Applies 2D fractional max pooling over an input signal composed of several input planes.
nnf_fractional_max_pool2d(
input,
kernel_size,
output_size = NULL,
output_ratio = NULL,
return_indices = FALSE,
random_samples = NULL
)the input tensor
the size of the window to take a max over. Can be a
single number \(k\) (for a square kernel of \(k * k\)) or
a tuple (kH, kW)
the target output size of the image of the form \(oH * oW\).
Can be a tuple (oH, oW) or a single number \(oH\) for a square image \(oH * oH\)
If one wants to have an output size as a ratio of the input size, this option can be given. This has to be a number or tuple in the range (0, 1)
if True, will return the indices along with the outputs.
optional random samples.
Fractional MaxPooling is described in detail in the paper Fractional MaxPooling_ by Ben Graham
The max-pooling operation is applied in \(kH * kW\) 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.