%tl0 = "tf.EmptyTensorList"(%element_shape, %max_size) : (tensor<1xi32>, tensor<i32>) -> tensor<!tf_type.variant<tensor<16xf32>>>
  // CHECK-NOT: tf.TensorListReserve
  // CHECK: tf.BroadcastTo
  // CHECK-SAME: tensor<10x32xf32>
  %tl1 = "tf.TensorListReserve"(%arg0, %max_size) : (tensor<*xi32>, tensor<i32>) -> tensor<!tf_type.variant<tensor<32xf32>>>
  func.return
}

// -----

  "tf_device.cluster"() ({
    // CHECK:      "tf.TensorListReserve"
    // CHECK-SAME: _xla_outside_compilation
    // CHECK:      "tf.TensorListGetItem"
    // CHECK-SAME: _xla_outside_compilation
    %0 = "tf.TensorListReserve"(%arg0, %arg1) : (tensor<i32>, tensor<i32>) -> tensor<!tf_type.variant<tensor<*x!tf_type.string>>>

      // zero reserved elements
      %num_elements = "tf.Const"() <{value = dense<0> : tensor<i32>}> {device = "/job:localhost/replica:0/task:0/device:CPU:0"} : () -> tensor<i32>

      %list = "tf.TensorListReserve"(%elem_shape, %num_elements) : (tensor<i32>, tensor<i32>) -> tensor<!tf_type.variant<tensor<64x1xbf16>>>

  }

  // CHECK-LABEL: not_allowlisted_op
  func.func @not_allowlisted_op(%arg0: tensor<3xi32>, %arg1: tensor<i32>, %arg2: tensor<i32>) -> tensor<?x?x?xf32> {
    // CHECK: tf.TensorListReserve
    %0 = "tf.TensorListReserve"(%arg0, %arg1) : (tensor<3xi32>, tensor<i32>) -> tensor<!tf_type.variant<tensor<?x?x?xf32>>>
    // CHECK: tf.TensorListGetItem

      %outputs_45, %control_46 = tf_executor.island wraps "tf.TensorListReserve"(%outputs_41, %outputs_43) {_tpu_replicate = "cluster_sample_sequence", device = ""} : (tensor<1xi32>, tensor<i32>) -> tensor<!tf_type.variant<tensor<*xf32>>>

  Output cast_a = ops::Cast(root.WithOpName("test/cast_a"), a, DT_INT32);
  Output cast_b = ops::Cast(root.WithOpName("test/cast_b"), b, DT_INT32);

  Output tensor_list_reserve = ops::TensorListReserve(
      root.WithOpName("test/tensor_list_reserve"), cast_a, cast_b, DT_FLOAT);

  std::unique_ptr<Graph> graph(new Graph(OpRegistry::Global()));
  TF_ASSERT_OK(root.ToGraph(graph.get()));

tensor list creation op are constant.

A tensor list creation op `tf.EmptyTensorList`/`tf.TensorListReserve` will be
turned in to a zero-initialized buffer, and the size is initialized to 0
for `tf.EmptyTensorList` or the specified size for `tf.TensorListReserve`.
Each push will be turned into `tf.XlaDynamicUpdateSlice` with the incremented

tensor list creation op are constant.

A tensor list creation op `tf.EmptyTensorList`/`tf.TensorListReserve` will be
turned in to a zero-initialized buffer, and the size is initialized to 0
for `tf.EmptyTensorList` or the specified size for `tf.TensorListReserve`.
Each push will be turned into `tf.XlaDynamicUpdateSlice` with the incremented

        }
      }
    }

    DenseIntElementsAttr dense_elem_attr;
    if (matchPattern(element_shape, m_Constant(&dense_elem_attr))) {
      // Note: It's technically unsafe to rewrite
      //     TensorListReserve(num_element, element_shape)
      // to
      //     Fill(Concat(num_element, element_shape), 0)
      // because element_shape may contain -1 to represent unknown dimension.
      //

  let regions = (region SizedRegion<1>:$cond, SizedRegion<1>:$body);

  let hasVerifier = 1;

  let hasCanonicalizer = 1;
}

def TF_TensorListReserveOp : TF_TensorListInitOp<"TensorListReserve"> {
  let summary = "List of the given size with empty elements.";

  let description = [{
element_shape: the shape of the future elements of the list
num_elements: the number of elements to reserve