#include "tensorflow/core/platform/logging.h"

namespace tensorflow {

namespace {

// Managing context for the DLManagedTensor, will manage the lifetime of
// DLManagedTensor. When calling DLManagedTensor::deleter, it will notify the
// original framework of destruction, and this context will be deleted also.
struct TfDlManagedTensorCtx {
  TensorReference reference;
  std::vector<int64_t> shape;
  std::vector<int64_t> strides;

    }
    TF_VLog(1, "GCS file block cache is %s.\n",
            (IsCacheEnabled() ? "enabled" : "disabled"));
  }

  ~RamFileBlockCache() {
    if (pruning_thread_) {
      stop_pruning_thread_.Notify();
      // Destroying pruning_thread_ will block until Prune() receives the above
      // notification and returns.
      pruning_thread_.reset();
    }
  }

                     char* buffer, TF_Status* status) -> int64_t {
    EXPECT_EQ(n, block_size);
    EXPECT_EQ(offset, 0);
    num_requests++;
    memset(buffer, 'x', n);
    notification.Notify();
    // Wait for other thread to issue read.
    Env::Default()->SleepForMicroseconds(100000);  // 0.1 secs
    TF_SetStatus(status, TF_OK, "");
    return n;
  };

## Enforcement

  std::unique_ptr<Thread> thread_;
};

DeviceThread::~DeviceThread() {
  {
    tensorflow::mutex_lock l(execution_mutex_);
    execution_state_ = ExecutionState::kShuttingDown;
  }
  start_execute_.notify_one();
}

void DeviceThread::AsyncWait(TF_Status* status) {
  tensorflow::mutex_lock l(execution_mutex_);
  TFE_ExecutorWaitForAllPendingNodes(executor_.get(), status);
  TFE_ExecutorClearError(executor_.get());

  tensorflow::Notification done;
  collective_executor_handle->get()->remote_access()->CheckPeerHealth(
      task, timeout_in_ms, [&done, status](const Status& s) {
        status->status = s;
        done.Notify();
      });
  done.WaitForNotification();
}

TF_ShapeAndTypeList* TF_NewShapeAndTypeList(int num_items) {
  TF_ShapeAndTypeList* result = new TF_ShapeAndTypeList;
  result->num_items = num_items;