fix dropout
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094b38ac03
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@ -2,6 +2,19 @@ istraining() = false
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@adjoint istraining() = true, _ -> nothing
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_dropout_shape(s, ::Colon) = size(s)
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_dropout_shape(s, dims) = tuple((i ∉ dims ? 1 : si for (i, si) ∈ enumerate(size(s)))...)
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_dropout_kernel(y::T, p, q) where {T} = y > p ? T(1 / q) : T(0)
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dropout(x, p; dims = :) = x
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@adjoint function dropout(x, p; dims = :)
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y = rand!(similar(x, _dropout_shape(x, dims)))
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y .= _dropout_kernel.(y, p, 1 - p)
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return x .* y, Δ -> (Δ .* y, nothing)
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end
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"""
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Dropout(p, dims = :)
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@ -12,33 +25,17 @@ A Dropout layer. For each input, either sets that input to `0` (with probability
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Does nothing to the input once in [`testmode!`](@ref).
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"""
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mutable struct Dropout{F}
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mutable struct Dropout{F,D}
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p::F
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dims::Union{Colon, Int, NTuple{N, Int} where N}
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dims::D
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end
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function Dropout(p; dims = :)
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@assert 0 ≤ p ≤ 1
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Dropout{typeof(p)}(p, dims)
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Dropout{typeof(p),typeof(dims)}(p, dims)
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end
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_dropout_shape(s, ::Colon) = size(s)
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_dropout_shape(s, dims) = tuple((i ∉ dims ? 1 : si for (i, si) ∈ enumerate(size(s)))...)
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_dropout_kernel(y::T, p, q) where {T} = y > p ? T(1 / q) : T(0)
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function dropout(x, p; dims = :)
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istraining() || return x
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y = similar(x, _dropout_shape(x, dims))
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rand!(y)
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y .= _dropout_kernel.(y, p, 1 - p)
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return x .* y
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end
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function (a::Dropout)(x)
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istraining() || return x
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return dropout(x, a.p; dims = a.dims)
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end
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(a::Dropout)(x) = dropout(x, a.p; dims = a.dims)
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"""
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AlphaDropout(p)
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