Loading deepchem/trans/transformers.py +15 −17 Original line number Diff line number Diff line Loading @@ -2487,7 +2487,16 @@ class RxnSplitTransformer(Transformer): """ def __init__(self, sep_reagent: bool, dataset: Optional[Dataset] = None): def __init__(self, sep_reagent: bool = True, dataset: Optional[Dataset] = None): """Initializes the Reaction split Transformer. Parameters ---------- sep_reagent: bool, optional (default True) To separate the reagent and reactants for training. dataset: dc.data.Dataset object, optional (default None) Dataset to be transformed. """ # the transformer would have to split the source and target sequences # would also consider adding the option of separating the reagent here. Loading @@ -2497,10 +2506,10 @@ class RxnSplitTransformer(Transformer): def transform_array( self, X: np.ndarray, y: np.ndarray, w: np.ndarray, ids: np.ndarray) -> Tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray]: """Transform the data in a set of (X, y, w) arrays. """Transform the data in a set of (X, y, w, ids) arrays. Parameters ----- ---------- X: np.ndarray Array of features(the reactions) y: np.ndarray Loading Loading @@ -2540,17 +2549,6 @@ class RxnSplitTransformer(Transformer): return (X, y, w, ids) def untransform(self, z: np.ndarray) -> np.ndarray: """ Undo transformation on provided data. Parameters ---------- z: np.ndarray Array to transform back Returns ------- np.ndarray Array with normalization undone. """ # TODO return super().untransform(z) def untransform(self, z): """Not Implemented.""" raise NotImplementedError("Cannot untransform the source/target split.") Loading
deepchem/trans/transformers.py +15 −17 Original line number Diff line number Diff line Loading @@ -2487,7 +2487,16 @@ class RxnSplitTransformer(Transformer): """ def __init__(self, sep_reagent: bool, dataset: Optional[Dataset] = None): def __init__(self, sep_reagent: bool = True, dataset: Optional[Dataset] = None): """Initializes the Reaction split Transformer. Parameters ---------- sep_reagent: bool, optional (default True) To separate the reagent and reactants for training. dataset: dc.data.Dataset object, optional (default None) Dataset to be transformed. """ # the transformer would have to split the source and target sequences # would also consider adding the option of separating the reagent here. Loading @@ -2497,10 +2506,10 @@ class RxnSplitTransformer(Transformer): def transform_array( self, X: np.ndarray, y: np.ndarray, w: np.ndarray, ids: np.ndarray) -> Tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray]: """Transform the data in a set of (X, y, w) arrays. """Transform the data in a set of (X, y, w, ids) arrays. Parameters ----- ---------- X: np.ndarray Array of features(the reactions) y: np.ndarray Loading Loading @@ -2540,17 +2549,6 @@ class RxnSplitTransformer(Transformer): return (X, y, w, ids) def untransform(self, z: np.ndarray) -> np.ndarray: """ Undo transformation on provided data. Parameters ---------- z: np.ndarray Array to transform back Returns ------- np.ndarray Array with normalization undone. """ # TODO return super().untransform(z) def untransform(self, z): """Not Implemented.""" raise NotImplementedError("Cannot untransform the source/target split.")
