brator and it will work as well.
From here not much changes in terms of how to execution works. You are still able to fully use LibTorch as the sole interface for inference. Data should remain
in FP32 precision when it’s passed into
        <cite>
         trt_mod.forward
        </cite>
        . There exists an example application in the Torch-TensorRT demo that takes you from training a VGG16 network on
CIFAR10 to deploying in INT8 with Torch-TensorRT here:
        <a class="reference external" href="h