
Fractional MaxPooling is described in detail in the paper Fractional MaxPooling by Ben Graham
nn_fractional_max_pool3d(
kernel_size,
output_size = NULL,
output_ratio = NULL,
return_indices = FALSE
)
the size of the window to take a max over.
Can be a single number k (for a square kernel of k x k x k) or a tuple (kt x kh x kw)
the target output size of the image of the form oT x oH x oW
.
Can be a tuple (oT, oH, oW)
or a single number oH for a square image oH x oH x 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.
Useful to pass to nn_max_unpool3d()
. Default: FALSE
The max-pooling operation is applied in
if (torch_is_installed()) {
# pool of cubic window of size=3, and target output size 13x12x11
m <- nn_fractional_max_pool3d(3, output_size = c(13, 12, 11))
# pool of cubic window and target output size being half of input size
m <- nn_fractional_max_pool3d(3, output_ratio = c(0.5, 0.5, 0.5))
input <- torch_randn(20, 16, 50, 32, 16)
output <- m(input)
}
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