This is a follow-up question regarding this question. I managed to verify in
python that the output of the first pooling layer will be a $14 \times 14\times 32$ tensor.
I interpret this as having 32 $14 \times 14$ images. Maybe my interpretation is mistaken. In the second convolutional layer we apply $64$ filters.
When I type in
conv2.shape I get
TensorShape([Dimension(55000), Dimension(14), Dimension(14), Dimension(64)]).
How that comes? I mean I am in interested in the outcome of the depth, which is $64.$