Merge pull request #710 from johnnychen94/master

naive implementation of activations

src/layers/basic.jl

@@ -40,7 +40,24 @@ function Base.show(io::IO, c::Chain)
   print(io, ")")
 end
 
-activations(c::Chain, x) = accumulate((x, m) -> m(x), c.layers, init = x)
+
+# This is a temporary and naive implementation
+# it might be replaced in the future for better performance
+# see issue https://github.com/FluxML/Flux.jl/issues/702
+# Johnny Chen -- @johnnychen94
+"""
+    activations(c::Chain, input)
+Calculate the forward results of each layers in Chain `c` with `input` as model input.
+"""
+function activations(c::Chain, input)
+  rst = []
+  for l in c
+    x = get(rst, length(rst), input)
+    push!(rst, l(x))
+  end
+  return rst
+end
+
 
 """
     Dense(in::Integer, out::Integer, σ = identity)

test/layers/basic.jl

@@ -1,6 +1,18 @@
 using Test, Random
+import Flux: activations
 
 @testset "basic" begin
+  @testset "helpers" begin
+    @testset "activations" begin
+      dummy_model = Chain(Dense(10,5,σ),Dense(5,2),softmax)
+      x = rand(10)
+      @test activations(Chain(), x) == []
+      @test activations(dummy_model, x)[1] == dummy_model[1](x)
+      @test activations(dummy_model, x)[2] == x |> dummy_model[1] |> dummy_model[2]
+      @test activations(Chain(identity, x->:foo), x)[2] == :foo # results include `Any` type
+    end
+  end
+
   @testset "Chain" begin
     @test_nowarn Chain(Dense(10, 5, σ), Dense(5, 2))(randn(10))
     @test_throws DimensionMismatch Chain(Dense(10, 5, σ),Dense(2, 1))(randn(10))