




'''simple docstring'''



UpperCAmelCase_       :  Tuple      =		'''
# Installation de Transformers
! pip install transformers datasets
# Pour installer à partir du code source au lieu de la dernière version, commentez la commande ci-dessus et décommentez la suivante.
# ! pip install git+https://github.com/huggingface/transformers.git
'''

UpperCAmelCase_       :  Optional[int]      =		[{'''type''': '''code''', '''content''': INSTALL_CONTENT}]
UpperCAmelCase_       :  List[Any]      =		{
    '''{processor_class}''': '''FakeProcessorClass''',
    '''{model_class}''': '''FakeModelClass''',
    '''{object_class}''': '''FakeObjectClass''',
}












'''simple docstring'''



# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
from typing import List







def 			_UpperCamelCase (_lowerCamelCase							:     List[str]   ,	_lowerCamelCase							:     str	)->   str:




     '''simple docstring'''





     if name != "training_function" and name != "main":
          raise ValueError(f'''Incorrect function name passed: {name}, choose either \'main\' or \'training_function\''''	)
     __snake_case					,    __snake_case    					=  [], False
     for line in lines:
          if not found_start and f'''def {name}''' in line:
               __snake_case    					=  True
               good_lines.append(_lowerCamelCase	)
               continue
          if found_start:
               if name == "training_function" and "def main" in line:
                    return good_lines
               if name == "main" and "if __name__" in line:
                    return good_lines
               good_lines.append(_lowerCamelCase	)







def 			_UpperCamelCase (_lowerCamelCase							:     List[str]	)->   int:




     '''simple docstring'''





     return [line for line in lines if not line.lstrip().startswith('''#'''	) and line != "\n"]







def 			_UpperCamelCase (_lowerCamelCase							:     str   ,	_lowerCamelCase							:     str   ,	_lowerCamelCase							:     bool   ,	_lowerCamelCase							:     str = None	)->   Optional[Any]:




     '''simple docstring'''





     with open(_lowerCamelCase   ,	'''r'''	) as f:
          __snake_case    					=  f.readlines()
     with open(os.path.abspath(os.path.join('''examples'''   ,	'''nlp_example.py'''	)	)   ,	'''r'''	) as f:
          __snake_case    					=  f.readlines()
     with open(_lowerCamelCase   ,	'''r'''	) as f:
          __snake_case    					=  f.readlines()
     if secondary_filename is not None:
          with open(_lowerCamelCase   ,	'''r'''	) as f:
               __snake_case    					=  f.readlines()

    # This is our base, we remove all the code from here in our `full_filename` and `feature_filename` to find the new content
     if parser_only:
          __snake_case    					=  clean_lines(get_function_contents_by_name(_lowerCamelCase   ,	'''main'''	)	)
          __snake_case    					=  clean_lines(get_function_contents_by_name(_lowerCamelCase   ,	'''main'''	)	)
          __snake_case    					=  clean_lines(get_function_contents_by_name(_lowerCamelCase   ,	'''main'''	)	)
          if secondary_filename is not None:
               __snake_case    					=  clean_lines(get_function_contents_by_name(_lowerCamelCase   ,	'''main'''	)	)
     else:
          __snake_case    					=  clean_lines(get_function_contents_by_name(_lowerCamelCase   ,	'''training_function'''	)	)
          __snake_case    					=  clean_lines(get_function_contents_by_name(_lowerCamelCase   ,	'''training_function'''	)	)
          __snake_case    					=  clean_lines(get_function_contents_by_name(_lowerCamelCase   ,	'''training_function'''	)	)
          if secondary_filename is not None:
               __snake_case    					=  clean_lines(
                   get_function_contents_by_name(_lowerCamelCase   ,	'''training_function'''	)	)

     __snake_case    					=  '''train_dataloader, eval_dataloader = get_dataloaders(accelerator, batch_size)\n'''

     # Specific code in our script that differs from the full version, aka what is new
     __snake_case    					=  []
     __snake_case    					=  []  # We keep track of the idxs just in case it's a repeated statement
     __snake_case    					=  iter(_lowerCamelCase	)
     for i in range(len(_lowerCamelCase	) - 1	):
          if i not in passed_idxs:
               __snake_case    					=  next(_lowerCamelCase	)
               if (line not in full_file_func) and (line.lstrip() != _dl_line):
                    if "TESTING_MOCKED_DATALOADERS" not in line:
                         new_feature_code.append(_lowerCamelCase	)
                         passed_idxs.append(_lowerCamelCase	)
                    else:
                         # Skip over the `config['num_epochs'] = 2` statement
                         __snake_case    					=  next(_lowerCamelCase	)

    # Extract out just the new parts from the full_file_training_func
     __snake_case    					=  []
     __snake_case    					=  []  # We keep track of the idxs just in case it's a repeated statement
     for i, line in enumerate(_lowerCamelCase	):
          if i not in passed_idxs:
               if (line not in full_file_func) and (line.lstrip() != _dl_line):
                    if "TESTING_MOCKED_DATALOADERS" not in line:
                         new_full_example_parts.append(_lowerCamelCase	)
                         passed_idxs.append(_lowerCamelCase	)

    # Finally, get the overall diff
     __snake_case    					=  [line for line in new_feature_code if line not in new_full_example_parts]
     if secondary_filename is not None:
          __snake_case    					=  [line for line in full_file_contents if line not in secondary_file_func]
          __snake_case    					=  [line for line in diff_from_example if line not in diff_from_two]

     return diff_from_example






