[FIX] base featurizer + [FIX] requirements to include right version of tensorflow probability

Author: jcapels

extra-requirements.txt

@@ -25,7 +25,7 @@ dgllife==0.3.2: deep-learning
 deepchem==2.8.0: deep-learning
 torch_geometric==2.6.1: deep-learning
 tensorflow==2.15.0: deep-learning
-tensorflow-probability==0.25.0: deep-learning
+tensorflow-probability==0.23.0: deep-learning
 boruta==0.4.3: preprocessing, machine-learning
 scikit-learn<1.6: machine-learning, deep-learning
 optuna==4.1.0: machine-learning, deep-learning

requirements.txt

@@ -23,7 +23,7 @@ numpy
 dgllife==0.3.2
 dill==0.3.6
 optuna==4.1.0
-tensorflow-probability==0.25.0
+tensorflow-probability==0.23.0
 torch_geometric==2.6.1
 scikit-multilearn==0.2.0
 scikeras==0.12.0

src/deepmol/compound_featurization/base_featurizer.py

@@ -98,9 +98,14 @@ def featurize(self,
 
         remove_mols_list = np.array(remove_mols)
         dataset.remove_elements(np.array(dataset.ids)[remove_mols_list], inplace=True)
-
+        
         features = np.array(features, dtype=object)
         features = features[~remove_mols_list]
+        
+        try:
+            features = features.astype('float64')
+        except:
+            pass
 
         if (isinstance(features[0], np.ndarray) and len(features[0].shape) == 2) or not isinstance(features[0],
                                                                                                    np.ndarray):