Make vad-related parameters configurable for batched inference. (#923)

This commit is contained in:
zh-plus
2024-07-24 10:00:32 +08:00
committed by GitHub
parent eb8390233c
commit 83a368e98a

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@@ -122,6 +122,8 @@ class BatchedInferencePipeline(Pipeline):
device: Union[int, str, "torch.device"] = -1, device: Union[int, str, "torch.device"] = -1,
chunk_length: int = 30, chunk_length: int = 30,
vad_device: Union[int, str, "torch.device"] = "auto", vad_device: Union[int, str, "torch.device"] = "auto",
vad_onset: float = 0.500,
vad_offset: float = 0.363,
framework="pt", framework="pt",
language: Optional[str] = None, language: Optional[str] = None,
**kwargs, **kwargs,
@@ -133,8 +135,8 @@ class BatchedInferencePipeline(Pipeline):
self._batch_size = kwargs.pop("batch_size", None) self._batch_size = kwargs.pop("batch_size", None)
self._num_workers = 0 self._num_workers = 0
self.use_vad_model = use_vad_model self.use_vad_model = use_vad_model
self.vad_onset = 0.500 self.vad_onset = vad_onset
self.vad_offset = 0.363 self.vad_offset = vad_offset
self.vad_model_path = os.path.join(get_assets_path(), "pyannote_vad_model.bin") self.vad_model_path = os.path.join(get_assets_path(), "pyannote_vad_model.bin")
self.vad_model = None self.vad_model = None