introduction to pytorch in [ ]torch norm( , out[ ]tensor( in [ ]torch norm( , out[ ]tensor( in [ ]torch norm( ,float('inf')out[ ]tensor( the renorm function allows you to normalize vector by dividing it by the norm listing - demonstrates normalizing operation on tensor listing - normalizing tensor in [ ] torch floattensor([[ , , , ]]in [ ] out[ ]tensor([[ ]]in [ ]torch renorm(adim= = maxnorm= out[ ]tensor([[ ]] ummary this offered brief introduction to pytorch with focus on tensors and tensor operations several of the tensor operations discussed in this will come handy in the next few you should spend quality time with tensors to improve you pytorch skills this will be immensely valuable for customizing deep learning networks and debugging the flow easily in the advent of an unaccounted error common tensor operations include view (to reshape tensors)size (to print the shape/size of the tensor)item (to extract data from single value tensor)squeeze (to reshape tensors)and cat (to concatenate tensorsmoreoverpytorch has two separate packages (torchvision and torchtext