tensorflow2.0——callback将每个epoch的loss保存

class LossHistory(keras.callbacks.Callback):
    def on_train_begin(self, logs={}):
        self.losses = []

    def on_batch_end(self, batch, logs={}):
        pass
        # self.losses.append(logs.get('loss'))
        # print('callback调用！！！！！！！！！')

    def on_epoch_end(self, epoch, logs=None):
        # self.losses.append(logs.get('loss'))
        print_loss = logs.get('loss')
        val_loss = logs.get('val_loss')
        print('\ncallback调用！！！！！！！！！\nloss:{}'.format(print_loss))
        print_loss = str(print_loss)
        val_loss =str(val_loss)
        with open(log_path,'a+') as f:
            f.write(print_loss+'\t'+val_loss)
            f.write('\n')

history2 = LossHistory()

history=my_model.fit(train_high0_img,train_rain,validation_data=(test_high0_img,test_rain),epochs=epochs, validation_freq=1,batch_size=bat,callbacks=[history2])