





"""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__						(	_UpperCAmelCase					,   _UpperCAmelCase   ):






  """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_    :			Union[str, Any]									=    [], False
  for line in lines:
    if not found_start and f"""def {name}""" in line:
      A_    :			Tuple									=    True
      good_lines.append(_UpperCAmelCase   )
      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(_UpperCAmelCase   )





def 		UpperCAmelCase__						(	_UpperCAmelCase   ):






  """simple docstring"""





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





def 		UpperCAmelCase__						(	_UpperCAmelCase					,   _UpperCAmelCase					,   _UpperCAmelCase					,   _UpperCAmelCase = None   ):






  """simple docstring"""





  with open(_UpperCAmelCase					,   'r'   ) as f:
    A_    :			str									=    f.readlines()
  with open(os.path.abspath(os.path.join('examples'					,   'nlp_example.py'   )   )					,   'r'   ) as f:
    A_    :			Optional[Any]									=    f.readlines()
  with open(_UpperCAmelCase					,   'r'   ) as f:
    A_    :			int									=    f.readlines()
  if secondary_filename is not None:
    with open(_UpperCAmelCase					,   'r'   ) as f:
      A_    :			Tuple									=    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_    :			Union[str, Any]									=    clean_lines(get_function_contents_by_name(_UpperCAmelCase					,   'main'   )   )
    A_    :			List[Any]									=    clean_lines(get_function_contents_by_name(_UpperCAmelCase					,   'main'   )   )
    A_    :			List[str]									=    clean_lines(get_function_contents_by_name(_UpperCAmelCase					,   'main'   )   )
    if secondary_filename is not None:
      A_    :			Optional[Any]									=    clean_lines(get_function_contents_by_name(_UpperCAmelCase					,   'main'   )   )
  else:
    A_    :			List[Any]									=    clean_lines(get_function_contents_by_name(_UpperCAmelCase					,   'training_function'   )   )
    A_    :			Dict									=    clean_lines(get_function_contents_by_name(_UpperCAmelCase					,   'training_function'   )   )
    A_    :			int									=    clean_lines(get_function_contents_by_name(_UpperCAmelCase					,   'training_function'   )   )
    if secondary_filename is not None:
      A_    :			int									=    clean_lines(
          get_function_contents_by_name(_UpperCAmelCase					,   'training_function'   )   )

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

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

    # Finally, get the overall diff
  A_    :			Optional[int]									=    [line for line in new_feature_code if line not in new_full_example_parts]
  if secondary_filename is not None:
    A_    :			Union[str, Any]									=    [line for line in full_file_contents if line not in secondary_file_func]
    A_    :			List[str]									=    [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_detr import DetrImageProcessor


lowerCamelCase_	:		List[str]         =   logging.get_logger(__name__)

class 					_UpperCAmelCase    (  UpperCAmelCase__						):



      '''simple docstring'''

      def __init__(	self   , *snake_case_   , **snake_case_    ):

        """simple docstring"""

        warnings.warn(
            'The class DetrFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'
            ' Please use DetrImageProcessor instead.'   , snake_case_   , )
        super().__init__(*snake_case_   , **snake_case_    )