std::vector<string> op_names) {
  OpList ops;
  absl::StatusOr<ApiDefMap> api_def_map =
      LoadOpsAndApiDefs(ops, false, api_def_dirs);

  TF_CHECK_OK(api_def_map.status());

  Env* env = Env::Default();
  absl::Status status;
  std::unique_ptr<WritableFile> fuzz_file = nullptr;
  for (const OpDef& op_def : ops.op()) {
    if (std::find(op_names.begin(), op_names.end(), op_def.name()) ==
        op_names.end())

               " $$(dirname $(location " + out_fuzz_files[0] + "))" +
               " " + api_def_src_locations + " " + (",".join(op_names))),
    )

    for op_name in op_names:
        cc_test(
            name = op_name.lower() + "_fuzz",
            srcs = [op_name + "_fuzz.cc"],
            deps = kernel_deps +
                   [
                       "//tensorflow/security/fuzzing/cc:fuzz_session",

namespace generator {

PathConfig::PathConfig(const string& output_dir, const string& source_dir,
                       const string& api_dir_list,
                       const std::vector<string> op_names)
    : output_path(output_dir), op_names(op_names) {
  api_dirs = str_util::Split(api_dir_list, ",", str_util::SkipEmpty());

  // Decompose the directory components given the output/source directories.
  //

struct PathConfig {
  string output_path;
  std::vector<string> op_names;
  std::vector<string> api_dirs;
  string tf_prefix_dir;
  string tf_root_dir;
  string tf_output_dir;

  explicit PathConfig() = default;
  explicit PathConfig(const string &output_dir, const string &source_dir,
                      const string &api_dir_list,
                      const std::vector<string> op_names);
};

}  // namespace generator

void Controller::BuildModel() {
  // Build the internal data model for the requested ops
  for (const auto& op_name : path_config_.op_names) {
    const OpDef* op_def = nullptr;
    TF_CHECK_OK(OpRegistry::Global()->LookUpOpDef(op_name, &op_def));
    CHECK(op_def != nullptr);  // Crash OK

    const ApiDef* api_def = api_def_map_->GetApiDef(op_name);
    CHECK(api_def != nullptr);  // Crash OK

      counted only if the ops are named 'op_name' and has 'attr_val' if
      'attr_name' is specified.
    """
    op_count = 0
    for op_name in op_names:
      # Check the main graph
      op_count += self._count_op_with_name_and_attribute(
          nodes=graphdef.node,
          op_name=op_name,
          attr_name=attr_name,
          attr_val=attr_val,
          get_op_name=get_op_name,

}

void TFE_GetExecutedOpNames(TFE_Context* ctx, TF_Buffer* buf,
                            TF_Status* status) {
  const std::vector<std::string>& op_names =
      tensorflow::unwrap(ctx)->GetLoggedOpsTestonly();

  std::ostringstream op_names_oss;
  for (const auto& op : op_names) {
    op_names_oss << op << ", ";
  }
  const std::string& op_names_str = op_names_oss.str();

                        false /* copy_names */));
}

Scope Scope::WithOpNameImpl(const string& op_name) const {
  if (impl()->single_use_scope()) {
    UpdateStatus(errors::InvalidArgument("Cannot set op name ", op_name,
                                         " on this scope"));
    return *this;
  }
  return Scope(new Impl(*this, Impl::Tags::OpName(), impl()->name_, op_name));
}

       bool copy_names);
  Impl(const Scope& other, Tags::OpName, const string& name,
       const string& op_name);
  Impl(const Scope& other, Tags::ControlDeps,
       std::vector<Operation> control_deps, bool clear_control_deps);
  Impl(const Scope& other, Tags::Device, const string& device);
  Impl(const Scope& other, Tags::SingleUseScope, const string& op_name);
  Impl(const Scope& other, Tags::ExitOnError);

  # TODO(fengliuai): support input_binding and output_binding so the arguments
  # are not positional.
  def __init__(self,
               op_name,
               inputs=None,
               attrs=None,
               derived_attrs=None,
               outputs=None):
    self._op_name = op_name
    self._inputs = inputs
    self._attrs = attrs
    self._derived_attrs = derived_attrs
    self._outputs = outputs