refactored code to a class with fit and transform methods

pytorch_widedeep/utils/wide_utils.py

@@ -26,11 +26,12 @@ class PrepareWide(object):
         return df, crossed_colnames
 
     def fit(self, df:pd.DataFrame)->np.ndarray:
-
         df_wide = df.copy()[self.wide_cols]
         if self.crossed_cols is not None:
             df_wide, crossed_colnames = self.cross_cols(df_wide)
             self.wide_crossed_cols = self.wide_cols + crossed_colnames
+        else:
+            self.wide_crossed_cols = self.wide_cols
 
         if self.already_dummies:
             X_oh_1 = self.df_wide[self.already_dummies].values
@@ -41,7 +42,6 @@ class PrepareWide(object):
             return self.one_hot_enc.fit_transform(df_wide[self.wide_crossed_cols])
 
     def transform(self, df:pd.DataFrame)->np.ndarray:
-
         df_wide = df.copy()[self.wide_cols]
         if self.crossed_cols is not None:
             df_wide, _ = self.cross_cols(df_wide)