def main(conf): filterbank = load_best_filterbank_if_available(conf) _, checkpoint_dir = get_encoded_paths(conf, 'filterbank') if filterbank is None: print('There are no available filterbanks under: {}. Going to ' 'training.'.format(checkpoint_dir)) train_model_part(conf, train_part='filterbank') filterbank = load_best_filterbank_if_available(conf) else: print('Found available filterbank at: {}'.format(checkpoint_dir)) if not conf['filterbank_training']['reuse_pretrained_filterbank']: print('Refining filterbank...') train_model_part(conf, train_part='filterbank') filterbank = load_best_filterbank_if_available(conf) train_model_part(conf, train_part='separator', pretrained_filterbank=filterbank)
def main(conf): filterbank = load_best_filterbank_if_available(conf) _, checkpoint_dir = get_encoded_paths(conf, "filterbank") if filterbank is None: print("There are no available filterbanks under: {}. Going to " "training.".format(checkpoint_dir)) train_model_part(conf, train_part="filterbank") filterbank = load_best_filterbank_if_available(conf) else: print("Found available filterbank at: {}".format(checkpoint_dir)) if not conf["filterbank_training"]["reuse_pretrained_filterbank"]: print("Refining filterbank...") train_model_part(conf, train_part="filterbank") filterbank = load_best_filterbank_if_available(conf) train_model_part(conf, train_part="separator", pretrained_filterbank=filterbank)