Applies 3D fractional max pooling over an input signal composed of several input planes.
Usage
nnf_fractional_max_pool3d(
input,
kernel_size,
output_size = NULL,
output_ratio = NULL,
return_indices = FALSE,
random_samples = NULL
)Arguments
- input
the input tensor
- kernel_size
the size of the window to take a max over. Can be a single number \(k\) (for a square kernel of \(k * k * k\)) or a tuple
(kT, kH, kW)- output_size
the target output size of the form \(oT * oH * oW\). Can be a tuple
(oT, oH, oW)or a single number \(oH\) for a cubic output \(oH * oH * oH\)- output_ratio
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)
- return_indices
if
True, will return the indices along with the outputs.- random_samples
undocumented argument.
Details
Fractional MaxPooling is described in detail in the paper Fractional MaxPooling_ by Ben Graham
The max-pooling operation is applied in \(kT * kH * kW\) 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.