def util_dl_s3_model()

in ml-images/s3/app.py [0:0]

• 14 lines of code
• 2 McCabe index (conditional complexity)

def util_dl_s3_model():
    logger.info('Download model files from S3')
    if not os.path.isdir(MODEL_NLP_DIR):
        os.mkdir(MODEL_NLP_DIR)
        logger.info('Created folder: ' + MODEL_NLP_DIR)
    else:
        logger.info('Folder already exists: ' + MODEL_NLP_DIR)
    s3.meta.client.download_file(os.environ['S3_MODEL_BUCKET_NAME'], os.environ['S3_NLP1_MODEL'], '/tmp/nlp1/pytorch_model.bin')
    s3.meta.client.download_file(os.environ['S3_MODEL_BUCKET_NAME'], os.environ['S3_NLP1_CONFIG'], '/tmp/nlp1/config.json')
    s3.meta.client.download_file(os.environ['S3_MODEL_BUCKET_NAME'], os.environ['S3_NLP1_TOKENIZER'], '/tmp/nlp1/tokenizer.json')
    s3.meta.client.download_file(os.environ['S3_MODEL_BUCKET_NAME'], os.environ['S3_NLP1_TOKENIZER_CONFIG'], '/tmp/nlp1/tokenizer_config.json')
    tokenizer = AutoTokenizer.from_pretrained("/tmp/nlp1/")
    model = AutoModelForQuestionAnswering.from_pretrained("/tmp/nlp1/")
    return [model, tokenizer]