





import warnings

from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum

from ...processing_utils import ProcessorMixin


if is_torch_available():
    import torch





class  lowerCAmelCase							(       _UpperCAmelCase ):
  __lowerCamelCase		=      'char'
  __lowerCamelCase		=      'bpe'
  __lowerCamelCase		=      'wp'
_snake_case           =			(DecodeType.CHARACTER, DecodeType.BPE, DecodeType.WORDPIECE)





class  lowerCAmelCase							(       _UpperCAmelCase ):
  __lowerCamelCase		=      ['image_processor', 'char_tokenizer']
  __lowerCamelCase		=      'ViTImageProcessor'
  __lowerCamelCase		=      'MgpstrTokenizer'







  def __init__(      self  :List[str]   ,							_lowercase  :List[str]=None   ,							_lowercase  :str=None   ,							**_lowercase  :Optional[int] ):






     '''simple docstring'''





     lowercase__			       =  None
     if "feature_extractor" in kwargs:
        warnings.warn(
            "The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"
            " instead."   ,							SCREAMING_SNAKE_CASE_   ,							)
        lowercase__			       =  kwargs.pop("feature_extractor" )

     lowercase__			       =  image_processor if image_processor is not None else feature_extractor
     if image_processor is None:
        raise ValueError("You need to specify an `image_processor`." )
     if tokenizer is None:
        raise ValueError("You need to specify a `tokenizer`." )

     lowercase__			       =  tokenizer
     lowercase__			       =  AutoTokenizer.from_pretrained("gpt2" )
     lowercase__			       =  AutoTokenizer.from_pretrained("bert-base-uncased" )

     super().__init__(SCREAMING_SNAKE_CASE_   ,							SCREAMING_SNAKE_CASE_ )







  def __call__(      self  :int   ,							_lowercase  :List[Any]=None   ,							_lowercase  :int=None   ,							_lowercase  :Optional[Any]=None   ,							**_lowercase  :Tuple ):






     '''simple docstring'''





     if images is None and text is None:
        raise ValueError("You need to specify either an `images` or `text` input to process." )

     if images is not None:
        lowercase__			       =  self.image_processor(SCREAMING_SNAKE_CASE_   ,							return_tensors=SCREAMING_SNAKE_CASE_   ,							**SCREAMING_SNAKE_CASE_ )
     if text is not None:
        lowercase__			       =  self.char_tokenizer(SCREAMING_SNAKE_CASE_   ,							return_tensors=SCREAMING_SNAKE_CASE_   ,							**SCREAMING_SNAKE_CASE_ )

     if text is None:
        return inputs
     elif images is None:
        return encodings
     else:
        lowercase__			       =  encodings["""input_ids"""]
        return inputs







  def   UpperCAmelCase					(      self  :List[str]   ,							_lowercase  :str ):






     '''simple docstring'''





     lowercase__			       =  sequences
     lowercase__			       =  char_preds.size(0 )

     lowercase__			       =  self._decode_helper(SCREAMING_SNAKE_CASE_   ,							"char" )
     lowercase__			       =  self._decode_helper(SCREAMING_SNAKE_CASE_   ,							"bpe" )
     lowercase__			       =  self._decode_helper(SCREAMING_SNAKE_CASE_   ,							"wp" )

     lowercase__			       =  []
     lowercase__			       =  []
     for i in range(SCREAMING_SNAKE_CASE_ ):
        lowercase__			       =  [char_scores[i], bpe_scores[i], wp_scores[i]]
        lowercase__			       =  [char_strs[i], bpe_strs[i], wp_strs[i]]
        lowercase__			       =  scores.index(max(SCREAMING_SNAKE_CASE_ ) )
        final_strs.append(strs[max_score_index] )
        final_scores.append(scores[max_score_index] )

     lowercase__			       =  {}
     lowercase__			       =  final_strs
     lowercase__			       =  final_scores
     lowercase__			       =  char_strs
     lowercase__			       =  bpe_strs
     lowercase__			       =  wp_strs
     return out







  def   UpperCAmelCase					(      self  :Any   ,							_lowercase  :int   ,							_lowercase  :Optional[int] ):






