"""simple docstring"""






import functools
import logging
import os
import sys
import threading
from logging import (
    CRITICAL,  # NOQA
    DEBUG,  # NOQA
    ERROR,  # NOQA
    FATAL,  # NOQA
    INFO,  # NOQA
    NOTSET,  # NOQA
    WARN,  # NOQA
    WARNING,  # NOQA
)
from typing import Optional

import huggingface_hub.utils as hf_hub_utils
from tqdm import auto as tqdm_lib


A	     =					threading.Lock()
A	     =					None

A	     =					{
    '''debug''': logging.DEBUG,
    '''info''': logging.INFO,
    '''warning''': logging.WARNING,
    '''error''': logging.ERROR,
    '''critical''': logging.CRITICAL,
}

A	     =					logging.WARNING

A	     =					True

def       __A (     )						->						List[str]:
				__a	:  Optional[int]         =					os.getenv('''TRANSFORMERS_VERBOSITY'''				,    a_)
				if env_level_str:
								if env_level_str in log_levels:
												return log_levels[env_level_str]
								else:
												logging.getLogger().warning(
												    F"""Unknown option TRANSFORMERS_VERBOSITY={env_level_str}, """
												    F"""has to be one of: { ", ".join(log_levels.keys()) }""")
				return _default_log_level

def       __A (     )						->						str:
				return __name__.split('''.''')[0]

def       __A (     )						->						logging.Logger:
				return logging.getLogger(_get_library_name())

def       __A (     )						->						None:
				global _default_handler

				with _lock:
								if _default_handler:
												# This library has already configured the library root logger.
												return
								__a	:  Optional[Any]         =					logging.StreamHandler()  # Set sys.stderr as stream.
								__a	:  Optional[Any]         =					sys.stderr.flush

								# Apply our default configuration to the library root logger.
								__a	:  str         =					_get_library_root_logger()
								library_root_logger.addHandler(_default_handler)
								library_root_logger.setLevel(_get_default_logging_level())
								__a	:  Optional[int]         =					False

def       __A (     )						->						None:
				global _default_handler

				with _lock:
								if not _default_handler:
												return

								__a	:  List[str]         =					_get_library_root_logger()
								library_root_logger.removeHandler(_default_handler)
								library_root_logger.setLevel(logging.NOTSET)
								__a	:  Any         =					None

def       __A (     )						->						Union[str, Any]:
				return log_levels

def       __A (     a_  :Optional[str] = None)						->						logging.Logger:

				if name is None:
								__a	:  List[Any]         =					_get_library_name()

				_configure_library_root_logger()
				return logging.getLogger(a_)

def       __A (     )						->						int:
				_configure_library_root_logger()
				return _get_library_root_logger().getEffectiveLevel()

def       __A (     a_  :int)						->						None:
				_configure_library_root_logger()
				_get_library_root_logger().setLevel(a_)

def       __A (     )						->						List[Any]:
				return set_verbosity(a_)

def       __A (     )						->						List[Any]:
				return set_verbosity(a_)

def       __A (     )						->						Union[str, Any]:
				return set_verbosity(a_)

def       __A (     )						->						Optional[Any]:
				return set_verbosity(a_)

def       __A (     )						->						None:
				_configure_library_root_logger()

				assert _default_handler is not None
				_get_library_root_logger().removeHandler(_default_handler)

def       __A (     )						->						None:
				_configure_library_root_logger()

				assert _default_handler is not None
				_get_library_root_logger().addHandler(_default_handler)

def       __A (     a_  :logging.Handler)						->						None:
				_configure_library_root_logger()

				assert handler is not None
				_get_library_root_logger().addHandler(a_)

def       __A (     a_  :logging.Handler)						->						None:
				_configure_library_root_logger()

				assert handler is not None and handler not in _get_library_root_logger().handlers
				_get_library_root_logger().removeHandler(a_)

def       __A (     )						->						None:
				_configure_library_root_logger()
				__a	:  Union[str, Any]         =					False

def       __A (     )						->						None:
				_configure_library_root_logger()
				__a	:  List[str]         =					True

def       __A (     )						->						None:
				__a	:  Optional[int]         =					_get_library_root_logger().handlers

				for handler in handlers:
								__a	:  Optional[Any]         =					logging.Formatter('''[%(levelname)s|%(filename)s:%(lineno)s] %(asctime)s >> %(message)s''')
								handler.setFormatter(a_)

def       __A (     )						->						None:
				__a	:  List[Any]         =					_get_library_root_logger().handlers

				for handler in handlers:
								handler.setFormatter(a_)

def       __A (     self  :Dict				,    *a_  :int				,    **a_  :List[str])						->						List[str]:
				__a	:  Any         =					os.getenv('''TRANSFORMERS_NO_ADVISORY_WARNINGS'''				,    a_)
				if no_advisory_warnings:
								return
				self.warning(*a_				,    **a_)


A	     =					warning_advice

@functools.lru_cache(a_)
def       __A (     self  :Dict				,    *a_  :Tuple				,    **a_  :Union[str, Any])						->						List[Any]:
				self.warning(*a_				,    **a_)


A	     =					warning_once




class 			__lowercase     :







					'''simple docstring'''




					def __init__(  self		,     *_UpperCAmelCase		,     **_UpperCAmelCase       ):  # pylint: disable=unused-argument
									__a	:  List[Any]         =					args[0] if args else None







					def __iter__(  self       ):
									return iter(self._iterator       )







					def __getattr__(  self		,     _UpperCAmelCase       ):

									def empty_fn(*_UpperCAmelCase		,     **_UpperCAmelCase       ):  # pylint: disable=unused-argument
													return

									return empty_fn







					def __enter__(  self       ):
									return self







					def __exit__(  self		,     _UpperCAmelCase		,     _UpperCAmelCase		,     _UpperCAmelCase       ):
									return






class 			__lowercase     :







					'''simple docstring'''




					def __call__(  self		,     *_UpperCAmelCase		,     **_UpperCAmelCase       ):
									if _tqdm_active:
													return tqdm_lib.tqdm(*_UpperCAmelCase		,     **_UpperCAmelCase       )
									else:
													return EmptyTqdm(*_UpperCAmelCase		,     **_UpperCAmelCase       )







					def 	_lowerCamelCase						(  self		,     *_UpperCAmelCase		,     **_UpperCAmelCase       ):
									__a	:  Optional[Any]         =					None
									if _tqdm_active:
													return tqdm_lib.tqdm.set_lock(*_UpperCAmelCase		,     **_UpperCAmelCase       )







					def 	_lowerCamelCase						(  self       ):
									if _tqdm_active:
													return tqdm_lib.tqdm.get_lock()






A	     =					_tqdm_cls()

def       __A (     )						->						bool:
				global _tqdm_active
				return bool(_tqdm_active)

def       __A (     )						->						str:
				global _tqdm_active
				__a	:  int         =					True
				hf_hub_utils.enable_progress_bars()






def       __A (     )						->						Tuple:
				global _tqdm_active
				__a	:  Optional[Any]         =					False
				hf_hub_utils.disable_progress_bars()






"""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
A	     =					'''src/transformers'''
A	     =					'''docs/source/en/tasks'''

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

				__a	:  int         =					start_index
				while not lines[end_index].startswith(a_):
								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.
A	     =					direct_transformers_import(TRANSFORMERS_PATH)

A	     =					{
    '''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`).
A	     =					{
    '''summarization.md''': ('''nllb''',),
    '''translation.md''': ('''nllb''',),
}

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

				__a	:  Optional[Any]         =					get_model_list_for_task(a_)

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

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