Hi @ptrblck
First of all, I am thankful for your explanations and providing the links and image which really helped me to understand how grouped option works.
Kindly, there is still something unclear for me.
If I am not wrong, based on your scheme, it is possible that channels from different filter are grouped. Is that right? Because in the standard one each filter has 4 channel with size 3,3, while in the grouped one each filter has 8 channel with size 3,3.
could you please take a look in this link, where the an example of convolutional operation is explained.
Here is part of that link:
"Here the input layer is a 5 x 5 x 3 matrix, with 3 channels. The filter is a 3 x 3 x 3 matrix. First, each of the kernels in the filter are applied to three channels in the input layer, separately. Three convolutions are performed, which result in 3 channels with size 3 x 3. Then these three channels are summed together (element-wise addition) to form one single channel (3 x 3 x 1). This channel is the result of convolution of the input layer (5 x 5 x 3 matrix) using a filter (3 x 3 x 3 matrix)."
Then, based on your standard convolutional layer, each filter has shape [4,3,3] such that each [1,3,3] is separately applied on each [1,24,24] input activation. When convoultional operation is done, the output will be [4,24,24] for one filter, afterwards, they are summed across channel dimension to output activation with shape [1,24,24]. Am I right?
and what I need is the activations for each filter with shape [4,24,24] instead of [1,24,24].