     '''simple docstring'''





     if format == DecodeType.CHARACTER:
        lowercase__			       =  self.char_decode
        lowercase__			       =  1
        lowercase__			       =  """[s]"""
     elif format == DecodeType.BPE:
        lowercase__			       =  self.bpe_decode
        lowercase__			       =  2
        lowercase__			       =  """#"""
     elif format == DecodeType.WORDPIECE:
        lowercase__			       =  self.wp_decode
        lowercase__			       =  1_02
        lowercase__			       =  """[SEP]"""
     else:
        raise ValueError(f'''Format {format} is not supported.''' )

     lowercase__			       =  [], []
     lowercase__			       =  pred_logits.size(0 )
     lowercase__			       =  pred_logits.size(1 )
     lowercase__			       =  pred_logits.topk(1   ,							dim=-1   ,							largest=SCREAMING_SNAKE_CASE_   ,							sorted=SCREAMING_SNAKE_CASE_ )
     lowercase__			       =  preds_index.view(-1   ,							SCREAMING_SNAKE_CASE_ )[:, 1:]
     lowercase__			       =  decoder(SCREAMING_SNAKE_CASE_ )
     lowercase__			       =  torch.nn.functional.softmax(SCREAMING_SNAKE_CASE_   ,							dim=2 ).max(dim=2 )
     lowercase__			       =  preds_max_prob[:, 1:]

     for index in range(SCREAMING_SNAKE_CASE_ ):
        lowercase__			       =  preds_str[index].find(SCREAMING_SNAKE_CASE_ )
        lowercase__			       =  preds_str[index][:pred_eos]
        lowercase__			       =  preds_index[index].cpu().tolist()
        lowercase__			       =  pred_index.index(SCREAMING_SNAKE_CASE_ ) if eos_token in pred_index else -1
        lowercase__			       =  preds_max_prob[index][: pred_eos_index + 1]
        lowercase__			       =  pred_max_prob.cumprod(dim=0 )[-1] if pred_max_prob.nelement() != 0 else 0.0
        dec_strs.append(SCREAMING_SNAKE_CASE_ )
        conf_scores.append(SCREAMING_SNAKE_CASE_ )

     return dec_strs, conf_scores







  def   UpperCAmelCase					(      self  :Any   ,							_lowercase  :List[Any] ):






     '''simple docstring'''





     lowercase__			       =  [seq.replace(" "   ,							"" ) for seq in self.char_tokenizer.batch_decode(SCREAMING_SNAKE_CASE_ )]
     return decode_strs







  def   UpperCAmelCase					(      self  :Union[str, Any]   ,							_lowercase  :List[Any] ):






     '''simple docstring'''





     return self.bpe_tokenizer.batch_decode(SCREAMING_SNAKE_CASE_ )







  def   UpperCAmelCase					(      self  :Union[str, Any]   ,							_lowercase  :List[Any] ):






     '''simple docstring'''





     lowercase__			       =  [seq.replace(" "   ,							"" ) for seq in self.wp_tokenizer.batch_decode(SCREAMING_SNAKE_CASE_ )]
     return decode_strs













from __future__ import annotations


def _A       (   __magic_name__  , __magic_name__	):
   lowercase__			       =  []
   create_all_state(1  , __magic_name__  , __magic_name__  , []  , __magic_name__	)
   return result


def _A       (   __magic_name__  , __magic_name__  , __magic_name__  , __magic_name__  , __magic_name__  , ):
   if level == 0:
      total_list.append(current_list[:]	)
      return

   for i in range(__magic_name__  , total_number - level + 2	):
      current_list.append(__magic_name__	)
      create_all_state(i + 1  , __magic_name__  , level - 1  , __magic_name__  , __magic_name__	)
      current_list.pop()


def _A       (   __magic_name__	):
   for i in total_list:
      print(*__magic_name__	)


if __name__ == "__main__":
  _snake_case           =			4
  _snake_case           =			2
  _snake_case           =			generate_all_combinations(n, k)
  print_all_state(total_list)






