From 9ba0dbd98bf69c830dfcfde8f109a400cb65e4e5 Mon Sep 17 00:00:00 2001 From: 雾聪 <wucong.lyb@alibaba-inc.com> Date: 星期五, 29 三月 2024 17:24:59 +0800 Subject: [PATCH] fix func Forward --- runtime/python/onnxruntime/funasr_onnx/vad_bin.py | 24 ++++++++++++------------ 1 files changed, 12 insertions(+), 12 deletions(-) diff --git a/runtime/python/onnxruntime/funasr_onnx/vad_bin.py b/runtime/python/onnxruntime/funasr_onnx/vad_bin.py index af32b1d..6b3a1bc 100644 --- a/runtime/python/onnxruntime/funasr_onnx/vad_bin.py +++ b/runtime/python/onnxruntime/funasr_onnx/vad_bin.py @@ -61,10 +61,10 @@ "For the users in China, you could install with the command:\n" \ "\npip3 install -U funasr -i https://mirror.sjtu.edu.cn/pypi/web/simple" - model = AutoModel(model=cache_dir) - model_dir = model.export(type="onnx", quantize=quantize, device="cpu") - config_file = os.path.join(model_dir, 'vad.yaml') - cmvn_file = os.path.join(model_dir, 'vad.mvn') + model = AutoModel(model=model_dir) + model_dir = model.export(type="onnx", quantize=quantize) + config_file = os.path.join(model_dir, 'config.yaml') + cmvn_file = os.path.join(model_dir, 'am.mvn') config = read_yaml(config_file) self.frontend = WavFrontend( @@ -73,8 +73,8 @@ ) 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 if max_end_sil is not None else config["vad_post_conf"]["max_end_silence_time"] + self.vad_scorer = E2EVadModel(config["model_conf"]) + self.max_end_sil = max_end_sil if max_end_sil is not None else config["model_conf"]["max_end_silence_time"] self.encoder_conf = config["encoder_conf"] def prepare_cache(self, in_cache: list = []): @@ -225,11 +225,11 @@ "For the users in China, you could install with the command:\n" \ "\npip3 install -U funasr -i https://mirror.sjtu.edu.cn/pypi/web/simple" - model = AutoModel(model=cache_dir) - model_dir = model.export(type="onnx", quantize=quantize, device="cpu") + model = AutoModel(model=model_dir) + model_dir = model.export(type="onnx", quantize=quantize) - config_file = os.path.join(model_dir, 'vad.yaml') - cmvn_file = os.path.join(model_dir, 'vad.mvn') + config_file = os.path.join(model_dir, 'config.yaml') + cmvn_file = os.path.join(model_dir, 'am.mvn') config = read_yaml(config_file) self.frontend = WavFrontendOnline( @@ -238,8 +238,8 @@ ) 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 if max_end_sil is not None else config["vad_post_conf"]["max_end_silence_time"] + self.vad_scorer = E2EVadModel(config["model_conf"]) + self.max_end_sil = max_end_sil if max_end_sil is not None else config["model_conf"]["max_end_silence_time"] self.encoder_conf = config["encoder_conf"] def prepare_cache(self, in_cache: list = []): -- Gitblit v1.9.1