Custom Loss function for MSE on Matconvnet

Question

Issue when creating a custom loss function. Sorry I am a bit new to matconvnet

So essentially the output for my Neural Network is aimed to be a vector with 2 elements (ex: [1,2]) with an error function based upon the RMSE

So I changed the cnn_train so that the labels would be instead a 2 by # of training examples. In the code below x = 1 x 1 x 2 x batchSize set and c is the labels.

function y = wf_rmse(x, c, varargin)
% Custom loss function for MSE Error
org = size(x);
x = reshape(x, size(c));

if ~isempty(varargin) && ~ischar(varargin{1})  % passed in dzdy
    dzdy = varargin{1} ;
    varargin(1) = [] ;
else
    dzdy = [] ;
end

% Forward pass
if(nargin <= 2 || isempty(dzdy))
    y = sum(sum(((x-c).^2))/2));

% Back pass  
elseif(nargin == 3 && ~isempty(dzdy))
    y = 2 * dzdy * (x - c);
    y = reshape(y, org);
end

When I include this as part of the network, the network initializes fine, but I get an error during training of, even though the dimensions of the gradient output should match the dimensions of the others.

Error using vl_nnconv
DEROUTPUT dimensions are incompatible with X and FILTERS.

Any suggestions on resolving the issue?