MeanPool(window::NTuple; pad=0, stride=window)

Mean pooling layer, averaging all pixels in a block of size window.

Expects as input an array with ndims(x) == N+2, i.e. channel and batch dimensions, after the N feature dimensions, where N = length(window).

By default the window size is also the stride in each dimension. The keyword pad accepts the same options as for the Conv layer, including SamePad().

See also Conv, MaxPool, AdaptiveMeanPool.

Examples

			julia> xs = rand(Float32, 100, 100, 3, 50);

julia> m = Chain(Conv((5,5), 3 => 7), MeanPool((5,5), pad=SamePad()))
Chain(
  Conv((5, 5), 3 => 7),                 # 532 parameters
  MeanPool((5, 5), pad=2),
)

julia> m[1](xs) |> size
(96, 96, 7, 50)

julia> m(xs) |> size
(20, 20, 7, 50)