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# 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]`.

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