"Unable to find the dequeue node in the TF graph.");
    return nullptr;
  }

  VLOG(1) << "Running the dequeue op";
  TF_Output output{dequeue_op, 0};
  TF_Tensor* ret;
  TF_SessionRun(session, /*run_options*/ nullptr,
                // input related parameters
                /*inputs*/ nullptr, /*input_values*/ nullptr, /*ninputs*/ 0,
                // output related parameters

      *graph_def.mutable_versions() = graph.versions();
      // Fill graph_def with nodes with ids in the range
      // [session->last_num_graph_nodes, num_nodes), that is the nodes
      // added since the last TF_SessionRun() call.
      for (auto id = session->last_num_graph_nodes; id < num_nodes; ++id) {
        Node* const node = graph.FindNodeId(id);
        if (node != nullptr && node->IsOp()) {

  TF_Output feeds[] = {{x, 0}, {y, 0}};
  TF_Tensor* feedValues[] = {FloatTensor(X), FloatTensor(Y)};
  TF_Output fetches[] = {dxy_dx, dxy_dy};
  TF_Tensor* fetchValues[] = {nullptr, nullptr};

  TF_SessionRun(sess, nullptr /* run_options */, feeds, feedValues, 2, fetches,
                fetchValues, 2, nullptr /* target_opers */, 0,
                nullptr /* run_metadata */, s_);
  TF_DeleteTensor(feedValues[0]);

    previously `TF_Session` has been renamed to `TF_DeprecatedSession`.
*   C API: Renamed `TF_Port` to `TF_Output`.
*   C API: The caller retains ownership of `TF_Tensor` objects provided to
    `TF_Run`, `TF_SessionRun`, `TF_SetAttrTensor` etc.
*   Renamed `tf.image.per_image_whitening()` to
    `tf.image.per_image_standardization()`
*   Move Summary protobuf constructors to `tf.summary` submodule.