Hello! I am quite new to PyTorch and training DNN models in general. I’m working on audio separation and I would like to augment my dataset by cropping random overlapping segments of audio, adding noise, etc. What bothers me is how in general data augmentation works, meaning will I augment my data, save it to HDD and then load it, or is it done “per batch”, stored temporarily? I’m not sure if I have explained this properly. If the latter is the answer to my question, then is there anything similar (for audio) to augmentation for images in PyTorch (random crops, etc.)? Thanks in advance!