make a tool to check the alias name and __all__ part

docs/count.py

@@ -0,0 +1,98 @@
+import os
+
+
+def find_all(path='../fastNLP'):
+    head_list = []
+    alias_list = []
+    for path, dirs, files in os.walk(path):
+        for file in files:
+            if file.endswith('.py'):
+                name = ".".join(path.split('/')[1:])
+                if file.split('.')[0] != "__init__":
+                    name = name + '.' + file.split('.')[0]
+                if len(name.split('.')) < 3 or name.startswith('fastNLP.core'):
+                    heads, alias = find_one(path + '/' + file)
+                    for h in heads:
+                        head_list.append(name + "." + h)
+                    for a in alias:
+                        alias_list.append(a)
+    heads = {}
+    for h in head_list:
+        end = h.split('.')[-1]
+        file = h[:-len(end) - 1]
+        if end not in heads:
+            heads[end] = set()
+        heads[end].add(file)
+    alias = {}
+    for a in alias_list:
+        for each in a:
+            end = each.split('.')[-1]
+            file = each[:-len(end) - 1]
+            if end not in alias:
+                alias[end] = set()
+            alias[end].add(file)
+    print("IN alias NOT IN heads")
+    for item in alias:
+        if item not in heads:
+            print(item, alias[item])
+        elif len(heads[item]) != 2:
+            print(item, alias[item], heads[item])
+    
+    print("\n\nIN heads NOT IN alias")
+    for item in heads:
+        if item not in alias:
+            print(item, heads[item])
+
+
+def find_class(path):
+    with open(path, 'r') as fin:
+        lines = fin.readlines()
+    pars = {}
+    for i, line in enumerate(lines):
+        if line.strip().startswith('class'):
+            line = line.strip()[len('class'):-1].strip()
+            if line[-1] == ')':
+                line = line[:-1].split('(')
+                name = line[0].strip()
+                parents = line[1].split(',')
+                for i in range(len(parents)):
+                    parents[i] = parents[i].strip()
+                if len(parents) == 1:
+                    pars[name] = parents[0]
+                else:
+                    pars[name] = tuple(parents)
+    return pars
+
+
+def find_one(path):
+    head_list = []
+    alias = []
+    with open(path, 'r') as fin:
+        lines = fin.readlines()
+    flag = False
+    for i, line in enumerate(lines):
+        if line.strip().startswith('__all__'):
+            line = line.strip()[len('__all__'):].strip()
+            if line[-1] == ']':
+                line = line[1:-1].strip()[1:].strip()
+                head_list.append(line.strip("\"").strip("\'").strip())
+            else:
+                flag = True
+        elif line.strip() == ']':
+            flag = False
+        elif flag:
+            line = line.strip()[:-1].strip("\"").strip("\'").strip()
+            if len(line) == 0 or line[0] == '#':
+                continue
+            head_list.append(line)
+        if line.startswith('def') or line.startswith('class'):
+            if lines[i + 2].strip().startswith("别名："):
+                names = lines[i + 2].strip()[len("别名："):].split()
+                names[0] = names[0][len(":class:`"):-1]
+                names[1] = names[1][len(":class:`"):-1]
+                alias.append((names[0], names[1]))
+    return head_list, alias
+
+
+if __name__ == "__main__":
+    find_all()  # use to check __all__

fastNLP/__init__.py

@@ -13,11 +13,11 @@ fastNLP 中最常用的组件可以直接从 fastNLP 包中 import ，他们的
 __all__ = [
     "Instance",
     "FieldArray",
-
+    
     "DataSetIter",
     "BatchIter",
     "TorchLoaderIter",
-
+    
     "Vocabulary",
     "DataSet",
     "Const",
@@ -51,7 +51,8 @@ __all__ = [
     
     "LossFunc",
     "CrossEntropyLoss",
-    "L1Loss", "BCELoss",
+    "L1Loss",
+    "BCELoss",
     "NLLLoss",
     "LossInForward",