if (!status->status.ok()) {
        // Contract is we always delete input_values[i].
        return false;
      }
      // Note: session->session is not modified if Extend() fails, so
      // we only set last_num_graph_nodes if it succeeds.
      session->last_num_graph_nodes = num_nodes;
    } else {
      session->graph->mu.unlock();
    }
  }
  return true;
}

  // `is_async` operations finish. In addition to allowing the caller to cancel
  // the operation, its `StartCancel` method will be called if op execution
  // fails on any device in order to cancel the others.
  void StartExecute(TFE_Context* context, const char* operation_name,
                    std::vector<TFE_TensorHandle*> inputs,

  // Create a new tensor_handle.
  TFE_TensorHandle* h0_task0_new = TestMatrixTensorHandle(ctx);

  // Check that copying it to the old remote device (named localhost) fails.
  TFE_TensorHandleCopyToDevice(h0_task0_new, ctx, remote_device_name, status);
  EXPECT_NE(TF_OK, TF_GetCode(status)) << TF_Message(status);

  // Copying and executing on the new remote device works.

  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());
  ASSERT_TRUE(executed);
  TFE_DeleteTensorHandle(retval);

  // Custom device: inputs in different custom devices fails.
  matmul.reset(MatMulOp(context.get(), hcustom0.get(), hcustom1.get()));
  num_retvals = 1;
  TFE_Execute(matmul.get(), &retval, &num_retvals, status.get());
  ASSERT_NE(TF_OK, TF_GetCode(status.get()));