Interpreting fully connected layer in convolutional Neural network architecture

Question

I am trying to interpret this neural network architecture

3×3×32 Convolutional 2×2 MaxPool Dropout 3×3×64 Convolutional 2×2 MaxPool Dropout Flatten 1 × 128 Full connected Dropout 128 × 10 Fully connected Softmax

i am confused here 1 × 128 Full connected and 128 × 10 Fully connected what does it means?

Answer 1

After using the flattening operation, the output will be (None, x)

Next in the 128 node fully connected(FC) layer, x is passed through each of the 128 neurons (nodes)

Finally, each of the 128 node's output are passed to 10 node FC layer with softmax activation

Here is a visualization, hope it helps