def METHOD_NAME(fname, out_fname_prefix, dev=False):
    x = json.load(open(fname, encoding='utf8'))
    print(f"Preprocessing \"{fname}\" for fine-tuning...")
    if (os.path.exists(f'{out_fname_prefix}_src.txt') and 
        os.path.exists(f'{out_fname_prefix}_tgt.txt') and 
        os.path.exists(f'{out_fname_prefix}_gpt.json')):
        print(f"Skipped! Fine-tuning data existed at \"{out_fname_prefix}*.txt\"")
        if NEMO_LAUNCHER_CI:
            time.sleep(5)
        return
    with open(f'{out_fname_prefix}_src.txt', 'w') as f_src, open(f'{out_fname_prefix}_tgt.txt', 'w') as f_tgt, open(f'{out_fname_prefix}_gpt.json', 'w') as f_gpt:
        for i in x['data']:
            title = i['title'].replace('\n', '\\n')
            for j in i['paragraphs']:
                context = j['context'].replace('\n', '\\n')
                for k in j['qas']:
                    question = k['question'].replace('\n', '\\n')
                    if len(k['answers']) > 0:
                        if dev:
                            answer = k['answers'][0]['text'].replace('\n', '\\n')
                            f_src.write(f"Title: {title} Paragraph: {context} Question: {question}\n")
                            f_tgt.write(f"{answer}\n")
                            input_text = f"{question} {title} Paragraph: {context}"
                            gpt_sample = {"input" : input_text, "output" : answer}
                            gpt_sample = json.dumps(gpt_sample)
                            f_gpt.write(f"{gpt_sample}\n")
                        else:
                            for a in k['answers']:
                                answer = a['text'].replace('\n', '\\n')
                                f_src.write(f"Title: {title} Paragraph: {context} Question: {question}\n")
                                f_tgt.write(f"{answer}\n")
                                input_text = f"{question} {title} Paragraph: {context}"                        
                                gpt_sample = {"input" : input_text, "output" : answer}
                                gpt_sample = json.dumps(gpt_sample)
                                f_gpt.write(f"{gpt_sample}\n")
    print(f"Completed! Fine-tuning data saved at:")
    print(f"- \"{out_fname_prefix}_src.txt\"")
    print(f"- \"{out_fname_prefix}_tgt.txt\"")
    print(f"- \"{out_fname_prefix}_gpt.txt\"")