TF_SetFilesystemVersionMetadata(ops);
  ops->scheme = strdup(uri);

  ops->random_access_file_ops = static_cast<TF_RandomAccessFileOps*>(
      plugin_memory_allocate(TF_RANDOM_ACCESS_FILE_OPS_SIZE));
  ops->random_access_file_ops->cleanup = tf_random_access_file::Cleanup;
  ops->random_access_file_ops->read = tf_random_access_file::Read;

  ops->writable_file_ops = static_cast<TF_WritableFileOps*>(

  return response;
}

int TF_DeviceListCount(const TF_DeviceList* list) {
  return list->response.size();
}

#define TF_DEVICELIST_METHOD(return_type, method_name, accessor, err_val) \
  return_type method_name(const TF_DeviceList* list, const int index,     \
                          TF_Status* status) {                            \

      tensorflow::ContextFromInterface(tensorflow::unwrap(ctx));
  auto collective_executor_handle = context->GetCollectiveExecutorHandle();
  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();
}

//
// DeviceThread itself is thread-safe, in that StartExecute will block if there
// is a pending execution. Since StartExecute is equivalent to grabbing a lock,
// multiple DeviceThreads should always be accessed in the same order to avoid
// deadlocks.
class DeviceThread {
 public:
  // Starts a background thread waiting for `StartExecute`.
  explicit DeviceThread(const std::string& device, const bool is_async,

  }
  // For LLVM style RTTI.
  static bool classof(const AbstractOperation* ptr) {
    return ptr->getKind() == kGraph;
  }
  ~GraphOperation() override {}

 private:
  friend class GraphContext;  // For access to op_.
  TF_Graph* g_;
  std::unique_ptr<TF_OperationDescription> op_;
  // Hold `op_type` and `op_name` till both are available since we need both
  // to build a graph operation.
  string op_type_;

    data[i] = 0;
  }
  if (TF_TensorDefaultAlignment() > 0) {
    EXPECT_TRUE(TF_TensorIsAligned(a));
  }
  TF_DeleteTensor(a);
}

TEST(CAPI, TestTensorIsNotAligned) {
  // Test unaligned access via a Slice.
  Tensor x(DT_FLOAT, TensorShape({30}));
  x.flat<float>().setConstant(0.0);

  // Take an unaligned slice.
  Tensor y = x.Slice(1, 13);
  Status status;