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# torch.nan_to_num

torch.nan_to_num(input, nan=0.0, posinf=None, neginf=None, *, out=None) → Tensor

  Replaces `NaN`, positive infinity, and negative infinity values in `input` with the values specified by `nan`, `posinf`, and `neginf`, respectively. By default, `NaN`s are replaced with zero, positive infinity is replaced with the greatest finite value representable by `input`’s dtype, and negative infinity is replaced with the least finite value representable by `input`’s dtype.

  Parameters:

    - input (Tensor) – the input tensor.

    - nan (Number, optional) – the value to replace `NaN`s with. Default is zero.

    - posinf (Number, optional) – if a Number, the value to replace positive infinity values with. If None, positive infinity values are replaced with the greatest finite value representable by `input`’s dtype. Default is None.

    - neginf (Number, optional) – if a Number, the value to replace negative infinity values with. If None, negative infinity values are replaced with the lowest finite value representable by `input`’s dtype. Default is None.

  Keyword Arguments:

    out (Tensor, optional) – the output tensor.

  Example:

      >>> x = torch.tensor([float('nan'), float('inf'), -float('inf'), 3.14])
      >>> torch.nan_to_num(x)
      tensor([ 0.0000e+00,  3.4028e+38, -3.4028e+38,  3.1400e+00])
      >>> torch.nan_to_num(x, nan=2.0)
      tensor([ 2.0000e+00,  3.4028e+38, -3.4028e+38,  3.1400e+00])
      >>> torch.nan_to_num(x, nan=2.0, posinf=1.0)
      tensor([ 2.0000e+00,  1.0000e+00, -3.4028e+38,  3.1400e+00])

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