diff --git a/src/layers/normalise.jl b/src/layers/normalise.jl
index 1783d3ef..821a9d99 100644
--- a/src/layers/normalise.jl
+++ b/src/layers/normalise.jl
@@ -43,6 +43,37 @@ end
 
 _testmode!(a::Dropout, test) = (a.active = !test)
 
+"""
+    AlphaDropout(p)
+A dropout layer. It is used in Self-Normalizing Neural Networks. 
+(https://papers.nips.cc/paper/6698-self-normalizing-neural-networks.pdf)
+The AlphaDropout layer ensures that mean and variance of activations remains the same as before.
+"""
+mutable struct AlphaDropout{F}
+	p::F
+  active::Bool
+end
+
+function AlphaDropout(p)
+  @assert 0 ≤ p ≤ 1
+  AlphaDropout{typeof(p)}(p,true)
+end
+
+function (a::AlphaDropout)(x)
+  a.active || return x
+  α = -1.75813631
+  noise = randn(Float64, size(x.data))
+  y = collect(x)
+  y .= y .* (noise .> (1 - a.p)) + α .* (noise .<= (1 - a.p))
+  A = (a.p + a.p * (1 - a.p) * α ^ 2)^0.5
+  B = -A * α * (1 - a.p)
+  y .= A .* y .+ B
+  x1 = param(y)
+  return x1
+end
+
+_testmode!(a::AlphaDropout, test) = (a.active = !test)
+
 """
     LayerNorm(h::Integer)