torch.nn.functional.fractional_max_pool3d
torch.nn.functional.fractional_max_pool3d(args, *kwargs)
Applies 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 -- the size of the window to take a max over.
        Can be a single number k (for a square kernel of k \times k
        \times k) or a tuple (kT, kH, kW)
  * **output_size** -- the target output size of the form oT
    \times oH \times oW. Can be a tuple *(oT, oH, oW)* or a single
    number oH for a cubic output oH \times oH \times oH

  * **output_ratio** -- If one wants to have an output size as a
