Exemplo n.º 1
0
def setup():
    """Parse command line arguments, load model parameters, load configurations,
    setup environment and setup loggers."""
    # Parse the command line arguments
    args = parse_arguments()

    # Load parameters
    params = load_yaml(
        args.params)  # greg: args.params es el nombre del parameters_file yaml
    if params.get(
            'is_accompaniment') and params.get('condition_track_idx') is None:
        raise TypeError("`condition_track_idx` cannot be None type in "
                        "accompaniment mode.")

    # Load configurations
    config = load_yaml(args.config)
    update_not_none(config, vars(args))

    # Set unspecified schedule steps to default values
    for target in (config['learning_rate_schedule'], config['slope_schedule']):
        if target['start'] is None:
            target['start'] = 0
        if target['end'] is None:
            target['end'] = config['steps']

    # Setup experiment directories and update them to configuration dictionary
    setup_dirs(config)

    # Setup loggers
    del logging.getLogger('tensorflow').handlers[0]
    setup_loggers(config['log_dir'])

    # Setup GPUs
    os.environ["CUDA_VISIBLE_DEVICES"] = config['gpu']

    # Backup source code
    backup_src(config['src_dir'])

    return params, config
Exemplo n.º 2
0
def setup():
    """Parse command line arguments, load model parameters, load configurations,
    setup environment and setup loggers."""
    # Parse the command line arguments
    args = parse_arguments()

    # Load parameters
    params = load_yaml(args.params)
    if params['is_accompaniment'] and params['condition_track_idx'] is None:
        raise TypeError("`condition_track_idx` cannot be None type in "
                        "accompaniment mode.")

    # Load configurations
    config = load_yaml(args.config)
    update_not_none(config, vars(args))

    # Set unspecified schedule steps to default values
    for target in (config['learning_rate_schedule'], config['slope_schedule']):
        if target['start'] is None:
            target['start'] = 0
        if target['end'] is None:
            target['end'] = config['steps']

    # Setup experiment directories and update them to configuration dictionary
    setup_dirs(config)

    # Setup loggers
    del logging.getLogger('tensorflow').handlers[0]
    setup_loggers(config['log_dir'])

    # Setup GPUs
    os.environ["CUDA_VISIBLE_DEVICES"] = config['gpu']

    # Backup source code
    backup_src(config['src_dir'])

    return params, config