Loading deepchem/hyper/grid_search.py +5 −5 Original line number Diff line number Diff line Loading @@ -86,6 +86,11 @@ class GridHyperparamOpt(HyperparamOpt): dataset used for training valid_dataset: `dc.data.Dataset` dataset used for validation(optimization on valid scores) output_transformers: list[dc.trans.Transformer] Transformers for evaluation. This argument is needed since `train_dataset` and `valid_dataset` may have been transformed for learning and need the transform to be inverted before the metric can be evaluated on a model. metric: dc.metrics.Metric metric used for evaluation use_max: bool, optional Loading @@ -94,11 +99,6 @@ class GridHyperparamOpt(HyperparamOpt): logdir: str, optional The directory in which to store created models. If not set, will use a temporary directory. output_transformers: list[dc.trans.Transformer] Transformers for evaluation. This argument is needed since `train_dataset` and `valid_dataset` may have been transformed for learning and need the transform to be inverted before the metric can be evaluated on a model. Returns ------- Loading Loading
deepchem/hyper/grid_search.py +5 −5 Original line number Diff line number Diff line Loading @@ -86,6 +86,11 @@ class GridHyperparamOpt(HyperparamOpt): dataset used for training valid_dataset: `dc.data.Dataset` dataset used for validation(optimization on valid scores) output_transformers: list[dc.trans.Transformer] Transformers for evaluation. This argument is needed since `train_dataset` and `valid_dataset` may have been transformed for learning and need the transform to be inverted before the metric can be evaluated on a model. metric: dc.metrics.Metric metric used for evaluation use_max: bool, optional Loading @@ -94,11 +99,6 @@ class GridHyperparamOpt(HyperparamOpt): logdir: str, optional The directory in which to store created models. If not set, will use a temporary directory. output_transformers: list[dc.trans.Transformer] Transformers for evaluation. This argument is needed since `train_dataset` and `valid_dataset` may have been transformed for learning and need the transform to be inverted before the metric can be evaluated on a model. Returns ------- Loading
