some more tests

test/test_cells.jl

@@ -11,7 +11,7 @@ double_cells = [RANCell, NASCell, PeepholeLSTMCell]
 #cells with a little more complexity to them
 different_cells = [SCRNCell, RHNCell]
 
-@testset "Signle return cell: cell = $cell" for cell in single_cells
+@testset "Single return cell: cell = $cell" for cell in single_cells
     rnncell = cell(3 => 5)
     @test length(Flux.trainables(rnncell)) == 3
 
@@ -37,4 +37,33 @@ end
 
     inp = rand(Float32, 3)
     @test rnncell(inp) == rnncell(inp, (zeros(Float32, 5), zeros(Float32, 5)))
+end
+
+@testset "SCRNCell" begin
+    rnncell = SCRNCell(3 => 5)
+    @test length(Flux.trainables(rnncell)) == 4
+
+    inp = rand(Float32, 3)
+    @test rnncell(inp) == rnncell(inp, (zeros(Float32, 5), zeros(Float32, 5)))
+
+    rnncell = SCRNCell(3 => 5; bias=false)
+    @test length(Flux.trainables(rnncell)) == 3
+
+    inp = rand(Float32, 3)
+    @test rnncell(inp) == rnncell(inp, (zeros(Float32, 5), zeros(Float32, 5)))
+end
+
+@testset "RHNCell" begin
+    rnncell = RHNCell(3 => 5)
+    @test length(Flux.trainables(rnncell)) == 6
+
+    inp = rand(Float32, 3)
+    @test rnncell(inp) == rnncell(inp, zeros(Float32, 5))
+
+    ##TODO rhncell bias is bugged atm
+    #rnncell = RHNCell(3 => 5; bias=false)
+    #@test length(Flux.trainables(rnncell)) == 3
+
+    #inp = rand(Float32, 3)
+    #@test rnncell(inp) == rnncell(inp, zeros(Float32, 5))
 end