clean up logic in load_datasets

src/fairchem/core/trainers/base_trainer.py

@@ -159,10 +159,10 @@ def __init__(
             if len(dataset) > 2:
                 self.config["test_dataset"] = dataset[2]
         elif isinstance(dataset, dict):
-            self.config["dataset"] = dataset.get("train", None)
-            self.config["val_dataset"] = dataset.get("val", None)
-            self.config["test_dataset"] = dataset.get("test", None)
-            self.config["relax_dataset"] = dataset.get("relax", None)
+            self.config["dataset"] = dataset.get("train", {})
+            self.config["val_dataset"] = dataset.get("val", {})
+            self.config["test_dataset"] = dataset.get("test", {})
+            self.config["relax_dataset"] = dataset.get("relax", {})
         else:
             self.config["dataset"] = dataset
 
@@ -277,8 +277,19 @@ def load_datasets(self) -> None:
         self.val_loader = None
         self.test_loader = None
 
+        # Default all of the dataset portions to {} if
+        # they don't exist, or are null
+        if self.config.get("dataset", None):
+            self.config["dataset"] = {}
+        if self.config.get("val_dataset", None):
+            self.config["val_dataset"] = {}
+        if self.config.get("test_dataset", None):
+            self.config["test_dataset"] = {}
+        if self.config.get("relax_dataset", None):
+            self.config["relax_dataset"] = {}
+
         # load train, val, test datasets
-        if self.config.get("dataset", None) and self.config["dataset"].get("src", None):
+        if self.config["dataset"] and self.config["dataset"].get("src", None):
             logging.info(
                 f"Loading dataset: {self.config['dataset'].get('format', 'lmdb')}"
             )
@@ -295,10 +306,8 @@ def load_datasets(self) -> None:
                 self.train_dataset,
                 self.train_sampler,
             )
-        elif self.config.get("dataset", None) is None:
-            self.config["dataset"] = {}
 
-        if self.config.get("val_dataset", None):
+        if self.config.get["val_dataset"]:
             if self.config["val_dataset"].get("use_train_settings", True):
                 val_config = self.config["dataset"].copy()
                 val_config.update(self.config["val_dataset"])
@@ -319,10 +328,8 @@ def load_datasets(self) -> None:
                 self.val_dataset,
                 self.val_sampler,
             )
-        else:
-            self.config["val_dataset"] = {}
 
-        if self.config.get("test_dataset", None):
+        if self.config["test_dataset"]:
             if (
                 self.config["test_dataset"].get("use_train_settings", True)
                 and self.config[
@@ -348,10 +355,8 @@ def load_datasets(self) -> None:
                 self.test_dataset,
                 self.test_sampler,
             )
-        else:
-            self.config["test_dataset"] = {}
 
-        if self.config.get("relax_dataset", None):
+        if self.config["relax_dataset"]:
             if self.config["relax_dataset"].get("use_train_settings", True):
                 relax_config = self.config["dataset"].copy()
                 relax_config.update(self.config["relax_dataset"])
@@ -371,7 +376,7 @@ def load_datasets(self) -> None:
             self.relax_loader = self.get_dataloader(
                 self.relax_dataset,
                 self.relax_sampler,
-                )
+            )
 
     def load_task(self):
         # Normalizer for the dataset.