Coverage for /pythoncovmergedfiles/medio/medio/usr/local/lib/python3.8/site-packages/tensorflow/python/util/traceback_utils.py: 56%

1# Copyright 2021 The TensorFlow Authors. All Rights Reserved. 

2# 

3# Licensed under the Apache License, Version 2.0 (the "License"); 

4# you may not use this file except in compliance with the License. 

5# You may obtain a copy of the License at 

6# 

7# http://www.apache.org/licenses/LICENSE-2.0 

8# 

9# Unless required by applicable law or agreed to in writing, software 

10# distributed under the License is distributed on an "AS IS" BASIS, 

11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 

12# See the License for the specific language governing permissions and 

13# limitations under the License. 

14# ============================================================================== 

15"""Utilities related to TensorFlow exception stack trace prettifying.""" 

16 

17import os 

18import sys 

19import threading 

20import traceback 

21import types 

22from tensorflow.python.util import tf_decorator 

23from tensorflow.python.util.tf_export import tf_export 

24 

25 

26_ENABLE_TRACEBACK_FILTERING = threading.local() 

27_EXCLUDED_PATHS = ( 

28 os.path.abspath(os.path.join(__file__, '..', '..')), 

29) 

30 

31 

32@tf_export('debugging.is_traceback_filtering_enabled') 

33def is_traceback_filtering_enabled(): 

34 """Check whether traceback filtering is currently enabled. 

35 

36 See also `tf.debugging.enable_traceback_filtering()` and 

37 `tf.debugging.disable_traceback_filtering()`. Note that filtering out 

38 internal frames from the tracebacks of exceptions raised by TensorFlow code 

39 is the default behavior. 

40 

41 Returns: 

42 True if traceback filtering is enabled 

43 (e.g. if `tf.debugging.enable_traceback_filtering()` was called), 

44 and False otherwise (e.g. if `tf.debugging.disable_traceback_filtering()` 

45 was called). 

46 """ 

47 value = getattr(_ENABLE_TRACEBACK_FILTERING, 'value', True) 

48 return value 

49 

50 

51@tf_export('debugging.enable_traceback_filtering') 

52def enable_traceback_filtering(): 

53 """Enable filtering out TensorFlow-internal frames in exception stack traces. 

54 

55 Raw TensorFlow stack traces involve many internal frames, which can be 

56 challenging to read through, while not being actionable for end users. 

57 By default, TensorFlow filters internal frames in most exceptions that it 

58 raises, to keep stack traces short, readable, and focused on what's 

59 actionable for end users (their own code). 

60 

61 If you have previously disabled traceback filtering via 

62 `tf.debugging.disable_traceback_filtering()`, you can re-enable it via 

63 `tf.debugging.enable_traceback_filtering()`. 

64 

65 Raises: 

66 RuntimeError: If Python version is not at least 3.7. 

67 """ 

68 if sys.version_info.major != 3 or sys.version_info.minor < 7: 

69 raise RuntimeError( 

70 f'Traceback filtering is only available with Python 3.7 or higher. ' 

71 f'This Python version: {sys.version}') 

72 global _ENABLE_TRACEBACK_FILTERING 

73 _ENABLE_TRACEBACK_FILTERING.value = True 

74 

75 

76@tf_export('debugging.disable_traceback_filtering') 

77def disable_traceback_filtering(): 

78 """Disable filtering out TensorFlow-internal frames in exception stack traces. 

79 

80 Raw TensorFlow stack traces involve many internal frames, which can be 

81 challenging to read through, while not being actionable for end users. 

82 By default, TensorFlow filters internal frames in most exceptions that it 

83 raises, to keep stack traces short, readable, and focused on what's 

84 actionable for end users (their own code). 

85 

86 Calling `tf.debugging.disable_traceback_filtering` disables this filtering 

87 mechanism, meaning that TensorFlow exceptions stack traces will include 

88 all frames, in particular TensorFlow-internal ones. 

89 

90 **If you are debugging a TensorFlow-internal issue, you need to call 

91 `tf.debugging.disable_traceback_filtering`**. 

92 To re-enable traceback filtering afterwards, you can call 

93 `tf.debugging.enable_traceback_filtering()`. 

94 """ 

95 global _ENABLE_TRACEBACK_FILTERING 

96 _ENABLE_TRACEBACK_FILTERING.value = False 

97 

98 

99def include_frame(fname): 

100 for exclusion in _EXCLUDED_PATHS: 

101 if exclusion in fname: 

102 return False 

103 return True 

104 

105 

106def _process_traceback_frames(tb): 

107 new_tb = None 

108 tb_list = list(traceback.walk_tb(tb)) 

109 for f, line_no in reversed(tb_list): 

110 if include_frame(f.f_code.co_filename): 

111 new_tb = types.TracebackType(new_tb, f, f.f_lasti, line_no) 

112 if new_tb is None and tb_list: 

113 f, line_no = tb_list[-1] 

114 new_tb = types.TracebackType(new_tb, f, f.f_lasti, line_no) 

115 return new_tb 

116 

117 

118def filter_traceback(fn): 

119 """Decorator to filter out TF-internal stack trace frames in exceptions. 

120 

121 Raw TensorFlow stack traces involve many internal frames, which can be 

122 challenging to read through, while not being actionable for end users. 

123 By default, TensorFlow filters internal frames in most exceptions that it 

124 raises, to keep stack traces short, readable, and focused on what's 

125 actionable for end users (their own code). 

126 

127 Arguments: 

128 fn: The function or method to decorate. Any exception raised within the 

129 function will be reraised with its internal stack trace frames filtered 

130 out. 

131 

132 Returns: 

133 Decorated function or method. 

134 """ 

135 if sys.version_info.major != 3 or sys.version_info.minor < 7: 

136 return fn 

137 

138 def error_handler(*args, **kwargs): 

139 try: 

140 if not is_traceback_filtering_enabled(): 

141 return fn(*args, **kwargs) 

142 except NameError: 

143 # In some very rare cases, 

144 # `is_traceback_filtering_enabled` (from the outer scope) may not be 

145 # accessible from inside this function 

146 return fn(*args, **kwargs) 

147 

148 filtered_tb = None 

149 try: 

150 return fn(*args, **kwargs) 

151 except Exception as e: 

152 filtered_tb = _process_traceback_frames(e.__traceback__) 

153 raise e.with_traceback(filtered_tb) from None 

154 finally: 

155 del filtered_tb 

156 

157 return tf_decorator.make_decorator(fn, error_handler)