verify_consistency.py

import os
import sys
import pickle
import numpy as np
from tensorflow.keras.models import load_model

sys.path.append("backend")

MODEL_PATH = "model.h5"
ENCODER_PATH = "encoder.pkl"

def verify():
    if not os.path.exists(MODEL_PATH) or not os.path.exists(ENCODER_PATH):
        print("Model or encoder not found.")
        return

    try:
        print("Loading artifacts...")
        model = load_model(MODEL_PATH)
        with open(ENCODER_PATH, 'rb') as f:
            le = pickle.load(f)
        
        print(f"Model output shape: {model.output_shape}")
        expected_classes = model.output_shape[1]
        actual_classes_len = len(le.classes_)
        actual_classes = le.classes_
        
        print(f"Encoder classes ({actual_classes_len}): {actual_classes}")
        
        if expected_classes != actual_classes_len:
            print(f"FAIL: Mismatch! Model expects {expected_classes} outputs, but encoder has {actual_classes_len} classes.")
        else:
            print("PASS: Model and encoder dimensions match.")

    except Exception as e:
        print(f"Error during verification: {e}")

if __name__ == "__main__":
    verify()