What's the role of Inception_ResnetV1.py file in Face Recognition?

[rohansh-tty]

Reason:

f = open('./facerec_128D.txt','r')
    data_set = json.loads(f.read());
    returnRes = [];
    for (i,features_128D) in enumerate(features_arr):
        result = "Unknown";
        smallest = sys.maxsize
        for person in data_set.keys():
            person_data = data_set[person][positions[i]];
            for data in person_data:
                distance = np.sqrt(np.sum(np.square(data-features_128D)))
                if(distance < smallest):
                    smallest = distance;
                    result = person;
        percentage =  min(100, 100 * thres / smallest)
        if percentage <= percent_thres :
            result = "Unknown"
        returnRes.append((result,percentage))
    return returnRes    

```This is the main code block for face recognition task, where it compares and measures match percentage. I didn't understand what Resnet.py has to do here?
*I'm a beginner in Computer Vision, so if I've asked a wrong question, I'm sorry!

[rohansh-tty]

Actually I understood how the face recognition model works, also the contribution of Inception Resnet(Produce Face Embeddings vector). But I can't figure out how to save the model and then convert it to a TensorFlow lite model?