if (fflush(posix_file->handle) != 0)
    TF_SetStatusFromIOError(status, errno, posix_file->filename);
}

static void Sync(const TF_WritableFile* file, TF_Status* status) {
  // For historical reasons, this does the same as `Flush` at the moment.
  // TODO(b/144055243): This should use `fsync`/`sync`.
  Flush(file, status);
}

static void Close(const TF_WritableFile* file, TF_Status* status) {

// executed in sequence. Assigning nodes to different executors allows executing
// nodes in parallel.
// in_flight_nodes_limit: when is_async is true, this value controls the
// maximum number of in flight async nodes. Enqueuing of additional async ops
// after the limit is reached blocks until some inflight nodes finishes.
// The effect is bounding the memory held by inflight TensorHandles that are

}

// Note: this function looks up a thread local policy. So it should be called in
// the appropriate client thread. In particular, in async mode, it may not be
// safe to call this function from the async EagerExecutor threads.
extern TFE_ContextDevicePlacementPolicy TFE_ContextGetDevicePlacementPolicy(
    TFE_Context* ctx) {
  return static_cast<TFE_ContextDevicePlacementPolicy>(

*   `tf.distribute`:
    *   Support added for global sync `BatchNormalization` by using the newly
        added `tf.keras.layers.experimental.SyncBatchNormalization` layer. This
        layer will sync `BatchNormalization` statistics every step across all
        replicas taking part in sync training.
    *   Performance improvements for GPU multi-worker distributed training using

      tensorflow::unwrap(cancellation_manager));
  status->status = absl::OkStatus();
}

TFE_Executor* TFE_NewExecutor(bool is_async, bool enable_streaming_enqueue,
                              int in_flight_nodes_limit) {
  return new TFE_Executor(is_async, enable_streaming_enqueue,
                          in_flight_nodes_limit);
}

void TFE_DeleteExecutor(TFE_Executor* executor) { delete executor; }

    "if_google",
    "if_oss",
    "if_xla_available",
    "tf_cc_shared_object",
    "tf_custom_op_library_additional_deps_impl",
    "tf_monitoring_python_deps",
    "tf_native_cc_binary",
    "tsl_async_value_deps",
)
load(
    "//tensorflow:tensorflow.default.bzl",
    "ADDITIONAL_API_INDEXABLE_SETTINGS",
    "tf_cc_shared_library",
)
load(
    "@local_xla//xla/tsl/mkl:build_defs.bzl",
    "if_mkl_ml",
)