// meaningless value -1 for non resource outputs.
    out_desc.input_index =
        it != output_to_input_alias.end() ? it->getSecond() : -1;
    // MLIR-based TF-Compiler bridge doesn't support tensorlist output yet.
    // TODO(ycao): Support tensorlist-type output.
    out_desc.is_tensor_list = false;
  }

  // XLA computation always uses Tuple shape.
  *xla_output_shape = xla::ShapeUtil::MakeTupleShape(shapes);

    name = "tensor_types_test_util",
    testonly = True,
    hdrs = ["tensor_types_test_util.h"],
    deps = [
        "//tensorflow/c:tf_datatype",
    ],
)

tf_cc_test(
    name = "tensor_test",
    srcs = [
        "tensor_test.cc",
    ],
    deps = [
        ":tensor_types_test_util",
        "//tensorflow/c:tf_datatype",
        "//tensorflow/cc/experimental/base/public:status",

    }
  };

  while (!worklist.empty()) {
    tensorlist = worklist.top();
    worklist.pop();

    // TensorLists are semantically immutable. For example, TensorListSetItem
    // takes a TensorList as input and produces a TensorList as output. So to
    // traverse modifications to TensorList and verify that all elements written

             "legalized by this pass, then the IR won't be changed so that "
             "tensorlist ops can pass through (default false).">,
      Option<
        "default_to_single_batch_", "default-to-single-batch", "bool", "false",
        "When specified to true, if the tensorlist ops has unspecified batch "
        "size, this pass will assume that the batch size is one to proceed "

  OpBuilder builder(list);
  llvm::SmallVector<int64_t, 8> element_shape;
  // Infer TensorList element shape from the return type first, and then from
  // the const element shape operand. We first check the return type because
  // shape inference might have successfully inferred the element shape from
  // write operations on the TensorList.
  if (failed(GetElementShapeFromResultType(list.getType(), &element_shape))) {

  // If `emit_builtin_tflite_ops` is true, TF Lite legalization passes will be
  // added, which produces TF Lite ops.
  bool emit_builtin_tflite_ops = true;
  // If `lower_tensor_list_ops` is true, tensorlist ops will be lowered to basic
  // TF ops before legalization to TF Lite dialect.
  bool lower_tensor_list_ops = false;
  // The allowlist of functions that would be preserved after trimming.

        "//tensorflow/core/platform:status_matchers",
        "//tensorflow/core/platform:statusor",
    ],
)

tf_cc_test(
    name = "libtf_tensor_test",
    size = "medium",
    srcs = ["tests/tensor_test.cc"],
    tags = ["no_oss"],  # TODO(b/193268458): Need to disable TFRT.
    deps = [
        ":libtf",
        "//tensorflow/c:tf_status_helper",
        "//tensorflow/c/eager:abstract_context",

  let summary =
    "Replicate TensorList init ops for correct shape assignments in shape inference";

  let description = [{
    If we pass same TensorList to a while op as multiple arguments or just use
    the same TensorList at multiple places and assign different
    TensorListSetItem to elements of TensorList, the shape inference is then

    llvm::cl::init(false));

// NOLINTNEXTLINE
opt<bool> legalize_custom_tensor_list_ops(
    "legalize-custom-tensor-list-ops",
    llvm::cl::desc("Convert \"tf.TensorList*\" ops to \"tfl.custom_op\""
                   "if they can all be supported."),
    llvm::cl::init(false));

// NOLINTNEXTLINE
opt<bool> serialize_stablehlo_ops(
    "serialize-stablehlo-ops",

    llvm::cl::location(emit_custom_ops), llvm::cl::init(false));

// NOLINTNEXTLINE
static opt<bool, true> lower_tensor_list_ops_flag(
    "lower-tensor-list-ops",
    llvm::cl::desc("Lower the TensorList ops within the TFLite dialect"),
    llvm::cl::location(lower_tensor_list_ops), llvm::cl::init(false));

// NOLINTNEXTLINE
static opt<bool, true> strip_debug_info_flag(