Mastering Torch.arange() For Efficient Tensor Generation
arange() creates a 1D tensor of zero or integers or floating-point numbers between start and end-1. With torch, it has optional arguments: start, end, step, dtype, device, requires_grad, and out.
Buy Me a Coffee☕ *Memos: My post explains linspace(). My post explains logspace(). arange() can create the 1D tensor of zero or integers or floating-point numbers between start and end-1(start<=x<=end-1) as shown below: *Memos: arange() can be used with torch but not with a tensor. The 1st argument with torch is start(Optional-Default:0-Type:int, float, complex or bool): *Memos It must be lower than or equal to end. The 0D tensor of int, float, complex or bool also works. The 2nd argument with torch is end(Required-Type:int, float, complex or bool): *Memos: It must be greater than or...