create the model predictor by model config
(self)
| 102 | |
| 103 | # 预测器创建函数 |
| 104 | def eval(self): |
| 105 | ''' |
| 106 | create the model predictor by model config |
| 107 | ''' |
| 108 | # 创建预测器 |
| 109 | self.predictor = create_predictor(self.config) |
| 110 | |
| 111 | # 获取模型的输入输出名称 |
| 112 | self.input_names = self.predictor.get_input_names() |
| 113 | self.output_names = self.predictor.get_output_names() |
| 114 | |
| 115 | # 获取模型的输入输出节点数量 |
| 116 | self.input_num = len(self.input_names) |
| 117 | self.output_num = len(self.output_names) |
| 118 | |
| 119 | # 获取输入 |
| 120 | self.input_handles = [] |
| 121 | for input_name in self.input_names: |
| 122 | self.input_handles.append( |
| 123 | self.predictor.get_input_handle(input_name)) |
| 124 | |
| 125 | # 获取输出 |
| 126 | self.output_handles = [] |
| 127 | for output_name in self.output_names: |
| 128 | self.output_handles.append( |
| 129 | self.predictor.get_output_handle(output_name)) |
| 130 | |
| 131 | # 前向计算函数 |
| 132 | def forward(self, *input_datas, batch_size=1): |