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>

        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

    DefaultValuedOptionalAttr<BoolAttr, "false">:$enable_large_batch_splitting
  );

  let results = (outs
    Res<Variadic<TF_Tensor>, [{The output tensors.}]>:$out_tensors
  );

  TF_DerivedOperandTypeListAttr Tcaptured = TF_DerivedOperandTypeListAttr<1>;
  TF_DerivedOperandTypeListAttr Tin = TF_DerivedOperandTypeListAttr<0>;