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How to integrate mlflow with tensorflow object detection api

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.

The mlflow autologging will log whatever metrics are specified for the keras model, eg 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?

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