Tensor* CreateHostTensor(const TensorShape& shape,
                           const gtl::ArraySlice<T> data) {
    Tensor* host_tensor =
        new Tensor(host_allocator_, DataTypeToEnum<T>::v(), shape);
    test::FillValues<T>(host_tensor, data);
    tensors_.push_back(host_tensor);
    return host_tensor;
  }

  // Creates a Tensor on device using the device_allocator_
  template <typename T>

  Tensor* CreateHostTensor(const TensorShape& shape,
                           const gtl::ArraySlice<T> data) {
    Tensor* host_tensor =
        new Tensor(host_allocator_, DataTypeToEnum<T>::v(), shape);
    test::FillValues<T>(host_tensor, data);
    tensors_.push_back(host_tensor);
    return host_tensor;
  }

  // Creates a Tensor on device using the device_allocator_
  template <typename T>

    for (const int old_tensor : std::vector<int>(operations_[iop].tensors)) {
      const auto new_tensor =
          std::lower_bound(new_tensors.begin(), new_tensors.end(),
                           std::make_pair(old_tensor, 0));
      if (new_tensor != new_tensors.end() && new_tensor->first == old_tensor) {
        DelUse(iop, old_tensor);
        AddUse(iop, new_tensor->second);
      }
    }

        args.device_context = new XlaHostRecvDeviceContext(
            stream, device_memory_base, shape, done_event);

        Tensor host_tensor;
        TF_RETURN_IF_ERROR(
            ctx->rendezvous()->Send(parsed_key, args, host_tensor, false));

        return std::move(done_event);
      };
}

// Provide RecvDeviceMemoryFunction for XLA host callbacks.  This callback