Understanding arange, unsqueeze, repeat, stack methods in Pytorch
Understanding arange, unsqueeze, repeat, stack methods in Pytorch torch.arange(start=0, end, step=1) return 1-D tensor of size (end-start)/step which value begin from start and each value take with common differences step.
torch.unsqueeze(input, dim) return a new tensor with a dimension of size one insterted at specified position; A dim value within the range [-input.dim() - 1, input.dim() + 1) can be used.
tensor.repeat(size*) return a tensor; the new shape of tensor is that original shape multiplied by arguments correspondingly, if the number of paramter don’t match the original shape, then last dimension of new shape = the last dimension of original shape * last paramter;
