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# torch.fmod

torch.fmod(input, other, *, out=None) → Tensor

  Applies C++’s std::fmod entrywise. The result has the same sign as the dividend `input` and its absolute value is less than that of `other`.

  This function may be defined in terms of `torch.div()` as

      torch.fmod(a, b) == a - a.div(b, rounding_mode="trunc") * b

  Supports broadcasting to a common shape, type promotion, and integer and float inputs.

  Note

  When the divisor is zero, returns `NaN` for floating point dtypes on both CPU and GPU; raises `RuntimeError` for integer division by zero on CPU; Integer division by zero on GPU may return any value.

  Note

  Complex inputs are not supported. In some cases, it is not mathematically possible to satisfy the definition of a modulo operation with complex numbers.

  See also

  `torch.remainder()` which implements Python’s modulus operator. This one is defined using division rounding down the result.

  Parameters:

    - input (Tensor) – the dividend

    - other (Tensor or Scalar) – the divisor

  Keyword Arguments:

    out (Tensor, optional) – the output tensor.

  Example:

      >>> torch.fmod(torch.tensor([-3., -2, -1, 1, 2, 3]), 2)
      tensor([-1., -0., -1.,  1.,  0.,  1.])
      >>> torch.fmod(torch.tensor([1, 2, 3, 4, 5]), -1.5)
      tensor([1.0000, 0.5000, 0.0000, 1.0000, 0.5000])

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