rhn fixes

src/rhn_cell.jl

@@ -2,7 +2,7 @@
 #https://github.com/jzilly/RecurrentHighwayNetworks/blob/master/rhn.py#L138C1-L180C60
 
 struct RHNCellUnit{I,V}
-    weight::I
+    weights::I
     bias::V
 end
 
@@ -15,18 +15,22 @@ Flux.@layer RHNCellUnit
 """
 function RHNCellUnit((input_size, hidden_size)::Pair;
     init_kernel = glorot_uniform,
-    bias = true)
+    bias::Bool = true)
     weight = init_kernel(3 * hidden_size, input_size)
     b = create_bias(weight, bias, size(weight, 1))
     return RHNCellUnit(weight, b)
 end
 
+function initialstates(rhn::RHNCellUnit)
+    return zeros_like(rhn.weights, size(rhn.weights, 1) ÷ 3)
+end
+
 function (rhn::RHNCellUnit)(inp::AbstractVecOrMat)
-    state = zeros_like(inp, size(rhn.weight, 2))
+    state = initialstates(rhn)
     return rhn(inp, state)
 end
 
-function (rhn::RHNCellUnit)(inp::AbstractVecOrMat, state)
+function (rhn::RHNCellUnit)(inp::AbstractVecOrMat, state::AbstractVecOrMat)
     _size_check(rhn, inp, 1 => size(rhn.weight, 2))
     weight, bias = rhn.weight, rhn.bias
 
@@ -81,7 +85,7 @@ c_{\ell}^{[t]} &= \sigma(W_c x^{[t]}\mathbb{I}_{\ell = 1} + U_{c_{\ell}} s_{\ell
     rnncell(inp, [state])
 
 """
-function RHNCell((input_size, hidden_size), depth::Int = 3;
+function RHNCell((input_size, hidden_size), depth::Integer = 3;
     couple_carry::Bool = true, #sec 5, setup
     cell_kwargs...)
 
@@ -98,13 +102,16 @@ function RHNCell((input_size, hidden_size), depth::Int = 3;
     return RHNCell(Chain(layers), couple_carry)
 end
 
+function initialstates(rhn::RHNCell)
+    return initialstates(first(rhn.layers))
+end
 
-function (rhn::RHNCell)(inp, state=nothing)
+function (rhn::RHNCell)(inp::AbstractArray)
+    state = initialstates(rhn)
+    return rhn(inp, state)
+end
 
-    #not ideal
-    if state == nothing
-        state = zeros_like(inp, size(rhn.layers.layers[2].weight, 2))
-    end
+function (rhn::RHNCell)(inp::AbstractArray, state::AbstractVecOrMat)
 
     current_state = state
 
@@ -141,7 +148,7 @@ end
 Flux.@layer :noexpand RHN
 
 @doc raw"""
-    RHN((input_size => hidden_size)::Pair depth=3; kwargs...)
+    RHN((input_size => hidden_size) depth=3; kwargs...)
 
 [Recurrent highway network](https://arxiv.org/pdf/1607.03474).
 See [`RHNCellUnit`](@ref) for a the unit component of this layer.
@@ -166,17 +173,21 @@ c_{\ell}^{[t]} &= \sigma(W_c x^{[t]}\mathbb{I}_{\ell = 1} + U_{c_{\ell}} s_{\ell
 \end{aligned}
 ```
 """
-function RHN((input_size, hidden_size)::Pair, depth=3; kwargs...)
+function RHN((input_size, hidden_size)::Pair, depth::Integer=3; kwargs...)
     cell = RHNCell(input_size => hidden_size, depth; kwargs...)
     return RHN(cell)
 end
+
+function initialstates(rhn::RHN)
+    return initialstates(rhn.cell)
+end
 
-function (rhn::RHN)(inp)
-    state = zeros_like(inp, size(rhn.cell.layers[2].weights, 2))
+function (rhn::RHN)(inp::AbstractArray)
+    state = initialstates(rhn)
     return rhn(inp, state)
 end
 
-function (rhn::RHN)(inp, state)
+function (rhn::RHN)(inp::AbstractArray, state::AbstractVecOrMat)
     @assert ndims(inp) == 2 || ndims(inp) == 3
     new_state = []
     for inp_t in eachslice(inp, dims=2)