Finalizing tutorial SPIE

Author: mldiego

code/nnv/engine/nn/layers/BatchNormalizationLayer.m

@@ -219,7 +219,8 @@
                     for i=1:obj.NumChannels
                         x.V(:,:,:,i,:) = x.V(:,:,:,i,:) .* 1/sqrt(obj.TrainedVariance(:,:,:,i) + obj.Epsilon);
                     end
-                    % 2) Batch normalization operation further shifts and scales the activations using Scale and Offset values
+                    % 2) Batch normalization operation further shifts and scales the 
+                    % activations using Scale and Offset values
                     % 2a) Scale values
                     for i=1:obj.NumChannels
                         x.V(:,:,:,i,:) = x.V(:,:,:,i,:) .* obj.Scale(:,:,:,i);
@@ -262,7 +263,8 @@
                     for i=1:obj.NumChannels
                         x.V(:,:,i,:) = x.V(:,:,i,:) .* 1/sqrt(obj.TrainedVariance(:,:,i) + obj.Epsilon);
                     end
-                    % 2) Batch normalization operation further shifts and scales the activations using Scale and Offset values
+                    % 2) Batch normalization operation further shifts and scales the 
+                    % activations using Scale and Offset values
                     % 2a) Scale values
                     for i=1:obj.NumChannels
                         x.V(:,:,i,:) = x.V(:,:,i,:) .* obj.Scale(:,:,i);

code/nnv/engine/nn/layers/Conv2DLayer.m

@@ -520,8 +520,12 @@ function set_name(obj, name)
 
             % compute output sets
             if ~isa(input.V, 'gpuArray')
-                c = vl_nnconv(input.V(:,:,:,1), obj.Weights, obj.Bias, 'Stride', obj.Stride, 'Pad', obj.PaddingSize, 'Dilate', obj.DilationFactor);
-                V = vl_nnconv(input.V(:,:,:,2:input.numPred + 1), obj.Weights, [], 'Stride', obj.Stride, 'Pad', obj.PaddingSize, 'Dilate', obj.DilationFactor);   
+                % c = vl_nnconv(input.V(:,:,:,1), obj.Weights, obj.Bias, 'Stride', obj.Stride, 'Pad', obj.PaddingSize, 'Dilate', obj.DilationFactor);
+                % V = vl_nnconv(input.V(:,:,:,2:input.numPred + 1), obj.Weights, [], 'Stride', obj.Stride, 'Pad', obj.PaddingSize, 'Dilate', obj.DilationFactor);   
+                c = dlconv(dlarray(input.V(:,:,:,1), "SSC"), obj.Weights, obj.Bias, 'Stride', obj.Stride, 'Padding', obj.PaddingSize, 'DilationFactor', obj.DilationFactor);
+                V = dlconv(dlarray(input.V(:,:,:,2:input.numPred + 1), "SSCB"), obj.Weights, 0, 'Stride', obj.Stride, 'Padding', obj.PaddingSize, 'DilationFactor', obj.DilationFactor);
+                c = extractdata(c);
+                V = extractdata(V);
             else
                 c = dlconv(dlarray(input.V(:,:,:,1), "SSC"), obj.Weights, obj.Bias, 'Stride', obj.Stride, 'Padding', obj.PaddingSize, 'DilationFactor', obj.DilationFactor);
                 V = dlconv(dlarray(input.V(:,:,:,2:input.numPred + 1), "SSCB"), obj.Weights, 0, 'Stride', obj.Stride, 'Padding', obj.PaddingSize, 'DilationFactor', obj.DilationFactor);