


"""simple docstring"""




import os
from typing import List



def 						__a      (  a,		a					)     ->   Union[str, Any]:





       """simple docstring"""







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



def 						__a      (  a					)     ->   List[Any]:





       """simple docstring"""







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



def 						__a      (  a,		a,		a,		a = None					)     ->   Optional[Any]:





       """simple docstring"""







       with open(a,		"r"					) as f:
              _a          =				f.readlines()
       with open(os.path.abspath(os.path.join("examples",		"nlp_example.py"					)					),		"r"					) as f:
              _a          =				f.readlines()
       with open(a,		"r"					) as f:
              _a          =				f.readlines()
       if secondary_filename is not None:
              with open(a,		"r"					) as f:
                     _a          =				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:
              _a          =				clean_lines(get_function_contents_by_name(a,		"main"					)					)
              _a          =				clean_lines(get_function_contents_by_name(a,		"main"					)					)
              _a          =				clean_lines(get_function_contents_by_name(a,		"main"					)					)
              if secondary_filename is not None:
                     _a          =				clean_lines(get_function_contents_by_name(a,		"main"					)					)
       else:
              _a          =				clean_lines(get_function_contents_by_name(a,		"training_function"					)					)
              _a          =				clean_lines(get_function_contents_by_name(a,		"training_function"					)					)
              _a          =				clean_lines(get_function_contents_by_name(a,		"training_function"					)					)
              if secondary_filename is not None:
                     _a          =				clean_lines(
                         get_function_contents_by_name(a,		"training_function"					)					)

       _a          =				"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
       _a          =				[]
       _a          =				[]  # We keep track of the idxs just in case it's a repeated statement
       _a          =				iter(a					)
       for i in range(len(a					) - 1					):
              if i not in passed_idxs:
                     _a          =				next(a					)
                     if (line not in full_file_func) and (line.lstrip() != _dl_line):
                            if "TESTING_MOCKED_DATALOADERS" not in line:
                                   new_feature_code.append(a					)
                                   passed_idxs.append(a					)
                            else:
                                   # Skip over the `config['num_epochs'] = 2` statement
                                   _a          =				next(a					)

    # Extract out just the new parts from the full_file_training_func
       _a          =				[]
       _a          =				[]  # We keep track of the idxs just in case it's a repeated statement
       for i, line in enumerate(a					):
              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(a					)
                                   passed_idxs.append(a					)

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

       return diff_from_example




"""simple docstring"""




import warnings

from ...utils import logging
from .image_processing_vit import ViTImageProcessor


__SCREAMING_SNAKE_CASE					=						logging.get_logger(__name__)





class __snake_case		(					_SCREAMING_SNAKE_CASE      ):







   """simple docstring"""




   def __init__(		self							:Tuple				,  *UpperCamelCase__							:Tuple				,  **UpperCamelCase__							:Any       ):
          warnings.warn(
              "The class ViTFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"
              " use ViTImageProcessor instead."				,  UpperCamelCase__				,  )
          super().__init__(*UpperCamelCase__				,  **UpperCamelCase__       )
