// attributes.
  for (const tensorflow::OpDef::ArgDef& output_arg : op_def_->output_arg()) {
    int original_size = state_->types.size();
    if (!output_arg.number_attr().empty()) {
      // Same type repeated "repeats" times.
      Attribute repeats_attr = attrs_[output_arg.number_attr()];
      if (!repeats_attr)
        return InvalidArgument("Missing attribute '", output_arg.number_attr(),

    "'raw_outputs/class_predictions' type: DT_FLOAT } input_arg: { name: "
    "'anchors' type: DT_FLOAT } output_arg: { name: "
    "'TFLite_Detection_PostProcess' type: DT_FLOAT } output_arg: { name: "
    "'TFLite_Detection_PostProcess:1' type: DT_FLOAT } output_arg: { name: "
    "'TFLite_Detection_PostProcess:2' type: DT_FLOAT } output_arg: { name: "
    "'TFLite_Detection_PostProcess:3' type: DT_FLOAT } attr : { name: "

  in.mutable_composite_tensor()->add_components()->set_name("input1:0");
  in.mutable_composite_tensor()->add_components()->set_name("input2:0");

  TensorInfo& out = (*signature_def.mutable_outputs())["output_arg"];
  out.mutable_composite_tensor()->add_components()->set_name("output2:0");
  out.mutable_composite_tensor()->add_components()->set_name("output1:0");

  AddSignatureDefToSavedModelBundle(signature_def, "signature_def",

  EXPECT_EQ(f1_rewritten->signature().input_arg(1).type(), DT_RESOURCE);
  ASSERT_EQ(f1_rewritten->signature().output_arg_size(), 1);
  EXPECT_EQ(f1_rewritten->signature().output_arg(0).type(), DT_BOOL);

  // Check node "if" input and output edges.
  auto node_name_index = g->BuildNodeNameIndex();
  const Node *if_node = node_name_index.at("if");
  ASSERT_NE(if_node, nullptr);

      "    signature {"
      "      name: 'AddVariablesFunction'"
      "      input_arg {"
      "        name: 'var'"
      "        type: DT_RESOURCE"
      "      }"
      "      output_arg {"
      "        name: 'sum'"
      "        type: DT_FLOAT"
      "      }"
      "    }"
      "    node_def {"
      "      name: 'read0'"
      "      op: 'ReadVariableOp'"
      "      input: 'var'"

        // Add derived "result_segment_sizes" attr to the created operation.
        // TODO(b/146937733): Don't use <void> here.
        set_segment_sizes_attr(output_ranges, op_def->output_arg(),
                               mlir::OpTrait::AttrSizedResultSegments<
                                   void>::getResultSegmentSizeAttr());
      }
    }

    return success();
  }

 private:

  strings::StrAppend(out, "  }\n\n");

  for (int i = 0; i < op_info.graph_op_def.output_arg_size(); ++i) {
    const string arg_range = strings::StrCat(
        "_outputs_range[\"", op_info.graph_op_def.output_arg(i).name(), "\"]");
    if (op_info.is_list_output[i]) {
      strings::StrAppend(out, "  for (int32 i = ", arg_range, ".first; i < ",
                         arg_range, ".second; ++i)\n");

    const OpRegistrationData* op_reg;
    if (OpRegistry::Global()->LookUp(call_target.name(), &op_reg).ok()) {
      const OpDef& op = op_reg->op_def;
      if (absl::c_any_of(op.output_arg(), [](const OpDef::ArgDef arg) {
            return arg.is_ref();
          })) {
        return true;
      }
      continue;
    }

    callee_ref_nodes.clear();

  for (int i = 0; i < graph_op_def.output_arg_size(); ++i) {
    // ApiDef arguments must be in the same order as in OpDef since
    // we initialize ApiDef based on OpDef.
    const auto& arg = graph_op_def.output_arg(i);
    const auto& api_def_arg(api_def.out_arg(i));
    CHECK_EQ(arg.name(), api_def_arg.name());

    bool is_list = ArgIsList(arg);
    output_types.push_back(

        when:
        relocatedJarCreator.create(outputJar, [jarFile1, jarFile2, jarFile3, jarFile4, jarFile5, jarFile6, inputDirectory])

        then:

        TestFile[] contents = tmpDir.testDirectory.listFiles().findAll { it.isFile() }
        contents.length == 1
        contents[0] == outputJar
        handleAsJarFile(outputJar) { JarFile file ->
            List<JarEntry> entries = file.entries() as List