Multiply a 3D matrix with a 2D matrix

I would like to share my answer to the problems of:

1) making the tensor product of two tensors (of any valence);

2) making the contraction of two tensors along any dimension.

Here are my subroutines for the first and second tasks:

1) tensor product:

function [C] = tensor(A,B)
   C = squeeze( reshape( repmat(A(:), 1, numel(B)).*B(:).' , [size(A),size(B)] ) );
end

2) contraction: Here A and B are the tensors to be contracted along the dimesions i and j respectively. The lengths of these dimensions should be equal, of course. There's no check for this (this would obscure the code) but apart from this it works well.

   function [C] = tensorcontraction(A,B, i,j)
      sa = size(A);
      La = length(sa);
      ia = 1:La;
      ia(i) = [];
      ia = [ia i];

      sb = size(B);
      Lb = length(sb);
      ib = 1:Lb;
      ib(j) = [];
      ib = [j ib];

      % making the i-th dimension the last in A
      A1 = permute(A, ia);
      % making the j-th dimension the first in B
      B1 = permute(B, ib);

      % making both A and B 2D-matrices to make use of the
      % matrix multiplication along the second dimension of A
      % and the first dimension of B
      A2 = reshape(A1, [],sa(i));
      B2 = reshape(B1, sb(j),[]);

      % here's the implicit implication that sa(i) == sb(j),
      % otherwise - crash
      C2 = A2*B2;

      % back to the original shape with the exception
      % of dimensions along which we've just contracted
      sa(i) = [];
      sb(j) = [];
      C = squeeze( reshape( C2, [sa,sb] ) );
   end

Any critics?