def setup(): """Parse command line arguments, load model parameters, load configurations and setup environment.""" # Parse the command line arguments args = parse_arguments() # Load parameters params = load_yaml(args.params) # Load training 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'] # Make sure result directory exists make_sure_path_exists(config['result_dir']) # Setup GPUs os.environ["CUDA_VISIBLE_DEVICES"] = config['gpu'] return params, config
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
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