



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
__snake_case						:Optional[Any]      		=     '''src/transformers'''
__snake_case						:List[Any]      		=     '''docs/source/en/tasks'''





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

    __a						       =				start_index
    while not lines[end_index].startswith(_UpperCAmelCase				):
        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.
__snake_case						:Dict      		=     direct_transformers_import(TRANSFORMERS_PATH)

__snake_case						:List[str]      		=     {
    '''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`).
__snake_case						:Optional[int]      		=     {
    '''summarization.md''': ('''nllb''',),
    '''translation.md''': ('''nllb''',),
}





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

    __a						       =				get_model_list_for_task(_UpperCAmelCase				)

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

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










from importlib import import_module

from .logging import get_logger


A__								=						get_logger(__name__)


class       a							:



		def __init__(     self     :Optional[int]   ,__lowercase     :List[str]   ,__lowercase     :Any=None  ):
						snake_case__	:      List[str]     		=	attrs or []
						if module is not None:
										for key in module.__dict__:
														if key in attrs or not key.startswith('''__'''  ):
																		setattr(self   ,__lowercase   ,getattr(__lowercase   ,__lowercase  )  )
						snake_case__	:      Optional[Any]     		=	module._original_module if isinstance(__lowercase   ,_PatchedModuleObj  ) else module


class       a							:
		__lowerCAmelCase	:    Any											=					[]



		def __init__(     self     :List[str]   ,__lowercase     :Optional[Any]   ,__lowercase     :str   ,__lowercase     :Dict   ,__lowercase     :Any=None  ):
						snake_case__	:      Dict     		=	obj
						snake_case__	:      Dict     		=	target
						snake_case__	:      List[str]     		=	new
						snake_case__	:      int     		=	target.split('''.'''  )[0]
						snake_case__	:      List[str]     		=	{}
						snake_case__	:      Any     		=	attrs or []



		def __enter__(     self     :Tuple  ):
						*snake_case__		, snake_case__	:      str     		=	self.target.split('''.'''  )

						# Patch modules:
						# it's used to patch attributes of submodules like "os.path.join";
						# in this case we need to patch "os" and "os.path"

						for i in range(len(__lowercase  )  ):
										try:
														snake_case__	:      Any     		=	import_module('''.'''.join(submodules[: i + 1]  )  )
										except ModuleNotFoundError:
														continue
										# We iterate over all the globals in self.obj in case we find "os" or "os.path"
										for attr in self.obj.__dir__():
														snake_case__	:      Optional[int]     		=	getattr(self.obj   ,__lowercase  )
														# We don't check for the name of the global, but rather if its value *is* "os" or "os.path".
														# This allows to patch renamed modules like "from os import path as ospath".
														if obj_attr is submodule or (
														    (isinstance(__lowercase   ,_PatchedModuleObj  ) and obj_attr._original_module is submodule)
														):
																		snake_case__	:      List[Any]     		=	obj_attr
																		# patch at top level
																		setattr(self.obj   ,__lowercase   ,_PatchedModuleObj(__lowercase   ,attrs=self.attrs  )  )
																		snake_case__	:      List[Any]     		=	getattr(self.obj   ,__lowercase  )
																		# construct lower levels patches
																		for key in submodules[i + 1 :]:
																						setattr(__lowercase   ,__lowercase   ,_PatchedModuleObj(getattr(__lowercase   ,__lowercase   ,__lowercase  )   ,attrs=self.attrs  )  )
																						snake_case__	:      List[Any]     		=	getattr(__lowercase   ,__lowercase  )
																		# finally set the target attribute
																		setattr(__lowercase   ,__lowercase   ,self.new  )

        # Patch attribute itself:
        # it's used for builtins like "open",
        # and also to patch "os.path.join" we may also need to patch "join"
        # itself if it was imported as "from os.path import join".

						if submodules:  # if it's an attribute of a submodule like "os.path.join"
										try:
														snake_case__	:      int     		=	getattr(import_module('''.'''.join(__lowercase  )  )   ,__lowercase  )
										except (AttributeError, ModuleNotFoundError):
														return
										# We iterate over all the globals in self.obj in case we find "os.path.join"
										for attr in self.obj.__dir__():
														# We don't check for the name of the global, but rather if its value *is* "os.path.join".
														# This allows to patch renamed attributes like "from os.path import join as pjoin".
														if getattr(self.obj   ,__lowercase  ) is attr_value:
																		snake_case__	:      str     		=	getattr(self.obj   ,__lowercase  )
																		setattr(self.obj   ,__lowercase   ,self.new  )
						elif target_attr in globals()["__builtins__"]:  # if it'a s builtin like "open"
										snake_case__	:      str     		=	globals()['''__builtins__'''][target_attr]
										setattr(self.obj   ,__lowercase   ,self.new  )
						else:
										raise RuntimeError(F"""Tried to patch attribute {target_attr} instead of a submodule."""  )



		def __exit__(     self     :Tuple   ,*__lowercase     :Optional[int]  ):
						for attr in list(self.original  ):
										setattr(self.obj   ,__lowercase   ,self.original.pop(__lowercase  )  )



		def 	__lowerCamelCase			(     self     :Tuple  ):
						self.__enter__()
						self._active_patches.append(self  )






		def 	__lowerCamelCase			(     self     :Dict  ):
						try:
										self._active_patches.remove(self  )
						except ValueError:
										# If the patch hasn't been started this will fail
										return None

						return self.__exit__()

