diff --git a/src/base.jl b/src/base.jl
index 27c2629..1cd402c 100644
--- a/src/base.jl
+++ b/src/base.jl
@@ -68,10 +68,10 @@ const MatOrCentral{T,N} = Union{AbstractMatrix{T},CentralTensor{T,N}}
 function dense_central(ten::CentralTensor)
     # @cast V[(u1, u2), (d1, d2)] :=
     #     ten.e11[u1, d1] * ten.e21[u2, d1] * ten.e12[u1, d2] * ten.e22[u2, d2]
-    a11 = reshape(CuArray(ten.e11), size(ten.e11, 1), :, size(ten.e11, 2))
-    a21 = reshape(CuArray(ten.e21), :, size(ten.e21, 1), size(ten.e21, 2))
-    a12 = reshape(CuArray(ten.e12), size(ten.e12, 1), 1, 1, size(ten.e12, 2))
-    a22 = reshape(CuArray(ten.e22), 1, size(ten.e22, 1), 1, size(ten.e22, 2))
+    a11 = reshape(ten.e11, size(ten.e11, 1), :, size(ten.e11, 2))
+    a21 = reshape(ten.e21, :, size(ten.e21, 1), size(ten.e21, 2))
+    a12 = reshape(ten.e12, size(ten.e12, 1), 1, 1, size(ten.e12, 2))
+    a22 = reshape(ten.e22, 1, size(ten.e22, 1), 1, size(ten.e22, 2))
     V = @__dot__(a11 * a21 * a12 * a22)
     V = reshape(V, size(V, 1) * size(V, 2), size(V, 3) * size(V, 4))
     V ./ maximum(V)
diff --git a/src/contractions/central.jl b/src/contractions/central.jl
index a8e87df..a3ed82d 100644
--- a/src/contractions/central.jl
+++ b/src/contractions/central.jl
@@ -69,8 +69,9 @@ function batched_mul!(
     LE::Tensor{R,3},
     M::AbstractArray{R,2},
 ) where {R<:Real}
+    onGPU = typeof(newLE) <: CuArray ? true : false
     N1, N2 = size(M)
-    new_M = CUDA.CuArray(M)  # TODO: this is a hack to solve problem with types;
+    new_M = ArrayorCuArray(M, onGPU)  # TODO: this is a hack to solve problem with types;
     new_M = reshape(new_M, (N1, N2, 1))
     NNlib.batched_mul!(newLE, LE, new_M)
 end