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# torch.any

torch.any(input) → Tensor

  Tests if any element in `input` evaluates to True.

  Note

  This function matches the behaviour of NumPy in returning output of dtype bool for all supported dtypes except uint8. For uint8 the dtype of output is uint8 itself.

  Example:

      >>> a = torch.rand(1, 2).bool()
      >>> a
      tensor([[False, True]], dtype=torch.bool)
      >>> torch.any(a)
      tensor(True, dtype=torch.bool)
      >>> a = torch.arange(0, 3)
      >>> a
      tensor([0, 1, 2])
      >>> torch.any(a)
      tensor(True)

  torch.any(input, dim, keepdim=False, *, out=None) → Tensor

  For each row of `input` in the given dimension `dim`, returns True if any element in the row evaluate to True and False otherwise.

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

  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 (Tensor, optional) – the output tensor.

  Example:

      >>> a = torch.randn(4, 2) < 0
      >>> a
      tensor([[ True,  True],
              [False,  True],
              [ True,  True],
              [False, False]])
      >>> torch.any(a, 1)
      tensor([ True,  True,  True, False])
      >>> torch.any(a, 0)
      tensor([True, True])

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