and:
        NativeBinaryRules.assignTools(binary, toolChains, tmpDir.testDirectory)

        then:
        executableFile.file == tmpDir.testDirectory.file("exe/comp_name/exe_name")
        installation.directory == tmpDir.testDirectory.file("install/comp_name")
    }

    def "test shared library"() {
        def binary = initBinary(SharedLibraryBinarySpecInternal, NativeLibrarySpec)

        when:

  # 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

  // 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);
  }

               " $$(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",

  const string mul_op_name = linear.GetUniqueNameForOp("mul");
  const string bias_add_op_name = linear.GetUniqueNameForOp("bias_add");
  auto cop_names = AnotherCompositeOp(cop_scopes.last);
  return {mul_op_name, bias_add_op_name, cop_names[0], cop_names[1],
          cop_names[2]};
}

}  // namespace

TEST(ScopeTest, CompositeOp) {
  Scope root = Scope::NewRootScope();
  const auto names1 = LinearOp(root);

    all_dec_args.update(kw_dec_args)

    op_name = all_dec_args['op_name']
    op_def = op_def_registry.get(op_name)
    if op_def:
      if len(all_dec_args) > 1:
        # Op has been registered, so it is a user error to specify op def.
        raise ValueError('Op has been registered: ' + op_name)
      else:
        # Op has been registered, then we don't need to generate register code.

namespace tracing {

Status MaybeSetOpName(AbstractOperation* op, const char* op_name) {
  if (isa<TracingOperation>(op)) {
    TF_RETURN_IF_ERROR(dyn_cast<TracingOperation>(op)->SetOpName(op_name));
  }
  if (isa<gradients::TapeOperation>(op)) {
    TF_RETURN_IF_ERROR(MaybeSetOpName(
        dyn_cast<gradients::TapeOperation>(op)->GetBackingOperation(),
        op_name));
  }
  return absl::OkStatus();
}
}  // namespace tracing

	_ = x[OpMuxServerMsg-10]
	_ = x[OpUnblockSrvMux-11]
	_ = x[OpUnblockClMux-12]
	_ = x[OpAckMux-13]
	_ = x[OpRequest-14]
	_ = x[OpResponse-15]
	_ = x[OpDisconnect-16]
	_ = x[OpMerged-17]
}

const _Op_name = "ConnectConnectResponsePingPongConnectMuxMuxConnectErrorDisconnectClientMuxDisconnectServerMuxMuxClientMsgMuxServerMsgUnblockSrvMuxUnblockClMuxAckMuxRequestResponseDisconnectMerged"

using tensorflow::OpRegistrationData;
using tensorflow::OpRegistry;
using tensorflow::Status;

namespace {

void Register(const std::string& op_name, OpRegistry* registry) {
  registry->Register([op_name](OpRegistrationData* op_reg_data) -> Status {
    op_reg_data->op_def.set_name(op_name);
    return absl::OkStatus();
  });
}

}  // namespace

TEST(TfTextUtilsTest, TestTfTextRegistered) {

}

}  // namespace

void RegisterCostFunction(absl::string_view op_name,
                          CostFunction cost_function) {
  RegisterCostFunction(GetCostFunctionRegistry(), op_name,
                       std::move(cost_function));
}

bool HasCostFunctionRegistered(absl::string_view op_name) {
  return GetCostFunctionRegistry().contains(op_name);
}

int64_t CostAnalysis::GetCost(mlir::Operation* op) const {