Change abstract arrays back to arrays

dahong67 · Jan 12, 2024 · b72f6e9 · b72f6e9
1 parent 2a7f0c2
commit b72f6e9
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Showing 2 changed files with 5 additions and 6 deletions.
diff --git a/ext/CUDAExt.jl b/ext/CUDAExt.jl
@@ -19,8 +19,7 @@ function _gcp(
     T = promote_type(TX, Float32)
 
     # Random initialization
-    M0 = CPD(ones(T, r), rand.(T, size(X), r))
-    #M0norm = sqrt(mapreduce(abs2, +, M0[I] for I in CartesianIndices(size(M0))))
+    M0 = CPD(ones(T, r), rand.(T, size(X), r))X_gpu
     M0norm = sqrt(sum(abs2, M0[I] for I in CartesianIndices(size(M0))))
     Xnorm = sqrt(mapreduce(x -> isnan(x) ? 0 : abs2(x), +, X, init=0f0))
     for k in Base.OneTo(N)

diff --git a/src/gcp-opt.jl b/src/gcp-opt.jl
@@ -2,7 +2,7 @@
 
 # Main fitting function
 """
-    gcp(X::AbstractArray, r, loss = LeastSquaresLoss();
+    gcp(X::Array, r, loss = LeastSquaresLoss();
         constraints = default_constraints(loss),
         algorithm = default_algorithm(X, r, loss, constraints)) -> CPD
 
@@ -21,7 +21,7 @@ to see what losses are supported.
 See also: `CPD`, `AbstractLoss`.
 """
 gcp(
-    X::AbstractArray,
+    X::Array,
     r,
     loss = LeastSquaresLoss();
     constraints = default_constraints(loss),
@@ -43,7 +43,7 @@ function default_constraints(loss)
 end
 
 # Choose default algorithm
-default_algorithm(X::AbstractArray{<:Real}, r, loss::LeastSquaresLoss, constraints::Tuple{}) =
+default_algorithm(X::Array{<:Real}, r, loss::LeastSquaresLoss, constraints::Tuple{}) =
     GCPAlgorithms.ALS()
 default_algorithm(X, r, loss, constraints) = GCPAlgorithms.LBFGSB()
 
@@ -213,7 +213,7 @@ function mttkrp(X, U, n)
     return Rn
 end
 
-function khatrirao(A::Vararg{T,N}) where {T<:AbstractMatrix,N}
+function khatrirao(A::Vararg{T,N}) where {T<:Matrix,N}
     r = size(A[1],2)
     R = ntuple(Val(N)) do k
         dims = (ntuple(i->1,Val(N-k))..., :, ntuple(i->1,Val(k-1))..., r)