torch.Tensor.random_
Tensor.random_(from=0, to=None, *, generator=None) -> Tensor
Fills "self" tensor with numbers sampled from the discrete uniform
   distribution over "[from, to - 1]". If not specified, the values
   are usually only bounded by "self" tensor's data type. However, for
   floating point types, if unspecified, range will be "[0,
   2^mantissa]" to ensure that every value is representable. For
   example, torch.tensor(1, dtype=torch.double).random_() will be
   uniform in "[0, 2^53]".