_BUILDER(Name("AnonymousIteratorV3").Device(DEVICE),          \

    // expected-remark@above {{ID: 7}}
    %island = tf_executor.island {
        // expected-remark@above {{ID: 5}}
        // expected-remark@above {{Successors: {6}}}
        %handle, %deleter = "tf.AnonymousIteratorV2"() {_class = ["loc:@GeneratorDataset_2"], device = "/job:tpu_host_worker/replica:0/task:0/device:CPU:0", output_shapes = [#tf_type.shape<>], output_types = [!tf_type.string]} : () -> (tensor<!tf_type.resource>, tensor<!tf_type.variant>)

resource sharing by name, and does not keep a reference to the resource
container.}], [TF_DatasetIteratorAlloc]>:$handle
  );
}

def TF_AnonymousIteratorV2Op : TF_Op<"AnonymousIteratorV2", [TF_UniqueResourceAllocation]> {
  let summary = "A container for an iterator resource.";

  let arguments = (ins
    ConfinedAttr<TypeArrayAttr, [ArrayMinCount<1>]>:$output_types,