xnew_from_cat = torch.cat((x, x, x), 1) print(f'{xnew_from_cat.size()}') print() # stack serves the same role as append in lists. i.e. it doesn't change the original # vector space but instead adds a new index to the new tensor, so you retain the ability # get the original tensor you added to the list by indexing in the new dimension
cat is valid only for atomic types (logical, integer, real, complex, character) and names. It means you cannot call cat on a non-empty list or any type of object. In practice it simply converts arguments to characters and concatenates so you can think of something like as.character() %>% paste(). print is a generic function so you can define a specific implementation for a certain S3 class.
cat is an identity pipe. It only streams its input to its output. If the second program in the chain can take its input from the same argument you pass to cat (or from the standard input, if you pass no argument), then cat is absolutely useless and only results in an additional process being forked and an additional pipe being created.