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pythontensorflowkerasobject-detectionyolo

what exactly is the difference between warning and error in jupyter notebook?

I am following an instruction in github (https://github.com/experiencor/keras-yolo3) to learn object detection by YOLO-3. after running code below:

!python train.py -c config.json

I received several messages in the output, and I am trying to understand what each meanS.

One of them is as below:

WARNING:tensorflow:From train.py:26: The name tf.keras.backend.set_session is deprecated. Please use tf.compat.v1.keras.backend.set_session instead.

  1. Is that, do I have to fix the meantion part of code (tf.keras.backend.set_session) since it is "deprecated" as said here?

  2. How does a warning generally, and specifically this warning may effect my final model if not to be fixed?

Solution

  • Answer one : long story short, a deprecated function is an old one, replaced by something (hopefully) better, and still there for retro-compatibility. You can use it but will not get the latest development/support and, at some point, your code will not be functional anymore (since the faith of a deprecated function is to disappear in a future release).

    Answer two :

    Warning messages are typically issued in situations where it is useful to alert the user of some condition in a program, where that condition (normally) doesn’t warrant raising an exception and terminating the program. For example, one might want to issue a warning when a program uses an obsolete module.

    https://docs.python.org/3/library/warnings.html

    All in all, here, the interpreter just warms you that you are using a function that you will not be able to use in the future.