(self,back_units)
| 48 | self.is_input_layer = is_input_layer |
| 49 | |
| 50 | def initializer(self,back_units): |
| 51 | self.weight = np.asmatrix(np.random.normal(0,0.5,(self.units,back_units))) |
| 52 | self.bias = np.asmatrix(np.random.normal(0,0.5,self.units)).T |
| 53 | if self.activation is None: |
| 54 | self.activation = sigmoid |
| 55 | |
| 56 | def cal_gradient(self): |
| 57 | if self.activation == sigmoid: |