| | |
| | | import logging |
| | | |
| | | from funasr.lm.abs_model import AbsLM |
| | | from funasr.lm.abs_model import LanguageModel |
| | | from funasr.lm.seq_rnn_lm import SequentialRNNLM |
| | | from funasr.lm.transformer_lm import TransformerLM |
| | | from funasr.torch_utils.initialize import initialize |
| | |
| | | type_check=AbsLM, |
| | | default="seq_rnn", |
| | | ) |
| | | model_choices = ClassChoices( |
| | | "model", |
| | | classes=dict( |
| | | lm=LanguageModel, |
| | | ), |
| | | default="lm", |
| | | ) |
| | | |
| | | class_choices_list = [ |
| | | # --lm and --lm_conf |
| | | lm_choices |
| | | lm_choices, |
| | | # --model and --model_conf |
| | | model_choices |
| | | ] |
| | | |
| | | |
| | |
| | | else: |
| | | vocab_size = None |
| | | |
| | | # lm |
| | | lm_class = lm_choices.get_class(args.lm) |
| | | lm = lm_class(vocab_size=vocab_size, **args.lm_conf) |
| | | |
| | | model_class = model_choices.get_class(args.model) |
| | | model = model_class(lm=lm, vocab_size=vocab_size, **args.model_conf) |
| | | |
| | | # initialize |
| | | if args.init is not None: |
| | | initialize(model, args.init) |
| | | |
| | | return model |
| | |
| | | # 3. Initialize |
| | | if args.init is not None: |
| | | initialize(model, args.init) |
| | | |
| | | assert check_return_type(model) |
| | | return model |