how to check both training/eval performances in tensorflow object_detection

问题

When I check the tensorboard for observing the training performance, there only shows the eval_0 (in blue) result.

While it should be a separate train (in orange) and eval (in blue) result as shown in the website of tensorboard (https://www.tensorflow.org/guide/summaries_and_tensorboard?).

However, I want to compare the model performance on training dataset and eval dataset.

So I checked the models/research/object_detection/model_main.py and want to know

if I I can get the precision based on the train and eval dataset by set the flag of model_dir to model/eval folder and set the flag of eval_training_data to model/train folder?

flags.DEFINE_string('model_dir', None, 'Path to output model directory '
                     'where event and checkpoint files will be written.')

flags.DEFINE_boolean('eval_training_data', False,
                     'If training data should be evaluated for this job. Note '
                     'that one call only use this in eval-only mode, and '
                     '`checkpoint_dir` must be supplied.')

And I'm confused with this sentence.

Note that one call only use this in eval-only mode, and checkpoint_dir must be supplied.

Does it means if I just want run it in eval-only mode, then I must set the checkpoint_dir? And if I want to run it with train and eval at the same time, I don't need to set the checkpoint_dir?

来源：https://stackoverflow.com/questions/53663384/how-to-check-both-training-eval-performances-in-tensorflow-object-detection