()
| 246 | |
| 247 | #-------------MAIN------------------------- |
| 248 | def main(): |
| 249 | global current_loss |
| 250 | data = cp.creat_data(800) #生成数据 |
| 251 | cp.plot_data(data, "Right classification") |
| 252 | |
| 253 | #选择起始网络 |
| 254 | use_this_network = 'n' #No |
| 255 | while use_this_network != 'Y' and use_this_network != 'y': |
| 256 | network = Network(NETWORK_SHAPE) |
| 257 | inputs = data[:, (0, 1)] |
| 258 | outputs = network.network_forward(inputs) |
| 259 | classification = classify(outputs[-1]) |
| 260 | data[:, 2] = classification |
| 261 | cp.plot_data(data, "Choose network") |
| 262 | use_this_network = input("Use this network? Y to yes, N to No \n") |
| 263 | |
| 264 | #进行训练 |
| 265 | do_train = input("Train? Y to yes, N to No \n") |
| 266 | while do_train == 'Y' or do_train == 'y' or do_train.isnumeric() == True: |
| 267 | if do_train.isnumeric() == True: |
| 268 | n_entries = int(do_train) |
| 269 | else: |
| 270 | n_entries = int(input("Enter the number of data entries used to train. \n")) |
| 271 | |
| 272 | network.train(n_entries) |
| 273 | do_train = input("Train? Y to yes, N to No \n") |
| 274 | |
| 275 | #演示训练效果 |
| 276 | inputs = data[:, (0, 1)] |
| 277 | outputs = network.network_forward(inputs) |
| 278 | classification = classify(outputs[-1]) |
| 279 | data[:, 2] = classification |
| 280 | cp.plot_data(data, "After training") |
| 281 | print("谢谢,再见!") |
| 282 | #----------------TEST------------------------- |
| 283 | def test(): |
| 284 | pass |
no test coverage detected