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# torch.round

torch.round(input, *, decimals=0, out=None) → Tensor

  Rounds elements of `input` to the nearest integer.

  For integer inputs, follows the array-api convention of returning a copy of the input tensor. The return type of output is same as that of input’s dtype.

  Note

  This function implements the “round half to even” to break ties when a number is equidistant from two integers (e.g. round(2.5) is 2).

  When the :attr:`decimals` argument is specified the algorithm used is similar to NumPy’s around. This algorithm is fast but inexact and it can easily overflow for low precision dtypes. Eg. round(tensor([10000], dtype=torch.float16), decimals=3) is inf.

  See also

  `torch.ceil()`, which rounds up. `torch.floor()`, which rounds down. `torch.trunc()`, which rounds towards zero.

  Parameters:

    - input (Tensor) – the input tensor.

    - decimals (int) – Number of decimal places to round to (default: 0). If decimals is negative, it specifies the number of positions to the left of the decimal point.

  Keyword Arguments:

    out (Tensor, optional) – the output tensor.

  Example:

      >>> torch.round(torch.tensor((4.7, -2.3, 9.1, -7.7)))
      tensor([ 5.,  -2.,  9., -8.])

      >>> # Values equidistant from two integers are rounded towards the
      >>> #   the nearest even value (zero is treated as even)
      >>> torch.round(torch.tensor([-0.5, 0.5, 1.5, 2.5]))
      tensor([-0., 0., 2., 2.])

      >>> # A positive decimals argument rounds to the to that decimal place
      >>> torch.round(torch.tensor([0.1234567]), decimals=3)
      tensor([0.1230])

      >>> # A negative decimals argument rounds to the left of the decimal
      >>> torch.round(torch.tensor([1200.1234567]), decimals=-3)
      tensor([1000.])

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