mtthtlt

4 ms·

1. 1.▲
   by mtthtlt 5y ago

   I agree, especially when it is free accuracy wise :)
2. 2.▲
   by mtthtlt 5y ago

   That is so cool ! May I ask at which resolution you had those results ? We managed to get up to 10x for very low resolutions (160) for a resnet101 but it usually plateaus for high resolutions (above 896x896) at a 1.7~1.9 speed-up. Although
3. 3.▲
   by mtthtlt 5y ago

   I think using TRTorch[1] can be quick way to generate both easy to use and fast inference models from PyTorch. It compiles your model, using TensorRT, Ahead of Time and enables you to use the compiled model through torch.jit.load("your
4. 4.▲
   by mtthtlt 5y ago

   Matthieu here, ML engineer at PhotoRoom. We use a custom UNet model. We work with PyTorch for research and use Tensor RT and CoreML to deploy models.