Loading deepchem/trans/transformers.py +6 −4 Original line number Diff line number Diff line Loading @@ -1083,14 +1083,16 @@ class FlatteningTransformer(Transformer): Transformed array of ids """ ids = np.repeat( ids, [len(i) for i in X], axis=0) # each fragment should recieve parent mol id ids, [len(i) for i in X], axis=0) # each fragment should recieve parent mol id if self.transform_y: y = np.repeat( y, [len(i) for i in X], axis=0) # for consistency of shapes each fragment should recieve parent mol y y, [len(i) for i in X], axis=0 ) # for consistency of shapes each fragment should recieve parent mol y if self.transform_w: w = np.repeat( w, [len(i) for i in X], axis=0) # for consistency of shapes each fragment should recieve parent mol w w, [len(i) for i in X], axis=0 ) # for consistency of shapes each fragment should recieve parent mol w X = np.array([j for i in X for j in i]) # flatten return (X, y, w, ids) Loading Loading
deepchem/trans/transformers.py +6 −4 Original line number Diff line number Diff line Loading @@ -1083,14 +1083,16 @@ class FlatteningTransformer(Transformer): Transformed array of ids """ ids = np.repeat( ids, [len(i) for i in X], axis=0) # each fragment should recieve parent mol id ids, [len(i) for i in X], axis=0) # each fragment should recieve parent mol id if self.transform_y: y = np.repeat( y, [len(i) for i in X], axis=0) # for consistency of shapes each fragment should recieve parent mol y y, [len(i) for i in X], axis=0 ) # for consistency of shapes each fragment should recieve parent mol y if self.transform_w: w = np.repeat( w, [len(i) for i in X], axis=0) # for consistency of shapes each fragment should recieve parent mol w w, [len(i) for i in X], axis=0 ) # for consistency of shapes each fragment should recieve parent mol w X = np.array([j for i in X for j in i]) # flatten return (X, y, w, ids) Loading
