Loading deepchem/data/data_loader.py +4 −6 Original line number Diff line number Diff line Loading @@ -407,11 +407,9 @@ class CSVLoader(DataLoader): valid_inds: np.ndarray Indices of rows in source CSV with valid data. """ features = [ np.array(elt) for elt in self.featurizer(shard[self.feature_field]) ] features = [elt for elt in self.featurizer(shard[self.feature_field])] valid_inds = np.array( [1 if elt.size > 0 else 0 for elt in features], dtype=bool) [1 if np.array(elt).size > 0 else 0 for elt in features], dtype=bool) features = [ elt for (is_valid, elt) in zip(valid_inds, features) if is_valid ] Loading Loading @@ -734,9 +732,9 @@ class SDFLoader(DataLoader): def _featurize_shard(self, shard): """Featurizes a shard of an input dataframe.""" features = [np.array(elt) for elt in featurizer(shard[self.mol_field])] features = [elt for elt in featurizer(shard[self.mol_field])] valid_inds = np.array( [1 if elt.size > 0 else 0 for elt in features], dtype=bool) [1 if np.array(elt).size > 0 else 0 for elt in features], dtype=bool) features = [ elt for (is_valid, elt) in zip(valid_inds, features) if is_valid ] Loading Loading
deepchem/data/data_loader.py +4 −6 Original line number Diff line number Diff line Loading @@ -407,11 +407,9 @@ class CSVLoader(DataLoader): valid_inds: np.ndarray Indices of rows in source CSV with valid data. """ features = [ np.array(elt) for elt in self.featurizer(shard[self.feature_field]) ] features = [elt for elt in self.featurizer(shard[self.feature_field])] valid_inds = np.array( [1 if elt.size > 0 else 0 for elt in features], dtype=bool) [1 if np.array(elt).size > 0 else 0 for elt in features], dtype=bool) features = [ elt for (is_valid, elt) in zip(valid_inds, features) if is_valid ] Loading Loading @@ -734,9 +732,9 @@ class SDFLoader(DataLoader): def _featurize_shard(self, shard): """Featurizes a shard of an input dataframe.""" features = [np.array(elt) for elt in featurizer(shard[self.mol_field])] features = [elt for elt in featurizer(shard[self.mol_field])] valid_inds = np.array( [1 if elt.size > 0 else 0 for elt in features], dtype=bool) [1 if np.array(elt).size > 0 else 0 for elt in features], dtype=bool) features = [ elt for (is_valid, elt) in zip(valid_inds, features) if is_valid ] Loading
