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())

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.
  //

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));
}

 private:
  friend class GraphContext;  // For access to op_.
  TF_Graph* g_;
  std::unique_ptr<TF_OperationDescription> op_;
  // Hold `op_type` and `op_name` till both are available since we need both
  // to build a graph operation.
  string op_type_;
  const char* op_name_ = nullptr;
  // TODO(srbs): Use this.
  string device_name_;
};

// GraphContext wraps a TF_Graph modeling a single function and manages the

namespace odml {

static bool isDenseI64Array(llvm::StringRef op_name,
                            llvm::StringRef field_name) {
  if (op_name == "stablehlo.broadcast" && field_name == "broadcast_sizes")
    return true;
  if (op_name == "stablehlo.broadcast_in_dim" &&
      field_name == "broadcast_dimensions")
    return true;
  if ((op_name == "stablehlo.convolution" ||
       op_name == "stablehlo.dynamic_conv") &&

  attrs_[attr_name] = TypeAttr::get(mlir_type);
  return absl::OkStatus();
}

Status MlirAbstractOp::SetOpName(const char* const op_name) {
  // TODO(aminim): should we use a location?
  if (op_name_) {
    return FailedPrecondition("SetOpName called on already built op.");
  }
  op_name_ = op_name;
  return absl::OkStatus();
}

Status MlirAbstractOp::AddRef(Type type, Type* output_type) {

  // Find the op names with tf or tfl dialect prefix, Ex: "tf.Abs" or "tfl.Abs".
  auto collectOps = [this](Operation *op) {
    const auto &op_name = op->getName().getStringRef().str();
    if (absl::StartsWith(op_name, "tf.") || absl::StartsWith(op_name, "tfl.")) {
      loc_to_name_.emplace(op->getLoc(), op_name);
    }
  };

  for (auto &region : module->getRegions()) {
    region.walk(collectOps);
  }