| | |
|---|
| | | deep_update(model_conf, kwargs.get("model_conf", {})) |
|---|
| | | deep_update(model_conf, kwargs) |
|---|
| | | model = model_class(**model_conf, vocab_size=vocab_size) |
|---|
| | | model.to(device) |
|---|
| | | |
|---|
| | | # init_param |
|---|
| | | init_param = kwargs.get("init_param", None) |
|---|
| | |
|---|
| | | model.to(torch.float16) |
|---|
| | | elif kwargs.get("bf16", False): |
|---|
| | | model.to(torch.bfloat16) |
|---|
| | | model.to(device) |
|---|
| | | return model, kwargs |
|---|
| | | |
|---|
| | | def __call__(self, *args, **cfg): |
|---|
| | |
|---|
| | | input, input_len=input_len, model=self.vad_model, kwargs=self.vad_kwargs, **cfg |
|---|
| | | ) |
|---|
| | | end_vad = time.time() |
|---|
| | | |
|---|
| | | |
|---|
| | | # FIX(gcf): concat the vad clips for sense vocie model for better aed |
|---|
| | | if kwargs.get("merge_vad", False): |
|---|
| | | for i in range(len(res)): |
|---|
| | |
|---|
| | | result[k] = restored_data[j][k] |
|---|
| | | else: |
|---|
| | | result[k] += restored_data[j][k] |
|---|
| | | |
|---|
| | | |
|---|
| | | if not len(result["text"].strip()): |
|---|
| | | continue |
|---|
| | | return_raw_text = kwargs.get("return_raw_text", False) |
|---|
| | |
|---|
| | | if return_raw_text: |
|---|
| | | result["raw_text"] = raw_text |
|---|
| | | result["text"] = punc_res[0]["text"] |
|---|
| | | |
|---|
| | | |
|---|
| | | # speaker embedding cluster after resorted |
|---|
| | | if self.spk_model is not None and kwargs.get("return_spk_res", True): |
|---|
| | | if raw_text is None: |
|---|
| | |
|---|
| | | ) |
|---|
| | | |
|---|
| | | with torch.no_grad(): |
|---|
| | | export_dir = export_utils.export(model=model, data_in=data_list, **kwargs) |
|---|
| | | export_dir = export_utils.export(model=model, data_in=data_list, **kwargs) |
|---|
| | | |
|---|
| | | return export_dir |
|---|
