fix lawbench 2-1 f0.5 score calculation bug (#795)

* fix lawbench 2-1 f0.5 score calculation bug

* use path in overall datasets folder

---------
Co-authored-by: Leymore <zfz-960727@163.com>

opencompass/datasets/lawbench/utils/modules/alignment.py

@@ -22,8 +22,7 @@ def read_cilin():
     Cilin 詞林 is a thesaurus with semantic information
     """
     # TODO -- fix this path
-    project_dir = os.path.dirname(os.path.dirname(__file__))  # ymliu@2023.5.30 fix the path
-    lines = open(os.path.join(project_dir, "data", "cilin.txt"), "r", encoding="gbk").read().strip().split("\n")
+    lines = open(os.path.join(os.path.dirname(__file__), "..", "..", "..", "..", "..", "data", "lawbench", "eval_assets", "cilin.txt"), "r", encoding="gbk").read().strip().split("\n")
     semantic_dict = {}
     semantic_classes = {}
     for line in lines:
@@ -40,8 +39,7 @@ def read_cilin():
 
 def read_confusion():
     confusion_dict = {}
-    project_dir = os.path.dirname(os.path.dirname(__file__))  # ymliu@2023.5.30 fix the path
-    with open(os.path.join(project_dir, "data", "confusion_dict.txt"), "r", encoding="utf-8") as f:
+    with open(os.path.join(os.path.dirname(__file__), "..", "..", "..", "..", "..", "data", "lawbench", "eval_assets", "confusion_dict.txt"), "r", encoding="utf-8") as f:
         for line in f:
             li = line.rstrip('\n').split(" ")
             confusion_dict[li[0]] = li[1:]

opencompass/datasets/lawbench/utils/modules/classifier.py

@@ -10,8 +10,7 @@ Correction = namedtuple(
         "inds",
     ],
 ) 
-file_path = os.path.dirname(os.path.abspath(__file__))
-char_smi = CharFuncs(os.path.join(file_path.replace("modules", ""), 'data/char_meta.txt'))
+char_smi = CharFuncs(os.path.join(os.path.dirname(__file__), "..", "..", "..", "..", "..", "data", "lawbench", "eval_assets", "char_meta.txt"))
 
 def check_spell_error(src_span: str,
                       tgt_span: str,

opencompass/datasets/lawbench/utils/modules/tokenizer.py

@@ -57,8 +57,7 @@ class Tokenizer:
         """
         if bpe:
             from . import tokenization
-            project_dir = os.path.dirname(os.path.dirname(__file__))
-            tokenizer = tokenization.FullTokenizer(vocab_file=os.path.join(project_dir,"data","chinese_vocab.txt"), do_lower_case=False)
+            tokenizer = tokenization.FullTokenizer(vocab_file=os.path.join(os.path.dirname(__file__), "..", "..", "..", "..", "..", "data", "lawbench", "eval_assets", "chinese_vocab.txt"), do_lower_case=False)
         results = []
         for input_string in input_strings:
             if not self.segmented:  # 如果没有被分字，就按照每个字符隔开（不考虑英文标点的特殊处理，也不考虑BPE），否则遵循原分字结果