Keras自定义回调:网格点训练终止条件

from keras.callbacks import Callback

class GridSearchTermination(Callback):
    def __init__(self, target_metric, target_value):
        super(GridSearchTermination, self).__init__()
        self.target_metric = target_metric
        self.target_value = target_value

    def on_epoch_end(self, epoch, logs=None):
        current_value = logs.get(self.target_metric)
        if current_value is not None and current_value >= self.target_value:
            self.model.stop_training = True
            print("Grid search terminated. Target metric reached.")

# 使用示例
grid_search_termination = GridSearchTermination(target_metric='val_loss', target_value=0.1)
model.fit(x_train, y_train, validation_data=(x_val, y_val), callbacks=[grid_search_termination])