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游雁 2023-03-29 00:42:32 +08:00
parent 242431452b
commit cf00b4a13f
1 changed files with 8 additions and 5 deletions
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13
funasr/runtime/python/onnxruntime/funasr_onnx/vad_bin.py
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@ -23,7 +23,7 @@ class Fsmn_vad():
device_id: Union[str, int] = "-1", device_id: Union[str, int] = "-1",
quantize: bool = False, quantize: bool = False,
intra_op_num_threads: int = 4, intra_op_num_threads: int = 4,
max_end_sil: int = 800, max_end_sil: int = None,
): ):
if not Path(model_dir).exists(): if not Path(model_dir).exists():
@ -43,14 +43,17 @@ class Fsmn_vad():
self.ort_infer = OrtInferSession(model_file, device_id, intra_op_num_threads=intra_op_num_threads) self.ort_infer = OrtInferSession(model_file, device_id, intra_op_num_threads=intra_op_num_threads)
self.batch_size = batch_size self.batch_size = batch_size
self.vad_scorer = E2EVadModel(config["vad_post_conf"]) self.vad_scorer = E2EVadModel(config["vad_post_conf"])
self.max_end_sil = max_end_sil self.max_end_sil = max_end_sil if max_end_sil is not None else config["vad_post_conf"]["max_end_silence_time"]
self.encoder_conf = config["encoder_conf"]
def prepare_cache(self, in_cache: list = []): def prepare_cache(self, in_cache: list = []):
if len(in_cache) > 0: if len(in_cache) > 0:
return in_cache return in_cache
fsmn_layers = self.encoder_conf["fsmn_layers"]
for i in range(4): proj_dim = self.encoder_conf["proj_dim"]
cache = np.random.rand(1, 128, 19, 1).astype(np.float32) lorder = self.encoder_conf["lorder"]
for i in range(fsmn_layers):
cache = np.random.rand(1, proj_dim, lorder-1, 1).astype(np.float32)
in_cache.append(cache) in_cache.append(cache)
return in_cache return in_cache