DuplicateFlagError when trying to train tensorflow object detection api on google collaboratory

Question

I am trying to train Tensorflow Object Detection API on my dataset containing apples and capsicum. For that, I generated the required files (TFrecords and images with annotations) and placed them in models/research/object_detection directory. Then, I forked the Object detection api from github and pushed my files to my forked repo. Then, I clone this repo inside Google Collaboratory and run the train.py file but I get the DuplicateFlagError:master error.

---------------------------------------------------------------------------

DuplicateFlagError               Traceback (most recent call last)
/content/models/research/object_detection/train.py in <module>()
     56 
     57 flags = tf.app.flags
---> 58 flags.DEFINE_string('master', '', 'Name of the TensorFlow master to use.')
     59 flags.DEFINE_integer('task', 0, 'task id')
     60 flags.DEFINE_integer('num_clones', 1, 'Number of clones to deploy per worker.')

/usr/local/lib/python3.6/dist-packages/tensorflow/python/platform/flags.py in wrapper(*args, **kwargs)
     56           'Use of the keyword argument names (flag_name, default_value, '
     57           'docstring) is deprecated, please use (name, default, help) instead.')
---> 58     return original_function(*args, **kwargs)
     59 
     60   return tf_decorator.make_decorator(original_function, wrapper)

/usr/local/lib/python3.6/dist-packages/absl/flags/_defines.py in DEFINE_string(name, default, help, flag_values, **args)
    239   parser = _argument_parser.ArgumentParser()
    240   serializer = _argument_parser.ArgumentSerializer()
--> 241   DEFINE(parser, name, default, help, flag_values, serializer, **args)
    242 
    243 

/usr/local/lib/python3.6/dist-packages/absl/flags/_defines.py in DEFINE(parser, name, default, help, flag_values, serializer, module_name, **args)
     80   """
     81   DEFINE_flag(_flag.Flag(parser, serializer, name, default, help, **args),
---> 82               flag_values, module_name)
     83 
     84 

/usr/local/lib/python3.6/dist-packages/absl/flags/_defines.py in DEFINE_flag(flag, flag_values, module_name)
    102   # Copying the reference to flag_values prevents pychecker warnings.
    103   fv = flag_values
--> 104   fv[flag.name] = flag
    105   # Tell flag_values who's defining the flag.
    106   if module_name:

/usr/local/lib/python3.6/dist-packages/absl/flags/_flagvalues.py in __setitem__(self, name, flag)
    425         # module is simply being imported a subsequent time.
    426         return
--> 427       raise _exceptions.DuplicateFlagError.from_flag(name, self)
    428     short_name = flag.short_name
    429     # If a new flag overrides an old one, we need to cleanup the old flag's

DuplicateFlagError: The flag 'master' is defined twice. First from object_detection/train.py, Second from object_detection/train.py.  Description from first occurrence: Name of the TensorFlow master to use.

To solve it, I tried to comment that line, but then I got DuplicateFlagError on next flag i.e on next line. So, to try to solve the issue, I commented all the lines in train.py that declared those flags i.e I commented from line 58 to line 82. But then, I got the error NotFoundError: ;

---------------------------------------------------------------------------
NotFoundError                             Traceback (most recent call last)
/content/models/research/object_detection/train.py in <module>()
    165 
    166 if __name__ == '__main__':
--> 167   tf.app.run()

/usr/local/lib/python3.6/dist-packages/tensorflow/python/platform/app.py in run(main, argv)
    124   # Call the main function, passing through any arguments
    125   # to the final program.
--> 126   _sys.exit(main(argv))
    127 
    128 

/content/models/research/object_detection/train.py in main(_)
    105                            ('input.config', FLAGS.input_config_path)]:
    106         tf.gfile.Copy(config, os.path.join(FLAGS.train_dir, name),
--> 107                       overwrite=True)
    108 
    109   model_config = configs['model']

/usr/local/lib/python3.6/dist-packages/tensorflow/python/lib/io/file_io.py in copy(oldpath, newpath, overwrite)
    390   with errors.raise_exception_on_not_ok_status() as status:
    391     pywrap_tensorflow.CopyFile(
--> 392         compat.as_bytes(oldpath), compat.as_bytes(newpath), overwrite, status)
    393 
    394 

/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/errors_impl.py in __exit__(self, type_arg, value_arg, traceback_arg)
    514             None, None,
    515             compat.as_text(c_api.TF_Message(self.status.status)),
--> 516             c_api.TF_GetCode(self.status.status))
    517     # Delete the underlying status object from memory otherwise it stays alive
    518     # as there is a reference to status from this from the traceback due to

NotFoundError: ; No such file or directory

How should I solve it? This is my Collab notebook - https://drive.google.com/file/d/1mZGOKX3JZXyG4XYkI6WHIXoNbRSpkE_F/view?usp=sharing

Solution

####Delete all flags before declare#####

def del_all_flags(FLAGS):
    flags_dict = FLAGS._flags()    
    keys_list = [keys for keys in flags_dict]    
    for keys in keys_list:
        FLAGS.__delattr__(keys)

del_all_flags(tf.flags.FLAGS)

Comments

[Filnor]

While this code snippet may solve the question, including an explanation really helps to improve the quality of your post. Remember that you are answering the question for readers in the future, and those people might not know the reasons for your code suggestion. Please also try not to crowd your code with explanatory comments, this reduces the readability of both the code and the explanations!

[Md. Asaf-uddowla Golap]

Thank you @Filnor for your valuable suggestions.