I have trained a PyTorch model, which I converted to Keras using the pytorch2keras lib.
using this Keras model to convert to tflite. I want to run the tflite on coral devices.
things which i noticed :

Keras model size (57.6MB)
Using dynamic range quantization the generated tflite is of size(15MB)
Using integer only quantization the generated tflite is also of size(15MB)

Ideally, we should be able to reduce the model size even further as we convert fp32 to int8
Can Anyone help me to understand why this happening?
sharing my conversion notebook and Keras modelkeras_model : data.zip - Google Drive 7