unit test modelscope for sd

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2023-02-27 e14323e6ab5e78e01bce98bec236947b07069d5e

unit test modelscope for sd

 funasr/bin/diar_inference_launch.py

@@ -127,7 +127,7 @@
def inference_launch(mode, **kwargs):
    if mode == "sond":
        from funasr.bin.sond_inference import inference_modelscope
        return inference_modelscope(**kwargs)
        return inference_modelscope(mode=mode, **kwargs)
    elif mode == "sond_demo":
        from funasr.bin.sond_inference import inference_modelscope
        param_dict = {
@@ -141,7 +141,7 @@
                    kwargs["param_dict"][key] = param_dict[key]
        else:
            kwargs["param_dict"] = param_dict
        return inference_modelscope(**kwargs)
        return inference_modelscope(mode=mode, **kwargs)
    else:
        logging.info("Unknown decoding mode: {}".format(mode))
        return None

 funasr/bin/sond_inference.py

@@ -231,6 +231,7 @@
        dur_threshold: int = 10,
        out_format: str = "vad",
        param_dict: Optional[dict] = None,
        mode: str = "sond",
        **kwargs,
):
    assert check_argument_types()
@@ -254,7 +255,7 @@
    set_all_random_seed(seed)

    # 2a. Build speech2xvec [Optional]
    if param_dict is not None and "extract_profile" in param_dict and param_dict["extract_profile"]:
    if mode == "sond_demo" and param_dict is not None and "extract_profile" in param_dict and param_dict["extract_profile"]:
        assert "sv_train_config" in param_dict, "sv_train_config must be provided param_dict."
        assert "sv_model_file" in param_dict, "sv_model_file must be provided in param_dict."
        sv_train_config = param_dict["sv_train_config"]