torch.nn.functional.fractional_max_pool2d
torch.nn.functional.fractional_max_pool2d(args, *kwargs)
Applies 2D 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 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)
        or a tuple (kH, kW)
  * **output_size** -- the target output size of the image of the
    form oH \times oW. Can be a tuple *(oH, oW)* or a single
    number oH for a square image oH \times oH

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