make_predict_function() changed to non-private version in training:102,...

make_predict_function() changed to non-private version in training:102, abstract_model_class:134+ disabled __compare_keras_optimizers and rewrite empty lists with None

mlair/model_modules/abstract_model_class.py

@@ -139,6 +139,8 @@ class AbstractModelClass(ABC):
         for allow_k in self.__allowed_compile_options.keys():
             if hasattr(self, allow_k):
                 new_v_attr = getattr(self, allow_k)
+                if new_v_attr == list():
+                    new_v_attr = None
             else:
                 new_v_attr = None
             if isinstance(value, dict):
@@ -147,8 +149,10 @@ class AbstractModelClass(ABC):
                 new_v_dic = None
             else:
                 raise TypeError(f"`compile_options' must be `dict' or `None', but is {type(value)}.")
-            if (new_v_attr == new_v_dic or self.__compare_keras_optimizers(new_v_attr, new_v_dic)) or (
-                    (new_v_attr is None) ^ (new_v_dic is None)):
+            ## self.__compare_keras_optimizers() foremost disabled, because it does not work as expected
+            #if (new_v_attr == new_v_dic or self.__compare_keras_optimizers(new_v_attr, new_v_dic)) or (
+            #        (new_v_attr is None) ^ (new_v_dic is None)):
+            if (new_v_attr == new_v_dic) or ((new_v_attr is None) ^ (new_v_dic is None)):
                 if new_v_attr is not None:
                     self.__compile_options[allow_k] = new_v_attr
                 else:
@@ -171,7 +175,11 @@ class AbstractModelClass(ABC):
 
         :return True if optimisers are interchangeable, or False if optimisers are distinguishable.
         """
-        if first.__class__ == second.__class__ and first.__module__ == 'keras.optimizers':
+        if isinstance(list, type(second)):
+            res = False
+        else:
+            if first.__class__ == second.__class__ and '.'.join(
+                    first.__module__.split('.')[0:4]) == 'tensorflow.python.keras.optimizer_v2':
                 res = True
                 init = tf.compat.v1.global_variables_initializer()
                 with tf.compat.v1.Session() as sess:

mlair/run_modules/training.py

@@ -99,7 +99,7 @@ class Training(RunEnvironment):
         workers. To prevent this, the function is pre-compiled. See discussion @
         https://stackoverflow.com/questions/40850089/is-keras-thread-safe/43393252#43393252
         """
-        self.model._make_predict_function()
+        self.model.make_predict_function()
 
     def _set_gen(self, mode: str) -> None:
         """