nnf_fractional_max_pool2d: Fractional_max_pool2d

Description Usage Arguments Details

View source: R/nnf-pooling.R

Description

Applies 2D fractional max pooling over an input signal composed of several input planes.

Usage

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nnf_fractional_max_pool2d(
  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) or a tuple (kH, kW)

output_size

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

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

optional random samples.

Details

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.


torch documentation built on Oct. 7, 2021, 9:22 a.m.