From cf00b4a13f5fdedda19c3cae214943fc28df52ac Mon Sep 17 00:00:00 2001 From: 游雁 <zhifu.gzf@alibaba-inc.com> Date: 星期三, 29 三月 2023 00:42:32 +0800 Subject: [PATCH] export --- funasr/runtime/python/onnxruntime/funasr_onnx/vad_bin.py | 13 ++++++++----- 1 files changed, 8 insertions(+), 5 deletions(-) diff --git a/funasr/runtime/python/onnxruntime/funasr_onnx/vad_bin.py b/funasr/runtime/python/onnxruntime/funasr_onnx/vad_bin.py index 533b4b7..9568ac9 100644 --- a/funasr/runtime/python/onnxruntime/funasr_onnx/vad_bin.py +++ b/funasr/runtime/python/onnxruntime/funasr_onnx/vad_bin.py @@ -23,7 +23,7 @@ device_id: Union[str, int] = "-1", quantize: bool = False, intra_op_num_threads: int = 4, - max_end_sil: int = 800, + max_end_sil: int = None, ): if not Path(model_dir).exists(): @@ -43,14 +43,17 @@ self.ort_infer = OrtInferSession(model_file, device_id, intra_op_num_threads=intra_op_num_threads) self.batch_size = batch_size 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 = []): if len(in_cache) > 0: return in_cache - - for i in range(4): - cache = np.random.rand(1, 128, 19, 1).astype(np.float32) + fsmn_layers = self.encoder_conf["fsmn_layers"] + proj_dim = self.encoder_conf["proj_dim"] + 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) return in_cache -- Gitblit v1.9.1