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

Max pooling layer, which replaces all pixels in a block of size window with one.

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, MeanPool, AdaptiveMaxPool, GlobalMaxPool.

Examples

			julia> xs = rand(Float32, 100, 100, 3, 50);  # batch of 50 RGB images

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

julia> m[1](xs) |> size
(100, 100, 7, 50)

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

julia> layer = MaxPool((5,), pad=2, stride=(3,))  # one-dimensional window
MaxPool((5,), pad=2, stride=3)

julia> layer(rand(Float32, 100, 7, 50)) |> size
(34, 7, 50)