#include "xla/tsl/c/tsl_status_internal.h"
#include "xla/tsl/distributed_runtime/coordination/coordination_service_agent.h"
#include "tensorflow/core/common_runtime/composite_device.h"
#include "tensorflow/core/common_runtime/device.h"
#include "tensorflow/core/common_runtime/eager/eager_operation.h"
#include "tensorflow/core/distributed_runtime/coordination/coordination_service_error_util.h"
#include "tensorflow/core/framework/function.h"

    *   Added support for cross-trainer data caching in tf.data service. This
        saves computation resources when concurrent training jobs train from the
        same dataset. See
        (https://www.tensorflow.org/api_docs/python/tf/data/experimental/service#sharing_tfdata_service_with_concurrent_trainers)
        for more details.
    *   Added `dataset_id` to `tf.data.experimental.service.register_dataset`.

        "//tensorflow/core/distributed_runtime/eager:eager_client",
        "//tensorflow/core/distributed_runtime/rpc:grpc_channel",
        "//tensorflow/core/distributed_runtime/rpc:grpc_server_lib",
        "//tensorflow/core/distributed_runtime/rpc:grpc_worker_cache",
        "//tensorflow/core/distributed_runtime/rpc:grpc_worker_service",

        "@local_xla//xla/service:computation_placer",
        "//tensorflow/core",
        "//tensorflow/core/common_runtime/eager:context",
        "//tensorflow/core/common_runtime/eager:tensor_handle",
        "//tensorflow/core/config:flag_defs",
        "//tensorflow/core/config:flags",
        "//tensorflow/core/data/service:dispatcher_client",
        "//tensorflow/core/data/service:grpc_util",

    if _os.path.exists(_plugin_dir):
      _ll.load_library(_plugin_dir)
      # Load Pluggable Device Library
      _ll.load_pluggable_device_library(_plugin_dir)

if _os.getenv("TF_PLUGGABLE_DEVICE_LIBRARY_PATH", ""):
  _ll.load_pluggable_device_library(
      _os.getenv("TF_PLUGGABLE_DEVICE_LIBRARY_PATH")
  )

# Add Keras module aliases

}

void TF_SetRequestedDevice(TF_Graph* graph, TF_Operation* op,
                           const char* device) {
  using tensorflow::RecordMutation;
  mutex_lock l(graph->mu);
  op->node.set_requested_device(device);
  RecordMutation(graph, *op, "setting device");
}

void TF_RemoveAllControlInputs(TF_Graph* graph, TF_Operation* op) {
  mutex_lock l(graph->mu);

    srcs = ["c_api_experimental_test.cc"],
    data = [
        "testdata/tf_record",
        "//tensorflow/c/experimental/stream_executor/test:test_pluggable_device.so",
        "//tensorflow/core/common_runtime/next_pluggable_device/c:test_next_pluggable_device_plugin.so",
    ],
    extra_copts = if_google(["-DTENSORFLOW_NO_SHARED_OBJECTS=1"]),
    linkopts = select({
        "//tensorflow:macos": ["-headerpad_max_install_names"],

                              const char* device_name, void* device_info,
                              TF_Status* status) {
  // Fill in default values for optional functionality.
  if (device.pack == nullptr) {
    device.pack = &DefaultCustomDevicePack;
  }
  auto custom_device = std::make_unique<tensorflow::CustomDeviceAPI>(
      ctx, device, device_info, device_name);

  void Release() override { delete this; }
  Status Reset(const char* op, const char* raw_device_name) override {
    if (op_) {
      return errors::FailedPrecondition("Reset called on already built op.");
    }
    if (raw_device_name) {
      device_name_ = raw_device_name;
    }
    op_type_ = op;
    return absl::OkStatus();
  }
  Status SetOpName(const char* const op_name) override {

        output->Unref();
      }
      TF_RETURN_IF_ERROR(ctx->RegisterFunction(func));
    }

    AbstractOperationPtr fn_op(ctx->CreateOperation());
    TF_RETURN_IF_ERROR(fn_op->Reset(fn_name, /*raw_device_name=*/nullptr));
    for (auto input : inputs) {
      TF_RETURN_IF_ERROR(fn_op->AddInput(input));
    }
    int retvals = outputs.size() - null_indices.size();
    std::vector<AbstractTensorHandle*> fn_outputs(retvals);