FIX: utilize dlapi to simplify codes

Author: hyp1231

recbole/data/dataloader/abstract_dataloader.py

@@ -55,13 +55,6 @@ def __init__(self, config, dataset, batch_size=1, dl_format=InputType.POINTWISE,
         if self.real_time is None:
             self.real_time = True
 
-        self.join = self.dataset.join
-        self.history_item_matrix = self.dataset.history_item_matrix
-        self.history_user_matrix = self.dataset.history_user_matrix
-        self.inter_matrix = self.dataset.inter_matrix
-        self.get_user_feature = self.dataset.get_user_feature
-        self.get_item_feature = self.dataset.get_item_feature
-
         for dataset_attr in self.dataset._dataloader_apis:
             try:
                 flag = hasattr(self.dataset, dataset_attr)

recbole/data/dataset/dataset.py

@@ -1173,6 +1173,7 @@ def _check_field(self, *field_names):
             if getattr(self, field_name, None) is None:
                 raise ValueError(f'{field_name} isn\'t set.')
 
+    @dlapi.set()
     def join(self, df):
         """Given interaction feature, join user/item feature into it.
 
@@ -1429,6 +1430,7 @@ def save(self, filepath):
             if df is not None:
                 df.to_csv(os.path.join(filepath, f'{name}.csv'))
 
+    @dlapi.set()
     def get_user_feature(self):
         """
         Returns:
@@ -1440,6 +1442,7 @@ def get_user_feature(self):
         else:
             return self.user_feat
 
+    @dlapi.set()
     def get_item_feature(self):
         """
         Returns:
@@ -1536,6 +1539,7 @@ def _create_graph(self, tensor_feat, source_field, target_field, form='dgl', val
         else:
             raise NotImplementedError(f'Graph format [{form}] has not been implemented.')
 
+    @dlapi.set()
     def inter_matrix(self, form='coo', value_field=None):
         """Get sparse matrix that describe interactions between user_id and item_id.
 
@@ -1617,6 +1621,7 @@ def _history_matrix(self, row, value_field=None):
 
         return torch.LongTensor(history_matrix), torch.FloatTensor(history_value), torch.LongTensor(history_len)
 
+    @dlapi.set()
     def history_item_matrix(self, value_field=None):
         """Get dense matrix describe user's history interaction records.
 
@@ -1641,6 +1646,7 @@ def history_item_matrix(self, value_field=None):
         """
         return self._history_matrix(row='user', value_field=value_field)
 
+    @dlapi.set()
     def history_user_matrix(self, value_field=None):
         """Get dense matrix describe item's history interaction records.