




"""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
lowercase__     						=						"""src/transformers"""
lowercase__     						=						"""docs/source/en/tasks"""







def      _snake_case			(				lowercase__							,    lowercase__							,    lowercase__		):
				with open(lowercase__							,    'r'							,    encoding='utf-8'							,    newline='\n'		) as f:
								_lowerCamelCase     :			Tuple    =    f.readlines()
				# Find the start prompt.
				_lowerCamelCase     :			Tuple    =    0
				while not lines[start_index].startswith(lowercase__		):
								start_index += 1
				start_index += 1

				_lowerCamelCase     :			List[Any]    =    start_index
				while not lines[end_index].startswith(lowercase__		):
								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.
lowercase__     						=						direct_transformers_import(TRANSFORMERS_PATH)

lowercase__     						=						{
    """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`).
lowercase__     						=						{
    """summarization.md""": ("""nllb""",),
    """translation.md""": ("""nllb""",),
}







def      _snake_case			(				lowercase__		):
				_lowerCamelCase     :			Dict    =    TASK_GUIDE_TO_MODELS[task_guide]
				_lowerCamelCase     :			Union[str, Any]    =    SPECIAL_TASK_GUIDE_TO_MODEL_TYPES.get(lowercase__							,    set()		)
				_lowerCamelCase     :			Optional[Any]    =    {
				    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      _snake_case			(				lowercase__							,    lowercase__=False		):
				_lowerCamelCase, _lowerCamelCase, _lowerCamelCase, _lowerCamelCase     :			Dict    =    _find_text_in_file(
				    filename=os.path.join(lowercase__							,    lowercase__		)							,    start_prompt='<!--This tip is automatically generated by `make fix-copies`, do not fill manually!-->'							,    end_prompt='<!--End of the generated tip-->'							,    )

				_lowerCamelCase     :			Any    =    get_model_list_for_task(lowercase__		)

				if current_list != new_list:
								if overwrite:
												with open(os.path.join(lowercase__							,    lowercase__		)							,    '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__":
			lowercase__     						=						argparse.ArgumentParser()
			parser.add_argument("""--fix_and_overwrite""", action="""store_true""", help="""Whether to fix inconsistencies.""")
			lowercase__     						=						parser.parse_args()

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





"""simple docstring"""






import math







def      _snake_case			(				lowercase__		):
				return math.sqrt(lowercase__		) * math.sqrt(lowercase__		) == num







def      _snake_case			(				lowercase__		):
				_lowerCamelCase     :			Optional[int]    =    0
				_lowerCamelCase     :			List[Any]    =    n
				while left <= right:
								_lowerCamelCase     :			str    =    (left + right) // 2
								if mid**2 == n:
												return True
								elif mid**2 > n:
												_lowerCamelCase     :			str    =    mid - 1
								else:
												_lowerCamelCase     :			Optional[int]    =    mid + 1
				return False


if __name__ == "__main__":
			import doctest

			doctest.testmod()