chatted with kyle and made change so that this patch does not break p…

…rediction

chemprop/data/utils.py

@@ -111,7 +111,8 @@ def get_data(path: str,
              features_generator: List[str] = None,
              max_data_size: int = None,
              store_row: bool = False,
-             logger: Logger = None) -> MoleculeDataset:
+             logger: Logger = None,
+             skip_none_targets: bool = False) -> MoleculeDataset:
     """
     Gets SMILES and target values from a CSV file.
 
@@ -129,6 +130,8 @@ def get_data(path: str,
     :param max_data_size: The maximum number of data points to load.
     :param logger: A logger for recording output.
     :param store_row: Whether to store the raw CSV row in each :class:`~chemprop.data.data.MoleculeDatapoint`.
+    :param skip_none_targets: Whether to skip targets that are all 'None'. This is mostly relevant when --target_columns
+                              are passed in, so only a subset of tasks are examined.
     :return: A :class:`~chemprop.data.MoleculeDataset` containing SMILES and target values along
              with other info such as additional features when desired.
     """
@@ -179,8 +182,8 @@ def get_data(path: str,
 
             targets = [float(row[column]) if row[column] != '' else None for column in target_columns]
 
-            # Check whether all targets are None -- this is relevant when specifying target_columns
-            if all(x is None for x in targets):
+            if skip_none_targets and all(x is None for x in targets):
+            # Check whether all targets are None and skip if so
                 continue
 
             all_smiles.append(smiles)

chemprop/train/run_training.py

@@ -51,7 +51,7 @@ def run_training(args: TrainArgs, logger: Logger = None) -> List[float]:
 
     # Get data
     debug('Loading data')
-    data = get_data(path=args.data_path, args=args, logger=logger)
+    data = get_data(path=args.data_path, args=args, logger=logger, skip_none_targets=True)
     validate_dataset_type(data, dataset_type=args.dataset_type)
     args.features_size = data.features_size()
     debug(f'Number of tasks = {args.num_tasks}')