def LegalizeTensorListElementShape : Pat<(TF_TensorListElementShapeOp $input),
    (TFL_CustomOp (Size1InputRange $input),
    (CreateStringAttr<"\"TensorListElementShape\"">), (EmptyCustomOptions))>;

def LegalizeTensorListLength : Pat<(TF_TensorListLengthOp $input),
    (TFL_CustomOp (Size1InputRange $input),

// CHECK-LABEL: listElementShape
func.func @listElementShape(%arg0: tensor<!tf_type.variant<tensor<*xi32>>>) -> tensor<*xi32> {
  %0 = "tf.TensorListElementShape"(%arg0) : (tensor<!tf_type.variant<tensor<*xi32>>>) -> tensor<*xi32>
  // CHECK: %0 = "tfl.custom"(%arg0) <{custom_code = "TensorListElementShape", custom_option = #tfl<const_bytes : "0x">}> : (tensor<!tf_type.variant<tensor<*xi32>>>) -> tensor<*xi32>
  func.return %0 : tensor<*xi32>
}

// CHECK-LABEL: func @testTensorListElementShape
func.func @testTensorListElementShape(%arg0: tensor<!tf_type.variant<tensor<2x4xf32>>>) -> tensor<2xi32> {
  %0 = "tf.TensorListElementShape"(%arg0) : (tensor<!tf_type.variant<tensor<2x4xf32>>>) -> tensor<2xi32>
  // CHECK:         [[cst:%.*]] = "tf.Const{{.*}} dense<{{\[}}2, 4]> : tensor<2xi32>
  // CHECK-NEXT:    return [[cst]] : tensor<2xi32>

  // CHECK: %[[SHAPE:.*]] = "tf.Const"() <{value = dense<[8, 9]> : tensor<2xi64>}> : () -> tensor<2xi64>
  %shape = "tf.TensorListElementShape"(%tl) : (tensor<!tf_type.variant<tensor<8x9xf32>>>) -> tensor<2xi64>
  // CHECK-NEXT: return %[[SHAPE]] : tensor<2xi64>
  func.return %shape: tensor<2xi64>
}

// -----

// Test tensor list gather op.

  // because it would be trivial.
  Output dummy_cast =
      ops::Cast(root.WithOpName("test/dummy_cast"), dummy_input, DT_INT32);

  Output tensor_list_element_shape = ops::TensorListElementShape(
      root.WithOpName("test/tensor_list_element_shape"), variant_input,
      DT_INT32);

  root.graph()->AddControlEdge(dummy_cast.node(),
                               tensor_list_element_shape.node());

    %shape_32 = "tf.TensorListElementShape"(%tl_1) : (tensor<!tf_type.variant<tensor<?x1xf32>>>) -> tensor<?xi32>
    %shape_64 = "tf.TensorListElementShape"(%tl_1) : (tensor<!tf_type.variant<tensor<?x1xf32>>>) -> tensor<?xi64>
    // CHECK: %[[CAST:.*]] = "tf.Cast"(%[[ELEMENT_SHAPE]]){{.*}}: (tensor<2xi32>) -> tensor<2xi64>

      "TensorArrayScatterV3",
      "TensorArraySizeV3",
      "TensorArraySplitV3",
      "TensorArrayV3",
      "TensorArrayWriteV3",
      "TensorListConcatV2",
      "TensorListElementShape",
      "TensorListFromTensor",
      "TensorListGather",
      "TensorListGetItem",
      "TensorListLength",
      "TensorListPopBack",
      "TensorListPushBack",
      "TensorListReserve",

        add_to_worklist(use.getOwner()->getResult(use.getOperandNumber()));
        continue;
      }
      // Refining the tensor list element type might change the output of
      // TensorListElementShape which is expected to be the originally assigned
      // shape to TensorList init ops. So replace it with the original element
      // shape value.
      if (auto tl_element_shape =

  );

  TF_DerivedOperandTypeAttr shape_type = TF_DerivedOperandTypeAttr<1>;
  TF_DerivedResultTypeAttr element_dtype = TF_DerivedResultTypeAttr<0>;
}

def TF_TensorListElementShapeOp : TF_Op<"TensorListElementShape", [Pure]> {
  let summary = "The shape of the elements of the given list, as a tensor.";

  let description = [{
input_handle: the list
  element_shape: the shape of elements of the list
  }];