



"""simple docstring"""




from typing import Dict

from .base import GenericTensor, Pipeline






class      UpperCAmelCase_  (    _UpperCamelCase						):



      def 						snake_case_ (					self					:     Tuple					,     A					:     List[Any]=None					,     A					:     List[str]=None					,     A					:     List[Any]=None					,     **A					:     str						):
           if tokenize_kwargs is None:
                _UpperCAmelCase      :     str        =   {}

           if truncation is not None:
                if "truncation" in tokenize_kwargs:
                     raise ValueError(
                         "truncation parameter defined twice (given as keyword argument as well as in tokenize_kwargs)"						)
                _UpperCAmelCase      :     Any        =   truncation

           _UpperCAmelCase      :     List[Any]        =   tokenize_kwargs

           _UpperCAmelCase      :     Optional[int]        =   {}
           if return_tensors is not None:
                _UpperCAmelCase      :     Optional[Any]        =   return_tensors

           return preprocess_params, {}, postprocess_params



      def 						snake_case_ (					self					:     Union[str, Any]					,     A					:     int					,     **A					:     Tuple						):
           _UpperCAmelCase      :     Optional[Any]        =   self.framework
           _UpperCAmelCase      :     List[str]        =   self.tokenizer(A					,     return_tensors=A					,     **A						)
           return model_inputs



      def 						snake_case_ (					self					:     Union[str, Any]					,     A					:     List[Any]						):
           _UpperCAmelCase      :     List[Any]        =   self.model(**A						)
           return model_outputs



      def 						snake_case_ (					self					:     int					,     A					:     int					,     A					:     Union[str, Any]=False						):
           # [0] is the first available tensor, logits or last_hidden_state.
           if return_tensors:
                return model_outputs[0]
           if self.framework == "pt":
                return model_outputs[0].tolist()
           elif self.framework == "tf":
                return model_outputs[0].numpy().tolist()



      def __call__(					self					:     Tuple					,     *A					:     List[Any]					,     **A					:     int						):
           return super().__call__(*A					,     **A						)





"""simple docstring"""




import importlib
import inspect
import os
import re


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
_lowerCAmelCase    : Dict							=							"src/transformers"


# This is to make sure the transformers module imported is the one in the repo.
_lowerCAmelCase    : List[Any]							=							importlib.util.spec_from_file_location(
    "transformers",
    os.path.join(PATH_TO_TRANSFORMERS, "__init__.py"),
    submodule_search_locations=[PATH_TO_TRANSFORMERS],
)
_lowerCAmelCase    : Tuple							=							spec.loader.load_module()

_lowerCAmelCase    : Tuple							=							transformers.models.auto.configuration_auto.CONFIG_MAPPING

# Regex pattern used to find the checkpoint mentioned in the docstring of `config_class`.
# For example, `[bert-base-uncased](https://huggingface.co/bert-base-uncased)`
_lowerCAmelCase    : Optional[int]							=							re.compile("\[(.+?)\]\((https://huggingface\.co/.+?)\)")


_lowerCAmelCase    : Optional[int]							=							{
    "CLIPConfigMixin",
    "DecisionTransformerConfigMixin",
    "EncoderDecoderConfigMixin",
    "RagConfigMixin",
    "SpeechEncoderDecoderConfigMixin",
    "VisionEncoderDecoderConfigMixin",
    "VisionTextDualEncoderConfigMixin",
}

def 						__snake_case						(				)  ->       Dict:





     '''simple docstring'''

     _UpperCAmelCase      :     List[str]        =   []

     for config_class in list(CONFIG_MAPPING.values()    ):
          _UpperCAmelCase      :     Union[str, Any]        =   False

          # source code of `config_class`
          _UpperCAmelCase      :     Optional[int]        =   inspect.getsource(SCREAMING_SNAKE_CASE__    )
          _UpperCAmelCase      :     List[Any]        =   _re_checkpoint.findall(SCREAMING_SNAKE_CASE__    )

          for checkpoint in checkpoints:
               # Each `checkpoint` is a tuple of a checkpoint name and a checkpoint link.
               # For example, `('bert-base-uncased', 'https://huggingface.co/bert-base-uncased')`
               _UpperCAmelCase    ,	_UpperCAmelCase      :     List[Any]        =   checkpoint

               # verify the checkpoint name corresponds to the checkpoint link
               _UpperCAmelCase      :     Optional[Any]        =   f'https://huggingface.co/{ckpt_name}'
               if ckpt_link == ckpt_link_from_name:
                    _UpperCAmelCase      :     Optional[Any]        =   True
                    break

          _UpperCAmelCase      :     int        =   config_class.__name__
          if not checkpoint_found and name not in CONFIG_CLASSES_TO_IGNORE_FOR_DOCSTRING_CHECKPOINT_CHECK:
               configs_without_checkpoint.append(SCREAMING_SNAKE_CASE__    )

     if len(SCREAMING_SNAKE_CASE__    ) > 0:
          _UpperCAmelCase      :     List[str]        =   "\n".join(sorted(SCREAMING_SNAKE_CASE__    )    )
          raise ValueError(f'The following configurations don\'t contain any valid checkpoint:\n{message}'    )


if __name__ == "__main__":
 check_config_docstrings_have_checkpoints()
