





'''simple docstring'''





import argparse
import os

from transformers.utils import direct_transformers_import


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_task_guides.py
lowerCAmelCase_						   =    """src/transformers"""
lowerCAmelCase_						   =    """docs/source/en/tasks"""


def     lowerCamelCase_	(      lowerCAmelCase:	Union[str, Any]    ,							lowerCAmelCase:	Optional[Any]    ,							lowerCAmelCase:	str				)->		Tuple:
  with open(lowerCAmelCase    ,							'r'    ,							encoding='utf-8'    ,							newline='\n'				) as f:
    _snake_case   :				Any														=	f.readlines()
  # Find the start prompt.
  _snake_case   :				List[Any]														=	0
  while not lines[start_index].startswith(lowerCAmelCase				):
    start_index += 1
  start_index += 1

  _snake_case   :				int														=	start_index
  while not lines[end_index].startswith(lowerCAmelCase				):
    end_index += 1
  end_index -= 1

  while len(lines[start_index]				) <= 1:
    start_index += 1
  while len(lines[end_index]				) <= 1:
    end_index -= 1
  end_index += 1
  return "".join(lines[start_index:end_index]				), start_index, end_index, lines


# This is to make sure the transformers module imported is the one in the repo.
lowerCAmelCase_						   =    direct_transformers_import(TRANSFORMERS_PATH)

lowerCAmelCase_						   =    {
    """asr.md""": transformers_module.models.auto.modeling_auto.MODEL_FOR_CTC_MAPPING_NAMES,
    """audio_classification.md""": transformers_module.models.auto.modeling_auto.MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING_NAMES,
    """language_modeling.md""": transformers_module.models.auto.modeling_auto.MODEL_FOR_CAUSAL_LM_MAPPING_NAMES,
    """image_classification.md""": transformers_module.models.auto.modeling_auto.MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING_NAMES,
    """masked_language_modeling.md""": transformers_module.models.auto.modeling_auto.MODEL_FOR_MASKED_LM_MAPPING_NAMES,
    """multiple_choice.md""": transformers_module.models.auto.modeling_auto.MODEL_FOR_MULTIPLE_CHOICE_MAPPING_NAMES,
    """object_detection.md""": transformers_module.models.auto.modeling_auto.MODEL_FOR_OBJECT_DETECTION_MAPPING_NAMES,
    """question_answering.md""": transformers_module.models.auto.modeling_auto.MODEL_FOR_QUESTION_ANSWERING_MAPPING_NAMES,
    """semantic_segmentation.md""": transformers_module.models.auto.modeling_auto.MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING_NAMES,
    """sequence_classification.md""": transformers_module.models.auto.modeling_auto.MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING_NAMES,
    """summarization.md""": transformers_module.models.auto.modeling_auto.MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES,
    """token_classification.md""": transformers_module.models.auto.modeling_auto.MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING_NAMES,
    """translation.md""": transformers_module.models.auto.modeling_auto.MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES,
    """video_classification.md""": transformers_module.models.auto.modeling_auto.MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING_NAMES,
    """document_question_answering.md""": transformers_module.models.auto.modeling_auto.MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING_NAMES,
    """monocular_depth_estimation.md""": transformers_module.models.auto.modeling_auto.MODEL_FOR_DEPTH_ESTIMATION_MAPPING_NAMES,
}

# This list contains model types used in some task guides that are not in `CONFIG_MAPPING_NAMES` (therefore not in any
# `MODEL_MAPPING_NAMES` or any `MODEL_FOR_XXX_MAPPING_NAMES`).
lowerCAmelCase_						   =    {
    """summarization.md""": ("""nllb""",),
    """translation.md""": ("""nllb""",),
}


def     lowerCamelCase_	(      lowerCAmelCase:	Optional[int]				)->		Any:
  _snake_case   :				Tuple														=	TASK_GUIDE_TO_MODELS[task_guide]
  _snake_case   :				Union[str, Any]														=	SPECIAL_TASK_GUIDE_TO_MODEL_TYPES.get(lowerCAmelCase    ,							set()				)
  _snake_case   :				Dict														=	{
      code: name
      for code, name in transformers_module.MODEL_NAMES_MAPPING.items()
      if (code in model_maping_names or code in special_model_types)
  }
  return ", ".join([F"""[{name}](../model_doc/{code})""" for code, name in model_names.items()]				) + "\n"


def     lowerCamelCase_	(      lowerCAmelCase:	Union[str, Any]    ,							lowerCAmelCase:	Dict=False				)->		Union[str, Any]:
  _snake_case							,					_snake_case							,					_snake_case							,					_snake_case   :				Tuple														=	_find_text_in_file(
      filename=os.path.join(lowerCAmelCase    ,							lowerCAmelCase				)    ,							start_prompt='<!--This tip is automatically generated by `make fix-copies`, do not fill manually!-->'    ,							end_prompt='<!--End of the generated tip-->'    ,							)

  _snake_case   :				Optional[Any]														=	get_model_list_for_task(lowerCAmelCase				)

  if current_list != new_list:
    if overwrite:
      with open(os.path.join(lowerCAmelCase    ,							lowerCAmelCase				)    ,							'w'    ,							encoding='utf-8'    ,							newline='\n'				) as f:
        f.writelines(lines[:start_index] + [new_list] + lines[end_index:]				)
    else:
      raise ValueError(
          F"""The list of models that can be used in the {task_guide} guide needs an update. Run `make fix-copies`"""
          ' to fix this.'				)


if __name__ == "__main__":
      lowerCAmelCase_						   =    argparse.ArgumentParser()
      parser.add_argument("""--fix_and_overwrite""", action="""store_true""", help="""Whether to fix inconsistencies.""")
      lowerCAmelCase_						   =    parser.parse_args()

      for task_guide in TASK_GUIDE_TO_MODELS.keys():
            check_model_list_for_task(task_guide, args.fix_and_overwrite)











def     lowerCamelCase_	(      lowerCAmelCase:	int				)->		int:

  if not isinstance(lowerCAmelCase    ,							lowerCAmelCase				):
    _snake_case   :				Union[str, Any]														=	F"""Input value of [number={number}] must be an integer"""
    raise TypeError(lowerCAmelCase				)

  if number < 1:
    _snake_case   :				int														=	F"""Input value of [number={number}] must be > 0"""
    raise ValueError(lowerCAmelCase				)

  _snake_case   :				int														=	1

  for i in range(1    ,							lowerCAmelCase				):
    current_number *= 4 * i - 2
    current_number //= i + 1

  return current_number


if __name__ == "__main__":
      import doctest

      doctest.testmod()




