update with main (#1786)

zhifu gao

2024-06-06 32e783664534bbb8d3b8ba64c2c2ecb42398eb00

 funasr/models/sense_voice/model.py

@@ -1264,15 +1264,29 @@
        if isinstance(task, str):
            task = [task]
        task = "".join([f"<|{x}|>" for x in task])
        initial_prompt = kwargs.get("initial_prompt", f"<|startoftranscript|>{task}")
        
        sos = kwargs.get("model_conf").get("sos")
        if isinstance(sos, str):
            initial_prompt = kwargs.get("initial_prompt", f"<|startoftranscript|>{task}")

        language = DecodingOptions.get("language", None)
        language = None if language == "auto" else language
            language = DecodingOptions.get("language", None)
            language = None if language == "auto" else language

        sos = f"{initial_prompt}<|{language}|>" if language is not None else initial_prompt
        sos_int = tokenizer.encode(sos, allowed_special="all")
            sos = f"{initial_prompt}<|{language}|>" if language is not None else initial_prompt
            sos_int = tokenizer.encode(sos, allowed_special="all")
        else:
            language = DecodingOptions.get("language", None)
            language = None if language == "auto" else language
            initial_prompt = kwargs.get("initial_prompt", f"{task}")
            initial_prompt_lid = f"{initial_prompt}<|{language}|>" if language is not None else initial_prompt
            initial_prompt_lid_int = tokenizer.encode(initial_prompt_lid, allowed_special="all")
            sos_int = [sos] + initial_prompt_lid_int
        eos = kwargs.get("model_conf").get("eos")
        eos_int = tokenizer.encode(eos, allowed_special="all")
        if isinstance(eos, str):
            eos_int = tokenizer.encode(eos, allowed_special="all")
        else:
            eos_int = [eos]

        self.beam_search.sos = sos_int
        self.beam_search.eos = eos_int[0]

@@ -1298,7 +1312,7 @@
        self.beam_search.event_score_ga = DecodingOptions.get("gain_tokens_score", [1, 1, 1, 1])

        encoder_out, encoder_out_lens = self.encode(
            speech[None, :, :].permute(0, 2, 1), speech_lengths
            speech[None, :, :], speech_lengths
        )

        if text_token_int is not None: