Merge pull request #730 from guijiql/master

FIX: typos in doc for evaluator

.github/workflows/python-package.yml

@@ -44,4 +44,4 @@ jobs:
         python -m pytest -v tests/config/test_config.py
         export PYTHONPATH=.
         python tests/config/test_command_line.py --use_gpu=False --valid_metric=Recall@10 --split_ratio=[0.7,0.2,0.1] --metrics=['Recall@10'] --epochs=200 --eval_setting='LO_RS' --learning_rate=0.3
-    
+

recbole/evaluator/evaluators.py

@@ -189,7 +189,7 @@ def average_rank(self, scores):
             torch.Tensor: average_rank
 
         Example:
-            >>> average_rank(tensor([[1,2,2,2,3,3,6],[2,2,2,2,4,4,5]]))
+            >>> average_rank(tensor([[1,2,2,2,3,3,6],[2,2,2,2,4,5,5]]))
             tensor([[1.0000, 3.0000, 3.0000, 3.0000, 5.5000, 5.5000, 7.0000],
             [2.5000, 2.5000, 2.5000, 2.5000, 5.0000, 6.5000, 6.5000]])
 
@@ -243,7 +243,7 @@ def evaluate(self, batch_matrix_list, eval_data):
             eval_data (Dataset): the class of test data
 
         Returns:
-            dict: such as ``{'GAUC:0.9286}``
+            dict: such as ``{'GAUC': 0.9286}``
 
         """
         pos_len_list = eval_data.get_pos_len_list()
@@ -282,8 +282,6 @@ def __str__(self):
         msg = 'The Rank Evaluator Info:\n' + \
               '\tMetrics:[' + \
               ', '.join([rank_metrics[metric.lower()] for metric in self.metrics]) + \
-              '], TopK:[' + \
-              ', '.join(map(str, self.topk)) + \
               ']'
         return msg
 

recbole/evaluator/metrics.py

@@ -120,13 +120,13 @@ def ndcg_(pos_index, pos_len):
             \mathrm {DCG@K}=\sum_{i=1}^{K} \frac{2^{rel_i}-1}{\log_{2}{(i+1)}}\\
             \mathrm {IDCG@K}=\sum_{i=1}^{K}\frac{1}{\log_{2}{(i+1)}}\\
             \mathrm {NDCG_u@K}=\frac{DCG_u@K}{IDCG_u@K}\\
-            \mathrm {NDCG@K}=\frac{\sum \nolimits_{u \in u^{te}NDCG_u@K}}{|u^{te}|}
+            \mathrm {NDCG@K}=\frac{\sum \nolimits_{u \in U^{te}NDCG_u@K}}{|U^{te}|}
         \end{gather}
 
     :math:`K` stands for recommending :math:`K` items.
     And the :math:`rel_i` is the relevance of the item in position :math:`i` in the recommendation list.
-    :math:`2^{rel_i}` equals to 1 if the item hits otherwise 0.
-    :math:`U^{te}` is for all users in the test set.
+    :math:`{rel_i}` equals to 1 if the item is ground truth otherwise 0.
+    :math:`U^{te}` stands for all users in the test set.
 
     """
     len_rank = np.full_like(pos_len, pos_index.shape[1])

tests/model/test_model_auto.py

@@ -6,7 +6,7 @@
 # UPDATE
 # @Time    :   2020/11/17
 # @Author  :   Xingyu Pan
-# @email   :   [email protected]  
+# @email   :   [email protected]
 
 import os
 import unittest
@@ -160,14 +160,15 @@ def test_MacridVAE(self):
             'training_neg_sample_num': 0
         }
         quick_test(config_dict)
- 
+
     def test_CDAE(self):
         config_dict = {
             'model': 'CDAE',
             'training_neg_sample_num': 0
         }
         quick_test(config_dict)
 
+
 class TestContextRecommender(unittest.TestCase):
     # todo: more complex context information should be test, such as criteo dataset