// Assign the internal ShapedBuffer to new memory for the given dtype and
  // shape. If a ShapedBuffer exists already (has_shaped_buffer() == true), it
  // is replaced and the managed memory deallocated.
  Status AllocateShapedBuffer(DataType dtype, const xla::Shape& on_device_shape,
                              xla::LocalClient* client, int device_ordinal);

  // Some Tensors can have complex on-device shapes, including tuple shapes. To

  } else {
    return se::DeviceMemoryBase(const_cast<char*>(tensor.tensor_data().data()),
                                tensor.tensor_data().size());
  }
}

Status XlaTensor::AllocateShapedBuffer(DataType dtype,
                                       const xla::Shape& on_device_shape,
                                       xla::LocalClient* client,
                                       int device_ordinal) {

    // The device tensor should always be fresh.
    TF_RET_CHECK(!xla_tensor->has_shaped_buffer());

    TF_RETURN_IF_ERROR(
        xla_tensor->AllocateShapedBuffer(device_tensor->dtype(), shape, client_,
                                         stream_->parent()->device_ordinal()));

    // The cpu_tensor and literal that we created here hold the data of host

                            input->shape(), input->dtype(),
                            /*use_fast_memory=*/false, layout_preference));
    TF_RETURN_IF_ERROR(xla_output->AllocateShapedBuffer(
        input->dtype(), shape, dst_xla_context->client(), dst_device_ordinal));

    VLOG(2) << "TpuDeviceToDeviceCopy: src: "
            << src_compute_stream->parent()->device_ordinal() << ", "