"""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      :		Optional[Any]           =   'src/transformers'
_a      :		Any           =   'docs/source/en/tasks'





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

  _lowerCAmelCase						:       List[Any]  			=     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.
_a      :		Union[str, Any]           =   direct_transformers_import(TRANSFORMERS_PATH)

_a      :		Optional[int]           =   {
    '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      :		Tuple           =   {
    'summarization.md': ('nllb',),
    'translation.md': ('nllb',),
}





def 							SCREAMING_SNAKE_CASE     (			_lowerCamelCase						:       Dict	)       ->      Optional[int]:
  _lowerCAmelCase						:       int  			=     TASK_GUIDE_TO_MODELS[task_guide]
  _lowerCAmelCase						:       Any  			=     SPECIAL_TASK_GUIDE_TO_MODEL_TYPES.get(_lowerCamelCase			,set()	)
  _lowerCAmelCase						:       List[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 							SCREAMING_SNAKE_CASE     (			_lowerCamelCase						:       Union[str, Any]			,_lowerCamelCase						:       Optional[Any]=False	)       ->      Dict:
  _lowerCAmelCase			,	_lowerCAmelCase			,	_lowerCAmelCase			,	_lowerCAmelCase						:       Optional[Any]  			=     _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-->"""			,)

  _lowerCAmelCase						:       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__":
     _a      :		List[str]           =   argparse.ArgumentParser()
     parser.add_argument('--fix_and_overwrite', action='store_true', help='Whether to fix inconsistencies.')
     _a      :		Dict           =   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"""





from math import cos, sin, sqrt, tau

from audio_filters.iir_filter import IIRFilter







def 	__a     (		__lowerCamelCase,		__lowerCamelCase,		__lowerCamelCase = 1 / sqrt(2  )  ):
   UpperCAmelCase_					:					int			     =    tau * frequency / samplerate
   UpperCAmelCase_					:					List[str]			     =    sin(__lowerCamelCase  )
   UpperCAmelCase_					:					int			     =    cos(__lowerCamelCase  )
   UpperCAmelCase_					:					Optional[Any]			     =    _sin / (2 * q_factor)

   UpperCAmelCase_					:					int			     =    (1 - _cos) / 2
   UpperCAmelCase_					:					Optional[Any]			     =    1 - _cos

   UpperCAmelCase_					:					int			     =    1 + alpha
   UpperCAmelCase_					:					Dict			     =    -2 * _cos
   UpperCAmelCase_					:					Tuple			     =    1 - alpha

   UpperCAmelCase_					:					Dict			     =    IIRFilter(2  )
   filt.set_coefficients([aa, aa, aa],		[ba, ba, ba]  )
   return filt







def 	__a     (		__lowerCamelCase,		__lowerCamelCase,		__lowerCamelCase = 1 / sqrt(2  )  ):
   UpperCAmelCase_					:					Dict			     =    tau * frequency / samplerate
   UpperCAmelCase_					:					Tuple			     =    sin(__lowerCamelCase  )
   UpperCAmelCase_					:					Any			     =    cos(__lowerCamelCase  )
   UpperCAmelCase_					:					List[str]			     =    _sin / (2 * q_factor)

   UpperCAmelCase_					:					List[Any]			     =    (1 + _cos) / 2
   UpperCAmelCase_					:					Optional[int]			     =    -1 - _cos

   UpperCAmelCase_					:					Union[str, Any]			     =    1 + alpha
   UpperCAmelCase_					:					Optional[int]			     =    -2 * _cos
   UpperCAmelCase_					:					Tuple			     =    1 - alpha

   UpperCAmelCase_					:					List[str]			     =    IIRFilter(2  )
   filt.set_coefficients([aa, aa, aa],		[ba, ba, ba]  )
   return filt







def 	__a     (		__lowerCamelCase,		__lowerCamelCase,		__lowerCamelCase = 1 / sqrt(2  )  ):
   UpperCAmelCase_					:					Union[str, Any]			     =    tau * frequency / samplerate
   UpperCAmelCase_					:					str			     =    sin(__lowerCamelCase  )
   UpperCAmelCase_					:					Tuple			     =    cos(__lowerCamelCase  )
   UpperCAmelCase_					:					List[Any]			     =    _sin / (2 * q_factor)

   UpperCAmelCase_					:					Any			     =    _sin / 2
   UpperCAmelCase_					:					Union[str, Any]			     =    0
   UpperCAmelCase_					:					Tuple			     =    -ba

   UpperCAmelCase_					:					Optional[Any]			     =    1 + alpha
   UpperCAmelCase_					:					Dict			     =    -2 * _cos
   UpperCAmelCase_					:					Optional[int]			     =    1 - alpha

   UpperCAmelCase_					:					List[str]			     =    IIRFilter(2  )
   filt.set_coefficients([aa, aa, aa],		[ba, ba, ba]  )
   return filt







def 	__a     (		__lowerCamelCase,		__lowerCamelCase,		__lowerCamelCase = 1 / sqrt(2  )  ):
   UpperCAmelCase_					:					Any			     =    tau * frequency / samplerate
   UpperCAmelCase_					:					Any			     =    sin(__lowerCamelCase  )
   UpperCAmelCase_					:					Optional[int]			     =    cos(__lowerCamelCase  )
   UpperCAmelCase_					:					str			     =    _sin / (2 * q_factor)

