models/hyperstyle/utils/train_utils.py

def aggregate_loss_dict(agg_loss_dict):
    mean_vals = {}
    for output in agg_loss_dict:
        for key in output:
            mean_vals[key] = mean_vals.setdefault(key, []) + [output[key]]
    for key in mean_vals:
        if len(mean_vals[key]) > 0:
            mean_vals[key] = sum(mean_vals[key]) / len(mean_vals[key])
        else:
            print(f'{key} has no value')
            mean_vals[key] = 0
    return mean_vals