From 8da8917e3b70f73d6e40892cdca31b1d3ce46121 Mon Sep 17 00:00:00 2001 From: xujiao Date: Tue, 8 Jul 2025 10:10:11 +0800 Subject: [PATCH] fixed some error --- netrans_py/netrans.py | 70 ++++++++++++++++++++++--------------------- 1 file changed, 36 insertions(+), 34 deletions(-) diff --git a/netrans_py/netrans.py b/netrans_py/netrans.py index 2af43c8..33ed415 100644 --- a/netrans_py/netrans.py +++ b/netrans_py/netrans.py @@ -36,7 +36,7 @@ class Netrans(): raise FileNotFoundError(f"Directory not found: {model_path}") self.model_path = os.path.abspath(model_path) self.model_name = os.path.basename(self.model_path) - self.set_netrans(netrans) + self._set_netrans_path(netrans) def model2nbg(self, quantize_type, inputmeta=False, **kargs): """ @@ -53,7 +53,7 @@ class Netrans(): self.export(**kargs) - def get_os_netrans_path(self): + def _get_os_netrans_path(self): """ 获取系统环境变量中的 NETRANS_PATH。 @@ -62,9 +62,10 @@ class Netrans(): """ return os.environ.get('NETRANS_PATH') - def set_netrans(self, netrans_path=None): + def _set_netrans_path(self, netrans_path=None): """ 设置 Netrans 路径。 + 如果未设置环境变量 NETRANS_PATH，则可以通过此参数指定。 Args: netrans_path (str, optional): 如果未设置环境变量 NETRANS_PATH，则可以通过此参数指定。 @@ -72,7 +73,7 @@ class Netrans(): if netrans_path is not None : netrans_path = os.path.abspath(netrans_path) else : - netrans_path = self.get_os_netrans_path() + netrans_path = self._get_os_netrans_path() if not os.path.exists(netrans_path): raise FileExistsError('未找到 Netrans 路径，请设置 NETRANS_PATH 或指定 netrans_path 参数') self.netrans = os.path.join(netrans_path, 'pnnacc') @@ -80,7 +81,11 @@ class Netrans(): def config(self, inputmeta=False, **kwargs): """ - 配置模型转换参数 + 用户处理inputmate的入口,和shell一致所以叫config. + 根据用户的实际场景,设置inputmeta参数swith对应的分支 + False: 生成inputmeta + True:使用原本的inputmeta + str:使用指定的inputmeta Args: inputmeta (bool or str, optional): 是否更新模型转换配置参数。 @@ -96,27 +101,18 @@ class Netrans(): self.input_meta = inputmeta elif isinstance(inputmeta, bool): if inputmeta is False : - self.inputmeta_gen() + self._config_gen_inputmeta_file() else : raise ValueError("inputmeta 参数无效，请设置为 False 或指定配置文件路径") if not os.path.exists(self.input_meta): raise FileExistsError(f"未找到配置文件: {self.input_meta}") if kwargs: - self.update_config(**kwargs) - # if len(kargs) == 0 : return - # if kargs['mean']==0 and kargs['scale'] ==1 : return - # if isinstance(kargs['mean'], list) or isinstance(kargs['scale'], (int, float)) or isinstance(kargs['reverse_channel'], bool): - # with open(self.input_meta,'r') as f : - # yaml = YAML() - # data = yaml.load(f) - # data = self.upload_cfg(data ,**kargs) - # with open(self.input_meta,'w') as f : - # yaml = YAML() - # yaml.dump(data, f) + self._update_config(**kwargs) - def update_config(self, **kwargs): + def _update_config(self, **kwargs): """ - 更新配置文件中的参数。 + 如果用户通过kwargs[配置预处理参数,则调用该函数更新配置文件中的参数。 + 包括文件读写和更新 Args: kwargs (dict): 包含需要更新的参数，如 mean、scale、reverse_channel 等。 @@ -124,12 +120,12 @@ class Netrans(): with open(self.input_meta, 'r') as f: yaml = YAML() data = yaml.load(f) - data = self.upload_cfg(data, **kwargs) + data = self._update_config_data(data, **kwargs) with open(self.input_meta, 'w') as f: yaml.dump(data, f) - def upload_cfg(self, data, **kwargs): + def _update_config_data(self, data, **kwargs): """ 更新配置文件中的参数。 @@ -139,17 +135,17 @@ class Netrans(): """ grey = data['input_meta']['databases'][0]['ports'][0]['preprocess']['preproc_node_params'] == 'IMAGE_GRAY' if 'mean' in kwargs: - mean = self.handle_param(kwargs['mean'], grey) - data = self.upload_cfg_mean(data, mean) + mean = self._format_preprocess_param(kwargs['mean'], grey) + data = self._upload_config_mean(data, mean) if 'scale' in kwargs: - scale = self.handle_param(kwargs['scale'], grey) - data = self.upload_cfg_scale(data, scale) + scale = self._format_preprocess_param(kwargs['scale'], grey) + data = self._upload_config_scale(data, scale) if 'reverse_channel' in kwargs: - data = self.upload_cfg_reverse_channel(data, kwargs['reverse_channel']) + data = self._upload_config_reverse_channel(data, kwargs['reverse_channel']) return data - def upload_cfg_mean(self, data, mean): + def _upload_config_mean(self, data, mean): """ 更新配置文件中的mean值 @@ -160,7 +156,7 @@ class Netrans(): for db in data['input_meta']['databases']: db['ports'][0]['preprocess']['mean'] = mean return data - def upload_cfg_scale(self, data, scale): + def _upload_config_scale(self, data, scale): """ scale @@ -172,7 +168,7 @@ class Netrans(): db['ports'][0]['preprocess']['scale'] = scale return data - def upload_cfg_reverse_channel(self, data, reverse_channel): + def _upload_config_reverse_channel(self, data, reverse_channel): """ 更新配置文件中的reverse_channel @@ -184,8 +180,12 @@ class Netrans(): db['ports'][0]['preprocess']['reverse_channel'] = reverse_channel return data - def handle_param(self, param, grey=False): + def _format_preprocess_param(self, param, grey=False): """ + 用于 update model config. + 在模型预处理参数更新的时候,灰度图像仅有一个C,而RGB图像存在三个 channel, + 因此,用户输入的 scale 和 mean 为一个值的时候,需要将其转换成列表 + 同时根据图像类型调整为 list.length() == channel 处理参数，根据图像类型调整参数格式。 Args: @@ -199,7 +199,7 @@ class Netrans(): return param return param if isinstance(param, list) else [param] * 3 - def read_input_meta_data(self): + def _verify_preprocess_value(self): """单元测试中用于判断是否成功修改配置文件中的参数 Returns: @@ -223,7 +223,7 @@ class Netrans(): func = ImportModel(self) func.import_network() - def inputmeta_gen(self): + def _config_gen_inputmeta_file(self): """ 自动生成配置文件 """ @@ -240,7 +240,9 @@ class Netrans(): Raises: TypeError: 仅支持量化成 uint8, int8, int16 """ - if quantize_type not in ['unit8', 'int8', 'int16']: + if quantize_type not in ['uint8', 'int8', 'int16']: + print(quantize_type) + print(type(quantize_type)) raise TypeError(f"不支持的量化类型: {quantize_type}，仅支持 uint8, int8, int16") self.quantize_type = quantize_type Quantize(self).quantize_network() @@ -260,5 +262,5 @@ class Netrans(): if __name__ == '__main__': network = '../../model_zoo/yolov4_tiny' yolo = Netrans(network) - yolo.inputmeta_gen() + yolo._config_gen_inputmeta_file() yolo.model2nbg("uint8") \ No newline at end of file