   UpperCAmelCase_					:					List[str]			     =    1 - alpha
   UpperCAmelCase_					:					str			     =    -2 * _cos
   UpperCAmelCase_					:					Any			     =    1 + alpha

   UpperCAmelCase_					:					Tuple			     =    IIRFilter(2  )
   filt.set_coefficients([ba, ba, ba],		[ba, ba, ba]  )
   return filt







def 	__a     (		__lowerCamelCase,		__lowerCamelCase,		__lowerCamelCase,		__lowerCamelCase = 1 / sqrt(2  ),		):
   UpperCAmelCase_					:					Dict			     =    tau * frequency / samplerate
   UpperCAmelCase_					:					Union[str, Any]			     =    sin(__lowerCamelCase  )
   UpperCAmelCase_					:					int			     =    cos(__lowerCamelCase  )
   UpperCAmelCase_					:					Optional[int]			     =    _sin / (2 * q_factor)
   UpperCAmelCase_					:					List[str]			     =    10 ** (gain_db / 40)

   UpperCAmelCase_					:					List[Any]			     =    1 + alpha * big_a
   UpperCAmelCase_					:					Tuple			     =    -2 * _cos
   UpperCAmelCase_					:					Tuple			     =    1 - alpha * big_a
   UpperCAmelCase_					:					str			     =    1 + alpha / big_a
   UpperCAmelCase_					:					List[str]			     =    -2 * _cos
   UpperCAmelCase_					:					List[str]			     =    1 - alpha / big_a

   UpperCAmelCase_					:					Tuple			     =    IIRFilter(2  )
   filt.set_coefficients([aa, aa, aa],		[ba, ba, ba]  )
   return filt







def 	__a     (		__lowerCamelCase,		__lowerCamelCase,		__lowerCamelCase,		__lowerCamelCase = 1 / sqrt(2  ),		):
   UpperCAmelCase_					:					str			     =    tau * frequency / samplerate
   UpperCAmelCase_					:					int			     =    sin(__lowerCamelCase  )
   UpperCAmelCase_					:					Optional[Any]			     =    cos(__lowerCamelCase  )
   UpperCAmelCase_					:					Tuple			     =    _sin / (2 * q_factor)
   UpperCAmelCase_					:					List[Any]			     =    10 ** (gain_db / 40)
   UpperCAmelCase_					:					Tuple			     =    (big_a + 1) - (big_a - 1) * _cos
   UpperCAmelCase_					:					int			     =    (big_a + 1) + (big_a - 1) * _cos
   UpperCAmelCase_					:					Optional[Any]			     =    (big_a - 1) - (big_a + 1) * _cos
   UpperCAmelCase_					:					Optional[int]			     =    (big_a - 1) + (big_a + 1) * _cos
   UpperCAmelCase_					:					Dict			     =    2 * sqrt(__lowerCamelCase  ) * alpha

   UpperCAmelCase_					:					List[str]			     =    big_a * (pmc + aaa)
   UpperCAmelCase_					:					int			     =    2 * big_a * mpc
   UpperCAmelCase_					:					int			     =    big_a * (pmc - aaa)
   UpperCAmelCase_					:					Dict			     =    ppmc + aaa
   UpperCAmelCase_					:					Any			     =    -2 * pmpc
   UpperCAmelCase_					:					List[str]			     =    ppmc - aaa

   UpperCAmelCase_					:					List[Any]			     =    IIRFilter(2  )
   filt.set_coefficients([aa, aa, aa],		[ba, ba, ba]  )
   return filt







def 	__a     (		__lowerCamelCase,		__lowerCamelCase,		__lowerCamelCase,		__lowerCamelCase = 1 / sqrt(2  ),		):
   UpperCAmelCase_					:					int			     =    tau * frequency / samplerate
   UpperCAmelCase_					:					Optional[Any]			     =    sin(__lowerCamelCase  )
   UpperCAmelCase_					:					Optional[Any]			     =    cos(__lowerCamelCase  )
   UpperCAmelCase_					:					Optional[Any]			     =    _sin / (2 * q_factor)
   UpperCAmelCase_					:					Tuple			     =    10 ** (gain_db / 40)
   UpperCAmelCase_					:					Tuple			     =    (big_a + 1) - (big_a - 1) * _cos
   UpperCAmelCase_					:					Optional[Any]			     =    (big_a + 1) + (big_a - 1) * _cos
   UpperCAmelCase_					:					List[Any]			     =    (big_a - 1) - (big_a + 1) * _cos
   UpperCAmelCase_					:					Any			     =    (big_a - 1) + (big_a + 1) * _cos
   UpperCAmelCase_					:					Dict			     =    2 * sqrt(__lowerCamelCase  ) * alpha

   UpperCAmelCase_					:					Any			     =    big_a * (ppmc + aaa)
   UpperCAmelCase_					:					Union[str, Any]			     =    -2 * big_a * pmpc
   UpperCAmelCase_					:					Dict			     =    big_a * (ppmc - aaa)
   UpperCAmelCase_					:					Optional[int]			     =    pmc + aaa
   UpperCAmelCase_					:					Union[str, Any]			     =    2 * mpc
   UpperCAmelCase_					:					int			     =    pmc - aaa

   UpperCAmelCase_					:					Union[str, Any]			     =    IIRFilter(2  )
   filt.set_coefficients([aa, aa, aa],		[ba, ba, ba]  )
   return filt


