Loading deepchem/molnet/load_function/uspto_datasets.py +5 −5 Original line number Diff line number Diff line Loading @@ -80,7 +80,7 @@ def load_uspto( ) -> Tuple[List[str], Tuple[Dataset, ...], List[dc.trans.Transformer]]: """Load USPTO Datasets. The USPTO dataset [1]_ consists of over 1.8 Million organic chemical reactions The USPTO dataset consists of over 1.8 Million organic chemical reactions extracted from US patents and patent applications. The dataset contains the reactions in the form of reaction SMILES, which have the general format: reactant>reagent>product. Loading @@ -92,10 +92,10 @@ def load_uspto( The 50K dataset contatins 50,000 reactions and is the benchmark for retrosynthesis predictions. The reactions are additionally classified into 10 reaction classes. The canonicalized version of the dataset used by the loader is the same as that used by Somnath et. al [2]_. is the same as that used by Somnath et. al. The loader uses the SpecifiedSplitter to use the same splits as specified by Schwaller [3]_ and Dai [4]_. Custom splitters could also be used. There by Schwaller et. al and Dai et. al. Custom splitters could also be used. There is a toggle in the loader to skip the source/target transformation needed for seq2seq tasks. There is an additional toggle to load the dataset with the reagents and reactants separated or mixed. This alters the entries in source Loading Loading
deepchem/molnet/load_function/uspto_datasets.py +5 −5 Original line number Diff line number Diff line Loading @@ -80,7 +80,7 @@ def load_uspto( ) -> Tuple[List[str], Tuple[Dataset, ...], List[dc.trans.Transformer]]: """Load USPTO Datasets. The USPTO dataset [1]_ consists of over 1.8 Million organic chemical reactions The USPTO dataset consists of over 1.8 Million organic chemical reactions extracted from US patents and patent applications. The dataset contains the reactions in the form of reaction SMILES, which have the general format: reactant>reagent>product. Loading @@ -92,10 +92,10 @@ def load_uspto( The 50K dataset contatins 50,000 reactions and is the benchmark for retrosynthesis predictions. The reactions are additionally classified into 10 reaction classes. The canonicalized version of the dataset used by the loader is the same as that used by Somnath et. al [2]_. is the same as that used by Somnath et. al. The loader uses the SpecifiedSplitter to use the same splits as specified by Schwaller [3]_ and Dai [4]_. Custom splitters could also be used. There by Schwaller et. al and Dai et. al. Custom splitters could also be used. There is a toggle in the loader to skip the source/target transformation needed for seq2seq tasks. There is an additional toggle to load the dataset with the reagents and reactants separated or mixed. This alters the entries in source Loading
