# /*---------------------------------------------------------------------------------------------
#  * Copyright (c) 2022 STMicroelectronics.
#  * All rights reserved.
#  * This software is licensed under terms that can be found in the LICENSE file in
#  * the root directory of this software component.
#  * If no LICENSE file comes with this software, it is provided AS-IS.
#  *--------------------------------------------------------------------------------------------*/


import logging
import os
import sys
import warnings

import hydra
import mlflow
from hydra.core.hydra_config import HydraConfig
from omegaconf import DictConfig, OmegaConf
from temp_scripts.tmp import stm32ai_deploy
warnings.filterwarnings("ignore")
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
import tensorflow as tf

logger = tf.get_logger()
logger.setLevel(logging.ERROR)

sys.path.append(os.path.abspath('../evaluate'))
sys.path.append(os.path.abspath('../utils'))
sys.path.append(os.path.abspath('../utils/models'))
sys.path.append(os.path.abspath('../../../common'))

from evaluate import evaluate_model
from utils import get_config, mlflow_ini, setup_seed


@hydra.main(version_base=None, config_path="", config_name="user_config")
def main(cfg: DictConfig) -> None:
    # Initilize configuration & mlflow
    configs = get_config(cfg)
    mlflow_ini(configs)

    # Set all seeds
    setup_seed(42)

    # Evaluate model performance / footprints
    evaluate_model(cfg, c_header=True, c_code=True)
    stm32ai_deploy(cfg, debug=False)

    # Record the whole hydra working directory to get all infos
    mlflow.log_artifact(HydraConfig.get().runtime.output_dir)
    mlflow.end_run()


if __name__ == "__main__":
    main()