| | |
| | | device = "cuda" |
| | | else: |
| | | device = "cpu" |
| | | |
| | | if param_dict is not None and "decoding_model" in param_dict: |
| | | if param_dict["decoding_model"] == "fast": |
| | | decoding_ind = 0 |
| | | decoding_mode = "model1" |
| | | elif param_dict["decoding_model"] == "normal": |
| | | decoding_ind = 0 |
| | | decoding_mode = "model2" |
| | | elif param_dict["decoding_model"] == "offline": |
| | | decoding_ind = 1 |
| | | decoding_mode = "model2" |
| | | else: |
| | | raise NotImplementedError("unsupported decoding model {}".format(param_dict["decoding_model"])) |
| | | |
| | | # 1. Set random-seed |
| | | set_all_random_seed(seed) |
| | |
| | | output_dir_v2: Optional[str] = None, |
| | | fs: dict = None, |
| | | param_dict: dict = None, |
| | | **kwargs, |
| | | ): |
| | | # 3. Build data-iterator |
| | | if data_path_and_name_and_type is None and raw_inputs is not None: |