TensorFlow Version: 1.15.4
Keras in TensorFlow:2.2.4-tf
I’m training a keras model using fit and 4 callbacks, Here is code:
mode = 'max'
verbose = 1
ckpt_name = os.path.join(
    self.context.ckpt_path, "{epoch:03d}-{%s:.4f}.h5" % monitor_name)
callbacks_list = [
    LogCallback(log_batch_num=self.context.metric_size),
    ReduceLROnPlateau(monitor=monitor_name,
                        factor=self.context.lr_decay_factor,
                        patience=self.context.lr_decay_step,
                        cooldown=1,
                        verbose=verbose,
                        min_lr=0.0001),
    TensorBoard(log_dir=self.context.tensorboard_path, write_graph=False),
    ModelCheckpoint(ckpt_name,
                    monitor=monitor_name,
                    verbose=verbose,
                    save_best_only=True,
                    save_weights_only=True,
                    mode=mode),
    EarlyStopping(monitor=monitor_name,
                    min_delta=self.context.min_delta,
                    patience=self.context.patience,
                    verbose=verbose,
                    mode=mode,
                    baseline=self.context.base_metric,
                    restore_best_weights=True)
]

It will cause the Error

image956×326 22.5 KB

I think maybe OutOfData->Train stop->Save model->Metric not available->metric not in Logs->_get_file_path Error
I want to know how to fix it, make the training stop and save model ok even if Out of Data?