(L_in,L_out)
| 189 | |
| 190 | # 随机初始化权重theta |
| 191 | def randInitializeWeights(L_in,L_out): |
| 192 | W = np.zeros((L_out,1+L_in)) # 对应theta的权重 |
| 193 | epsilon_init = (6.0/(L_out+L_in))**0.5 |
| 194 | W = np.random.rand(L_out,1+L_in)*2*epsilon_init-epsilon_init # np.random.rand(L_out,1+L_in)产生L_out*(1+L_in)大小的随机矩阵 |
| 195 | return W |
| 196 | |
| 197 | |
| 198 | # 检验梯度是否计算正确 |