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# torch.mode

torch.mode(input, dim=- 1, keepdim=False, *, out=None)

  Returns a namedtuple `(values, indices)` where `values` is the mode value of each row of the `input` tensor in the given dimension `dim`, i.e. a value which appears most often in that row, and `indices` is the index location of each mode value found.

  By default, `dim` is the last dimension of the `input` tensor.

  If `keepdim` is `True`, the output tensors are of the same size as `input` except in the dimension `dim` where they are of size 1. Otherwise, `dim` is squeezed (see `torch.squeeze()`), resulting in the output tensors having 1 fewer dimension than `input`.

  Note

  This function is not defined for `torch.cuda.Tensor` yet.

  Parameters:

    - input (Tensor) – the input tensor.

    - dim (int) – the dimension to reduce.

    - keepdim (bool) – whether the output tensor has `dim` retained or not.

  Keyword Arguments:

    out (tuple, optional) – the result tuple of two output tensors (values, indices)

  Example:

      >>> a = torch.randint(10, (5,))
      >>> a
      tensor([6, 5, 1, 0, 2])
      >>> b = a + (torch.randn(50, 1) * 5).long()
      >>> torch.mode(b, 0)
      torch.return_types.mode(values=tensor([6, 5, 1, 0, 2]), indices=tensor([2, 2, 2, 2, 2]))

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