use inner constructor for Bilinear, more like Dense

src/layers/basic.jl

@@ -287,7 +287,7 @@ end
     Bilinear(W::AbstractArray, [bias, σ])
 
 Creates a Bilinear layer, which operates on two inputs at the same time.
-It its output, given vectors `x`, `y` is another vector `z` with,
+Its output, given vectors `x` & `y`, is another vector `z` with,
 for all `i ∈ 1:out`:
 
     z[i] = σ(x' * W[i,:,:] * y + bias[i])
@@ -325,21 +325,22 @@ julia> sc(x) |> size
 (3, 32)
 ```
 """
-struct Bilinear{A,B,S}
+struct Bilinear{F,A,B}
   weight::A
   bias::B
-  σ::S
+  σ::F
+  function Bilinear(W::A, bias = true, σ::F = identity) where {A<:AbstractArray, F}
+    ndims(A) == 3 || throw(ArgumentError("expected a 3-array of weights"))
+    b = create_bias(W, bias, size(W,1))
+    new{F,A,typeof(b)}(W, b, σ)
+  end
 end
 
 @functor Bilinear
 
-Bilinear(weight::AbstractArray, bias = true) = Bilinear(weight, create_bias(weight, bias, size(weight,1)), identity)
-
 function Bilinear(in1::Integer, in2::Integer, out::Integer, σ = identity;
-  init = glorot_uniform, bias = true)
-  W = init(out, in1, in2)
-  b = create_bias(W, bias, out)
-  return Bilinear(W, b, σ)
+                  init = glorot_uniform, bias = true)
+  Bilinear(init(out, in1, in2), bias, σ)
 end
 
 function (a::Bilinear)(x::AbstractMatrix, y::AbstractMatrix)

test/layers/basic.jl

@@ -161,12 +161,17 @@ import Flux: activations
       b2 = Flux.Bilinear(randn(3,4,5), false)
       @test b2.bias == Flux.Zeros()
 
-      b3 = Flux.Bilinear(randn(3,4,5), true, tanh)
+      b3 = Flux.Bilinear(randn(Float16, 3,4,5), true, tanh)
       @test b3.σ == tanh
+      @test b2.bias isa Vector{Float16}
       @test size(b3(rand(4), rand(5))) == (3,)
 
       b4 = Flux.Bilinear(3,3,7; bias=1:7, init=Flux.zeros)
       @test  b4.bias isa Vector{Float32}
+
+      @test_throws ArgumentError Flux.Bilinear(rand(3)) # expects a 3-array
+      @test_throws ArgumentError Flux.Bilinear(rand(3,4), false, tanh)
+      @test_throws DimensionMismatch Flux.Bilinear(rand(3,4,5), rand(6), tanh) # wrong length bias
     end
   end