FractionalMaxPool3d
class torch.nn.FractionalMaxPool3d(kernel_size, output_size=None, output_ratio=None, return_indices=False, _random_samples=None)
Applies a 3D fractional max pooling over an input signal composed
   of several input planes.
Fractional MaxPooling is described in detail in the paper
   Fractional MaxPooling by Ben Graham
The max-pooling operation is applied in kT \times kH \times kW
   regions by a stochastic step size determined by the target output
   size. The number of output features is equal to the number of input
   planes.
Parameters:
      * kernel_size (Union[int, Tuple[int, int,
        int]]) -- the size of the window to take a max over.
        Can be a single number k (for a square kernel of k x k x k) or
        a tuple (kt x kh x kw)
  * **output_size** (*Union**[**int**, **Tuple**[**int**, **int**,
    **int**]**]*) -- the target output size of the image of the
