int64_t max_arg_size_ = 1;
  llvm::DenseMap<mlir::Operation*, int64_t> cost_map_;
  const tfrt_stub::CostRecorder* cost_recorder_;
};

struct CostContext {
  int64_t default_unranked_tensor_size;
};

using CostFunction =
    std::function<int64_t(const CostContext&, mlir::Operation*)>;

void RegisterCostFunction(absl::string_view op_name,
                          CostFunction cost_function);

  }

  return size;
}

int64_t InferTensorSize(const CostContext& context, mlir::TensorType type) {
  if (type.hasRank()) return GetRankedTensorSize(type);
  return context.default_unranked_tensor_size;
}

// The cost function for tf.LookupTableFindV2.
int64_t InferLookupTableFindV2Cost(const CostContext& context,
                                   mlir::TF::LookupTableFindV2Op op) {

// Creates a BEF file with a program that runs
// tfrt_fallback_async.batch_function with a empty function forwarding inputs or
// outputs.
std::pair<tfrt::BefBuffer, tfrt::RCReference<tfrt::BEFFile>> CreateBefFile(
    tfrt::HostContext* host) {
  std::string file_path = GetDataDependencyFilepath(
      "tensorflow/compiler/mlir/tfrt/tests/tfrt_fallback/"
      "batch_function_fallback.mlir.bef");

  std::string data;

                                    llvm::ArrayRef<Tensor> arguments);

 private:
  void RunTfrtInitializer();

  std::unique_ptr<thread::ThreadPoolInterface> intra_op_;
  std::unique_ptr<tfrt::HostContext> host_context_;
  tfrt::ResourceContext resource_context_;
  std::unique_ptr<tfrt::ExecutionContext> exec_ctx_;
  tfrt::BefBuffer bef_buffer_;
  tfrt::RCReference<tfrt::BEFFile> bef_file_;
};

 private:
  ThreadPool tpool_;
};
}  // namespace

RuntimeFallbackExecutor::RuntimeFallbackExecutor(int64_t num_threads)
    : intra_op_(std::make_unique<IntraOpThreadPool>(num_threads)) {
  // Create a HostContext for running TFRT functions. Concurrent work queue acts
  // similar to the Tensorflow `inter-op` thread pool, so we'll match the size.
  host_context_ = num_threads ? CreateMultiThreadedHostContext(num_threads)

        "@com_google_absl//absl/strings",
        "@com_google_googletest//:gtest_main",
        "@tf_runtime//:bef",
        "@tf_runtime//:befexecutor",
        "@tf_runtime//:core_runtime",
        "@tf_runtime//:hostcontext",
        "@tf_runtime//:init_tfrt_dialects",
        "@tf_runtime//:support",
        "@tf_runtime//:tracing",
    ],

        "@tf_runtime//:basic_kernels_alwayslink",
        "@tf_runtime//:bef",
        "@tf_runtime//:befexecutor",
        "@tf_runtime//:core_runtime_alwayslink",
        "@tf_runtime//:hostcontext",
        "@tf_runtime//:mlirtobef",
        "@tf_runtime//:support",
    ],
)

cc_library(
    name = "corert_converter",
    srcs = [
        "transforms/corert_converter.cc",
    ],

return c+s;});if(hostContext){selector=selector.replace(HOST_CONTEXT_PAREN,function(m,pre,paren,post){var replacement=pre+paren+' '+hostScope+post+COMPLEX_SELECTOR_SEP+' '+pre+hostScope+paren+post;if(dir){replacement+=...