I've recently stumbled across the torch_tensorrt.compile method for PyTorch models, but after a few hours of testing, I noticed that I could not run inference with these methods because the IFNet inference, namely when the block method is called, creates new shapes for the inputs, so passing the inputs parameter into torch_tensorrt.compile always returns an error. I was wondering if you had any idea how to implement this? I tried vsrife and vsgan-tensorrt-docker methods, but I think they have different structures from this repository. Any guidance would be appreciated. Thank you~
Update, about a week ago, through my research, I noticed that some models may not be compatible or May not work right out of the box with this request. Closing this.
Hello,
I've recently stumbled across the
torch_tensorrt.compile
method for PyTorch models, but after a few hours of testing, I noticed that I could not run inference with these methods because theIFNet
inference, namely when theblock
method is called, creates new shapes for the inputs, so passing theinputs
parameter intotorch_tensorrt.compile
always returns an error. I was wondering if you had any idea how to implement this? I triedvsrife
andvsgan-tensorrt-docker
methods, but I think they have different structures from this repository. Any guidance would be appreciated. Thank you~