()
| 102 | |
| 103 | |
| 104 | def run_model(): |
| 105 | |
| 106 | ### set model |
| 107 | with strategy.scope(): |
| 108 | # Everything that creates variables should be under the strategy scope. |
| 109 | # In general this is only model construction & `compile()`. |
| 110 | model = get_compiled_model() |
| 111 | |
| 112 | ### Set train steps and validation steps |
| 113 | train_steps = len(train_generator.labels)/ batch_size |
| 114 | val_steps = len(validation_generator.labels) / batch_size |
| 115 | |
| 116 | #### set the path to save models having lowest validation loss during training |
| 117 | save_model_dir = './models/' |
| 118 | if not os.path.exists(save_model_dir): |
| 119 | os.mkdir(save_model_dir) |
| 120 | filepath= "models/acl-"+args.structure+"-fold" + str(i+1) + "-" + database + "-" + args.model_name + "-" + str(image_size) + "-" + str(batch_size) + "-"+str(args.lr)+ ".h5" |
| 121 | |
| 122 | |
| 123 | checkpoint = ModelCheckpoint(filepath, monitor='val_loss', verbose=1, save_best_only=True, mode='min') |
| 124 | history = model.fit_generator( |
| 125 | train_generator, |
| 126 | epochs=num_epoches, |
| 127 | steps_per_epoch=train_steps, |
| 128 | validation_data=validation_generator, |
| 129 | validation_steps=val_steps, |
| 130 | use_multiprocessing=True, |
| 131 | workers=10, |
| 132 | callbacks=[checkpoint]) |
| 133 | ### Save training loss |
| 134 | train_auc = history.history['auc'] |
| 135 | val_auc = history.history['val_auc'] |
| 136 | train_loss = history.history['loss'] |
| 137 | val_loss = history.history['val_loss'] |
| 138 | d_loss = pd.DataFrame({'train_auc':train_auc, 'val_auc':val_auc, 'train_loss':train_loss, 'val_loss':val_loss}) |
| 139 | save_loss_dir = './loss' |
| 140 | if not os.path.exists(save_loss_dir): |
| 141 | os.mkdir(save_loss_dir) |
| 142 | d_loss.to_csv("loss/acl-"+args.structure+"-fold" + str(i+1) + "-" + database + "-" + args.model_name + "-" + str(image_size) + "-" + str(batch_size) + "-"+str(args.lr)+ ".csv", index=False) |
| 143 | |
| 144 | |
| 145 |
no test coverage detected