Hi @Vasiliy_Kuznetsov
Thank you for your input, I have updated my script to pass in a few images into the fused model as inputs for calibration.
Please see the updated script here

  
      github.com
  
  
    raghavgurbaxani/Quantization_Experiments/blob/master/try_quantization.py 5
import os
import config as cfg
from model import East
import torch
import utils
import preprossing
import cv2
import numpy as np
import time

def uninplace(model):
    if hasattr(model, 'inplace'):
        model.inplace = False
    if not model.children():
        return
    for child in model.children():
        uninplace(child)
        
def print_size_of_model(model):
    torch.save(model.state_dict(), "temp.p")


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But still the quantized model size is bigger than the original model -
Original Size:
Size (MB): 6.623636

Fused model Size:
Size (MB): 6.638188

Quantized model Size:
Size (MB): 6.712286

there seems to be some improvement due to the calibration, but the quantized model size is still not satisfactory compared to the original size  
Could you suggest what’s going wrong here ?