Merge pull request #95 from JuliaGNI/convert_tuple_functions_to_named…

…_tuple_functions

Internally now only working with `NamedTuples`, not with `Tuples` when dealing with `q` and `p`.

src/kernels/assign_q_and_p.jl

@@ -45,7 +45,7 @@ function assign_q_and_p(x::AbstractVector, N::Int)
     p_kernel! = assign_second_half!(backend)
     q_kernel!(q, x, ndrange=size(q))
     p_kernel!(p, x, N, ndrange=size(p))
-    (q, p)
+    (q=q, p=p)
 end
 
 function assign_q_and_p(x::AbstractMatrix, N::Int)
@@ -56,7 +56,7 @@ function assign_q_and_p(x::AbstractMatrix, N::Int)
     p_kernel! = assign_second_half!(backend)
     q_kernel!(q, x, ndrange=size(q))
     p_kernel!(p, x, N, ndrange=size(p))
-    (q, p)
+    (q=q, p=p)
 end
 
 function assign_q_and_p(x::AbstractArray{T, 3}, N::Int) where T
@@ -67,5 +67,5 @@ function assign_q_and_p(x::AbstractArray{T, 3}, N::Int) where T
     p_kernel! = assign_second_half!(backend)
     q_kernel!(q, x, ndrange=size(q))
     p_kernel!(p, x, N, ndrange=size(p))
-    (q, p)
+    (q=q, p=p)
 end

src/kernels/kernel_ad_routines/assign_q_and_p.jl

@@ -3,11 +3,11 @@ This implements the custom pullback for assign_q_and_p
 """
 
 function ChainRulesCore.rrule(::typeof(assign_q_and_p), x::AbstractArray, N::Integer)
-    q, p = assign_q_and_p(x, N)
+    qp = assign_q_and_p(x, N)
     function assign_q_and_p_pullback(qp_diff)
         f̄ = NoTangent()
         concat = @thunk vcat(qp_diff...)
         return f̄, concat, NoTangent()
     end
-    return (q, p), assign_q_and_p_pullback
+    return qp, assign_q_and_p_pullback
 end

src/layers/psd_like_layer.jl

@@ -29,18 +29,10 @@ function initialparameters(backend::KernelAbstractions.Backend, T::Type, ::PSDLa
     (weight =  N > M ? rand(backend, rng, StiefelManifold{T}, N÷2, M÷2) : rand(backend, rng, StiefelManifold{T}, M÷2, N÷2), )
 end
 
-function (::PSDLayer{M, N})(x::AbstractVecOrMat, ps::NamedTuple) where {M, N}
+function (::PSDLayer{M, N})(x::AbstractArray, ps::NamedTuple) where {M, N}
     dim = size(x, 1)
     @assert dim == M 
 
-    q, p = assign_q_and_p(x, dim÷2)
-    N > M ? vcat(ps.weight*q, ps.weight*p) : vcat(ps.weight'*q, ps.weight'*p)
-end
-
-function (::PSDLayer{M, N})(x::AbstractArray{T, 3}, ps::NamedTuple) where {M, N, T}
-    dim = size(x, 1)
-    @assert dim == M 
-
-    q, p = assign_q_and_p(x, dim÷2)
-    N > M ? vcat(mat_tensor_mul(ps.weight,q), mat_tensor_mul(ps.weight,p)) : vcat(mat_tensor_mul(ps.weight', q), mat_tensor_mul(ps.weight', p))
+    qp = assign_q_and_p(x, dim÷2)
+    N > M ? vcat(custom_mat_mul(ps.weight, qp.q), custom_mat_mul(ps.weight, qp.p)) : vcat(custom_mat_mul(ps.weight', qp.q), custom_mat_mul(ps.weight', qp.p))
 end

src/layers/sympnets.jl

@@ -182,6 +182,9 @@ function parameterlength(::LinearLayer{M, M}) where {M}
         (M÷2)*(M÷2+1)÷2
 end
 
+@doc raw"""
+Multiplies a matrix with a vector, a matrix or a tensor.
+"""
 custom_mat_mul(weight::AbstractMatrix, x::AbstractVecOrMat) = weight*x 
 function custom_mat_mul(weight::AbstractMatrix, x::AbstractArray{T, 3}) where T 
         mat_tensor_mul(weight, x)
@@ -236,8 +239,8 @@ It converts the Array to a `NamedTuple` (via `assign_q_and_p`), then calls the S
 """
 function apply_layer_to_nt_and_return_array(x::AbstractArray, d::SympNetLayer{M, M}, ps) where {M}
         N2 = size(x, 1)÷2
-        q, p = assign_q_and_p(x, N2)
-        output = d((q=q, p=p), ps)
+        qp = assign_q_and_p(x, N2)
+        output = d(qp, ps)
         return vcat(output.q, output.p)
 end