this served its purpose

examples/sketch.jl

@@ -1,57 +0,0 @@
-# Simple Perceptron Layer
-
-@flux type Simple
-  weight
-  bias
-  x -> σ( weight*x + bias )
-end
-
-Simple(nx::Integer, ny::Integer; init = randn) =
-  Simple(init(nx, ny), init(ny))
-
-# Time Delay Node
-
-type Delay
-  n::Int
-  next
-end
-
-# feed(l::Delay, x) = ...
-
-# back(l::Delay, y) = ...
-
-# Simple Recurrent
-
-@flux type RecurrentU
-  Wxh; Whh; Bh
-  Wxy; Why; By
-
-  function feed(x, hidden)
-    hidden′ = σ( Wxh*x + Whh*hidden + Bh )
-    y = σ( Wxy*x + Why*hidden′ + By )
-    y, hidden′
-  end
-end
-
-Recurrent(nx, ny, nh; init = randn) =
-  Recurrent(init(nx, nh), init(nh, nh), init(nh),
-            init(nx, ny), init(nh, ny), init(ny))
-
-@flux type Looped{T}
-  delay::Delay
-  layer::T
-
-  function (x)
-    y, hidden = layer(x, delay(hidden))
-    return y
-  end
-end
-
-type Recurrent
-  layer::Looped{RecurrentU}
-end
-
-Recurrent(nx, ny, nh; init = randn, delay = 10) =
-  Looped(Delay(delay, init(nh)), RecurrentU(nx, ny, nh))
-
-@forward Recurrent.layer feed