diff --git a/src/layers/basic.jl b/src/layers/basic.jl
index 005915bb..76704d0c 100644
--- a/src/layers/basic.jl
+++ b/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)
diff --git a/test/layers/basic.jl b/test/layers/basic.jl
index 3c5229f4..4deb545f 100644
--- a/test/layers/basic.jl
+++ b/test/layers/basic.jl
@@ -1,63 +1,75 @@
 using Test, Random
+import Flux: activations
 
 @testset "basic" begin
-    @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))
-        # numeric test should be put into testset of corresponding layer
+  @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))
+    # numeric test should be put into testset of corresponding layer
+  end
+
+  @testset "Dense" begin
+    @test  length(Dense(10, 5)(randn(10))) == 5
+    @test_throws DimensionMismatch Dense(10, 5)(randn(1))
+    @test_throws MethodError Dense(10, 5)(1) # avoid broadcasting
+    @test_throws MethodError Dense(10, 5).(randn(10)) # avoid broadcasting
+
+    @test Dense(10, 1, identity, initW = ones, initb = zeros)(ones(10,1)) == 10*ones(1, 1)
+    @test Dense(10, 1, identity, initW = ones, initb = zeros)(ones(10,2)) == 10*ones(1, 2)
+    @test Dense(10, 2, identity, initW = ones, initb = zeros)(ones(10,1)) == 10*ones(2, 1)
+    @test Dense(10, 2, identity, initW = ones, initb = zeros)([ones(10,1) 2*ones(10,1)]) == [10 20; 10 20]
+
+  end
+
+  @testset "Diagonal" begin
+    @test length(Flux.Diagonal(10)(randn(10))) == 10
+    @test length(Flux.Diagonal(10)(1)) == 10
+    @test length(Flux.Diagonal(10)(randn(1))) == 10
+    @test_throws DimensionMismatch Flux.Diagonal(10)(randn(2))
+
+    @test Flux.Diagonal(2)([1 2]) == [1 2; 1 2]
+    @test Flux.Diagonal(2)([1,2]) == [1,2]
+    @test Flux.Diagonal(2)([1 2; 3 4]) == [1 2; 3 4]
+  end
+
+  @testset "Maxout" begin
+    # Note that the normal common usage of Maxout is as per the docstring
+    # These are abnormal constructors used for testing purposes
+
+    @testset "Constructor" begin
+      mo = Maxout(() -> identity, 4)
+      input = rand(40)
+      @test mo(input) == input
     end
 
-    @testset "Dense" begin
-        @test  length(Dense(10, 5)(randn(10))) == 5
-        @test_throws DimensionMismatch Dense(10, 5)(randn(1))
-        @test_throws MethodError Dense(10, 5)(1) # avoid broadcasting
-        @test_throws MethodError Dense(10, 5).(randn(10)) # avoid broadcasting
-
-        @test Dense(10, 1, identity, initW = ones, initb = zeros)(ones(10,1)) == 10*ones(1, 1)
-        @test Dense(10, 1, identity, initW = ones, initb = zeros)(ones(10,2)) == 10*ones(1, 2)
-        @test Dense(10, 2, identity, initW = ones, initb = zeros)(ones(10,1)) == 10*ones(2, 1)
-        @test Dense(10, 2, identity, initW = ones, initb = zeros)([ones(10,1) 2*ones(10,1)]) == [10 20; 10 20]
-
+    @testset "simple alternatives" begin
+      mo = Maxout((x -> x, x -> 2x, x -> 0.5x))
+      input = rand(40)
+      @test mo(input) == 2*input
     end
 
-    @testset "Diagonal" begin
-        @test length(Flux.Diagonal(10)(randn(10))) == 10
-        @test length(Flux.Diagonal(10)(1)) == 10
-        @test length(Flux.Diagonal(10)(randn(1))) == 10
-        @test_throws DimensionMismatch Flux.Diagonal(10)(randn(2))
-
-        @test Flux.Diagonal(2)([1 2]) == [1 2; 1 2]
-        @test Flux.Diagonal(2)([1,2]) == [1,2]
-        @test Flux.Diagonal(2)([1 2; 3 4]) == [1 2; 3 4]
+    @testset "complex alternatives" begin
+      mo = Maxout((x -> [0.5; 0.1]*x, x -> [0.2; 0.7]*x))
+      input = [3.0 2.0]
+      target = [0.5, 0.7].*input
+      @test mo(input) == target
     end
 
-    @testset "Maxout" begin
-        # Note that the normal common usage of Maxout is as per the docstring
-        # These are abnormal constructors used for testing purposes
-
-        @testset "Constructor" begin
-            mo = Maxout(() -> identity, 4)
-            input = rand(40)
-            @test mo(input) == input
-        end
-
-        @testset "simple alternatives" begin
-            mo = Maxout((x -> x, x -> 2x, x -> 0.5x))
-            input = rand(40)
-            @test mo(input) == 2*input
-        end
-
-        @testset "complex alternatives" begin
-            mo = Maxout((x -> [0.5; 0.1]*x, x -> [0.2; 0.7]*x))
-            input = [3.0 2.0]
-            target = [0.5, 0.7].*input
-            @test mo(input) == target
-        end
-
-        @testset "params" begin
-            mo = Maxout(()->Dense(32, 64), 4)
-            ps = params(mo)
-            @test length(ps) == 8  #4 alts, each with weight and bias
-        end
+    @testset "params" begin
+      mo = Maxout(()->Dense(32, 64), 4)
+      ps = params(mo)
+      @test length(ps) == 8  #4 alts, each with weight and bias
     end
+  end
 end