I am new in Pytorch and although I am already able to work for example with FCN-GCN to segmentation problems, for example, I have some general questions regarding PyTorch. When I try to use a new network, I always struggle in the data processing phase, in particular when writing a Dataset object class to read my data, transform my data and convert it to Tensor type. I always have errors on the network, in particular with image or label shapes, etc… If it is not a pain, I really would kindly ask if someone could explain to me what it the best way of handling data for a general problem of classification or segmentation. For example, right now I am trying to develop a CNN for classification binary problem, and I am struggling with the labels ‘0’ and ‘1’, I always get shape and data type errors on my CNN. Not sure if could be also related with the criterion I am using: nn.CrossEntropyLoss().
I was using this tutorial: https://www.pluralsight.com/guides/image-classification-with-pytorch, but I am using my own Dataset.
Thank you in advance, and I understand if this is too confusing or difficult to answer