Do outer tensor-vector products more efficiently

src/gcp-opt.jl

@@ -190,19 +190,22 @@ function mttkrp(X, U, n)
     # Compute tensor-vector products right to left (equations 15, 17) for each rank
     for j in 1:r
         # Inner tensor-vector products
-        Rn_j = reshape(reshape(X, Jn, Kn) * reduce(kron, [view(U[i], :, j) for i in reverse(n+1:N)], init=1), size(X)[1:n]) 
-
+        inner = reshape(reshape(X, Jn, Kn) * reduce(kron, [view(U[i], :, j) for i in reverse(n+1:N)], init=1), size(X)[1:n]) 
         # Outer tensor-vector products
+        Jn_inner = prod(size(inner)[1:n-1])
+        Kn_inner = prod(size(inner)[n:end])
+        Rn[:, j] = transpose(reshape(inner, Jn_inner, Kn_inner)) * reduce(kron, [view(U[i], :, j) for i in reverse(1:n-1)], 
+                        init=1)
         # Permute so dims to be multiplied are last
-        Rn_j = permutedims(Rn_j, [n; 1:n-1])
+        #Rn_j = permutedims(Rn_j, [n; 1:n-1])
         # Multiply from right to left
-        sz = size(Rn_j)
-        m = length(sz)
-        for k in n-1:-1:1
-            Rn_j = reshape(Rn_j, prod(sz[1:m-1]), sz[m]) * U[k][:, j]
-            m -= 1
-        end
-        Rn[:, j] = Rn_j  
+        #sz = size(Rn_j)
+        #m = length(sz)
+        #for k in n-1:-1:1
+        #    Rn_j = reshape(Rn_j, prod(sz[1:m-1]), sz[m]) * U[k][:, j]
+        #    m -= 1
+        #end
+        #Rn[:, j] = Rn_j  
     end
     return Rn
 end