Add hints for tabular

flash/tabular/classification/data/data.py

@@ -70,13 +70,13 @@ class TabularData(DataModule):
 
     def __init__(
         self,
-        train_df,
+        train_df: DataFrame,
         categorical_input: List,
         numerical_input: List,
         target: str,
-        valid_df=None,
-        test_df=None,
-        batch_size=2,
+        valid_df: Optional[DataFrame] = None,
+        test_df: Optional[DataFrame] = None,
+        batch_size: int = 2,
         num_workers: Optional[int] = None,
     ):
         dfs = [train_df]
@@ -131,12 +131,12 @@ def num_features(self) -> int:
     @classmethod
     def from_df(
         cls,
-        train_df: pd.DataFrame,
+        train_df: DataFrame,
         target: str,
         categorical_input: List,
         numerical_input: List,
-        valid_df: pd.DataFrame = None,
-        test_df: pd.DataFrame = None,
+        valid_df: Optional[DataFrame] = None,
+        test_df: Optional[DataFrame] = None,
         batch_size: int = 8,
         num_workers: Optional[int] = None,
         val_size: float = None,
@@ -192,7 +192,7 @@ def from_df(
     @classmethod
     def from_csv(
         cls,
-        train_csv,
+        train_csv: str,
         target: str,
         categorical_input: List,
         numerical_input: List,

flash/tabular/classification/data/dataset.py

@@ -129,7 +129,15 @@ def _dfs_to_samples(dfs, cat_cols, num_cols) -> list:
 
 class PandasDataset(Dataset):
 
-    def __init__(self, df, cat_cols, num_cols, target_col, regression=False, predict=False):
+    def __init__(
+        self,
+        df: DataFrame,
+        cat_cols: List,
+        num_cols: List,
+        target_col: str,
+        regression: bool = False,
+        predict: bool = False
+    ):
         self._num_samples = len(df)
         self.predict = predict
         cat_vars = _to_cat_vars_numpy(df, cat_cols)