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Hi There :)
Can Anybody Tell Me What The Best Practice Is For Performing A Normalization In The Preprocess.Py Script Used By Clearml-Serving? Currently I Use A Sklearn Minmaxscaler Which Is Loaded And Applied Before And After The Data Is Send To The Model
Yes! I checked it should work (it checks if you have load(...) function on the preprocess class and if you do it will use it:
None
def load(local_file)
self._model = joblib.load(local_file_name)
self._preprocess_model = joblib.load(Model(hard_coded_model_id).get_weights())
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one year ago
one year ago