Is there some way to save best model only with tensorflow.estimator.train_and_evaluate()?

Question

I try retrain TF Object Detection API model from checkpoint with already .config file for training pipeline with tf.estimator.train_and_evaluate() method like in models/research

Answer 1

If you are training using the models repo of tensorflow/models. models/research/object_detection/model_lib.py file create_train_and_eval_specs function can be modified to include the best exporter:

final_exporter = tf.estimator.FinalExporter(
    name=final_exporter_name, serving_input_receiver_fn=predict_input_fn)

best_exporter = tf.estimator.BestExporter(
    name="best_exporter",
    serving_input_receiver_fn=predict_input_fn,
    event_file_pattern='eval_eval/*.tfevents.*',
    exports_to_keep=5)
exporters = [final_exporter, best_exporter]

train_spec = tf.estimator.TrainSpec(
    input_fn=train_input_fn, max_steps=train_steps)

eval_specs = [
    tf.estimator.EvalSpec(
        name=eval_spec_name,
        input_fn=eval_input_fn,
        steps=eval_steps,
        exporters=exporters)
]