Thanks for the kind words and yes you are correct. The input shapes are flexible due to the usage of the adaptive pooling layers, which make sure the output activation shape matches the desired feature dimension of the linear layers.
Note that larger inputs would work without a problem, but the model would be still limited to a min. input size, since the intermediate activations could become empty otherwise.