How to integrate mlflow with tensorflow object detection api

Question

I am trying to use the mlflow.tensorflow.autolog() with tensorflow object detection api. Adding mlflow.tensorflow.autolog() to model_main.py logs some parameters like global_norm/clipped_gradient_norm,global_norm/gradient_norm,global_step/sec,learning_rate_1,loss_1,loss_2 in mlflow. However the more important metrics like map,precision,recall are not being logged in mlfow.

Answer 1

The mlflow autologging will log whatever metrics are specified for the keras model, e.g. as in https://keras.io/metrics/ and https://github.com/mlflow/mlflow/blob/master/examples/keras/train.py#L66. Are those metrics specified but not logged?