fix format

Author: wangzhen38

models/recall/mhcn/config.yaml

@@ -13,7 +13,7 @@
 # limitations under the License.
 
 runner:
-  train_data_dir: "data/train"
+  train_data_dir: "data"
   rating_file: "data/ratings_100.txt"
   relation_file: "data/trusts_100.txt"
   train_batch_size: 8
@@ -23,13 +23,14 @@ runner:
   epochs: 5
   print_interval: 1
   model_save_path: "output_model_mhcn"
-  test_data_dir: "data/test"
+  test_data_dir: "data"
   infer_batch_size: 8
   infer_reader_path: "lastfm_reader" # importlib format
   infer_load_path: "output_model_mhcn"
   infer_start_epoch: 0
   infer_end_epoch: 5
   top_k: 10
+  is_train: True
 
   # hyper parameters of user-defined network
 hyper_parameters:

models/recall/mhcn/config_bigdata.yaml

@@ -13,7 +13,7 @@
 # limitations under the License.
 
 runner:
-  train_data_dir: "data/train"
+  train_data_dir: "data"
   rating_file: "../../../datasets/LastFM_MHCN/lastfm/ratings.txt"
   relation_file: "../../../datasets/LastFM_MHCN/lastfm/trusts.txt"
   train_batch_size: 2000
@@ -23,13 +23,14 @@ runner:
   epochs: 120
   print_interval: 1
   model_save_path: "output_model_mhcn_all"
-  test_data_dir: "data/test"
+  test_data_dir: "data"
   infer_batch_size: 2000
   infer_reader_path: "lastfm_reader" # importlib format
   infer_load_path: "output_model_mhcn_all"
   infer_start_epoch: 0
   infer_end_epoch: 117
   top_k: 10
+  is_train: True
 
   # hyper parameters of user-defined network
 hyper_parameters:

models/recall/mhcn/data/test/test.txt

@@ -386,8 +386,7 @@ def crossValidation(data, k, binarized=False):
 class RecDataset(IterableDataset):
     def __init__(self, file_list, config):
         super(RecDataset, self).__init__()
-        self.file_list = file_list
-        self.is_train = True if "train" in file_list or file_list else False
+        self.is_train = config.get("runner.is_train", True)
         self.trainingSet = loadDataSet(
             config.get("runner.rating_file", None),
             bTest=False,

models/recall/mhcn/data/train/train.txt

@@ -33,11 +33,6 @@ def __init__(self, n_layers=2, emb_size=50, config=None):
         self.data, self.social = self.recDataset.get_dataset()
         self.num_users, self.num_items, _ = self.data.trainingSize()
 
-        # user num:  1891
-        print("user num: ", self.num_users)
-        # item num:  15438
-        print("item num: ", self.num_items)
-
         self.userAdjacency = None
         self.itemAdjacency = None