| | |
| | | if asr_model.frontend is None and frontend_conf is not None: |
| | | frontend = WavFrontend(**frontend_conf) |
| | | asr_model.frontend = frontend |
| | | logging.info("asr_model: {}".format(asr_model)) |
| | | logging.info("asr_train_args: {}".format(asr_train_args)) |
| | | # logging.info("asr_model: {}".format(asr_model)) |
| | | # logging.info("asr_train_args: {}".format(asr_train_args)) |
| | | asr_model.to(dtype=getattr(torch, dtype)).eval() |
| | | |
| | | decoder = asr_model.decoder |
| | |
| | | else: |
| | | tokenizer = build_tokenizer(token_type=token_type) |
| | | converter = TokenIDConverter(token_list=token_list) |
| | | logging.info(f"Text tokenizer: {tokenizer}") |
| | | # logging.info(f"Text tokenizer: {tokenizer}") |
| | | |
| | | self.asr_model = asr_model |
| | | self.asr_train_args = asr_train_args |