basic sketch

README.md

@@ -1,3 +1,3 @@
 # Flux
 
-[![Build Status](https://travis-ci.org/one-more-minute/Flux.jl.svg?branch=master)](https://travis-ci.org/one-more-minute/Flux.jl)
+Flux is an experimental machine perception / ANN library for Julia.

examples/sketch.jl

@@ -0,0 +1,57 @@
+# Simple Perceptron Layer
+
+@flux type Simple
+  weight
+  bias
+  feed(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 feed(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

src/Flux.jl

@@ -2,4 +2,9 @@ module Flux
 
 # Zero Flux Given
 
+abstract Capacitor
+
+macro flux(x)
+end
+
 end # module