def init_model()

in experiment.py [0:0]

• 37 lines of code
• 8 McCabe index (conditional complexity)

def init_model(cfg, force_load=False, clear_stats=False, add_log_vars=None):

    # get the model
    model = C3DPO(**cfg.MODEL)

    # obtain the network outputs that should be logged
    if hasattr(model, 'log_vars'):
        log_vars = copy.deepcopy(model.log_vars)
    else:
        log_vars = ['objective']
    if add_log_vars is not None:
        log_vars.extend(copy.deepcopy(add_log_vars))

    visdom_env_charts = get_visdom_env(cfg) + "_charts"

    # init stats struct
    stats = Stats(log_vars, visdom_env=visdom_env_charts,
                  verbose=False, visdom_server=cfg.visdom_server,
                  visdom_port=cfg.visdom_port)

    # find the last checkpoint
    if cfg.resume_epoch > 0:
        model_path = get_checkpoint(cfg.exp_dir, cfg.resume_epoch)
    else:
        model_path = find_last_checkpoint(cfg.exp_dir)

    optimizer_state = None

    if model_path is not None:
        print("found previous model %s" % model_path)
        if force_load or cfg.resume:
            print("   -> resuming")
            model_state_dict, stats_load, optimizer_state = load_model(
                model_path)
            if not clear_stats:
                stats = stats_load
            else:
                print("   -> clearing stats")
            model.load_state_dict(model_state_dict, strict=True)
            model.log_vars = log_vars
        else:
            print("   -> but not resuming -> starting from scratch")

    # update in case it got lost during load:
    stats.visdom_env = visdom_env_charts
    stats.visdom_server = cfg.visdom_server
    stats.visdom_port = cfg.visdom_port
    stats.plot_file = os.path.join(cfg.exp_dir, 'train_stats.pdf')
    stats.synchronize_logged_vars(log_vars)

    return model, stats, optimizer_state