Style fix for Dataloader

dspy/datasets/dataloader.py

@@ -10,9 +10,7 @@
 
 
 class DataLoader(Dataset):
-    def __init__(
-        self,
-    ):
+    def __init__(self):
         pass
 
     def from_huggingface(
@@ -97,8 +95,7 @@ def from_parquet(self, file_path: str, fields: List[str] = None, input_keys: Tup
 
         return [dspy.Example({field: row[field] for field in fields}).with_inputs(input_keys) for row in dataset]
 
-    def from_rm(self, num_samples: int,
-                fields: List[str], input_keys: List[str]) -> List[dspy.Example]:
+    def from_rm(self, num_samples: int, fields: List[str], input_keys: List[str]) -> List[dspy.Example]:
         try:
             rm = dspy.settings.rm
             try:
@@ -107,9 +104,13 @@ def from_rm(self, num_samples: int,
                     for row in rm.get_objects(num_samples=num_samples, fields=fields)
                 ]
             except AttributeError:
-                raise ValueError("Retrieval module does not support `get_objects`. Please use a different retrieval module.")
+                raise ValueError(
+                    "Retrieval module does not support `get_objects`. Please use a different retrieval module."
+                )
         except AttributeError:
-            raise ValueError("Retrieval module not found. Please set a retrieval module using `dspy.settings.configure`.")
+            raise ValueError(
+                "Retrieval module not found. Please set a retrieval module using `dspy.settings.configure`."
+            )
 
     def sample(
         self,
@@ -119,7 +120,9 @@ def sample(
         **kwargs,
     ) -> List[dspy.Example]:
         if not isinstance(dataset, list):
-            raise ValueError(f"Invalid dataset provided of type {type(dataset)}. Please provide a list of examples.")
+            raise ValueError(
+                f"Invalid dataset provided of type {type(dataset)}. Please provide a list of `dspy.Example`s."
+            )
 
         return random.sample(dataset, n, *args, **kwargs)
 
@@ -141,17 +144,28 @@ def train_test_split(
         elif train_size is not None and isinstance(train_size, int):
             train_end = train_size
         else:
-            raise ValueError("Invalid train_size. Please provide a float between 0 and 1 or an int.")
+            raise ValueError(
+                "Invalid `train_size`. Please provide a float between 0 and 1 to represent the proportion of the "
+                "dataset to include in the train split or an int to represent the absolute number of samples to "
+                f"include in the train split. Received `train_size`: {train_size}."
+            )
 
         if test_size is not None:
             if isinstance(test_size, float) and (0 < test_size < 1):
                 test_end = int(len(dataset_shuffled) * test_size)
             elif isinstance(test_size, int):
                 test_end = test_size
             else:
-                raise ValueError("Invalid test_size. Please provide a float between 0 and 1 or an int.")
+                raise ValueError(
+                    "Invalid `test_size`. Please provide a float between 0 and 1 to represent the proportion of the "
+                    "dataset to include in the test split or an int to represent the absolute number of samples to "
+                    f"include in the test split. Received `test_size`: {test_size}."
+                )
             if train_end + test_end > len(dataset_shuffled):
-                raise ValueError("train_size + test_size cannot exceed the total number of samples.")
+                raise ValueError(
+                    "`train_size` + `test_size` cannot exceed the total number of samples. Received "
+                    f"`train_size`: {train_end}, `test_size`: {test_end}, and `dataset_size`: {len(dataset_shuffled)}."
+                )
         else:
             test_end = len(dataset_shuffled) - train_end