'''simple docstring'''




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     a__      (   UpperCAmelCase__ ):
     lowerCamelCase  :     Tuple							="char"
     lowerCamelCase  :     List[str]							="bpe"
     lowerCamelCase  :     Tuple							="wp"
__UpperCAmelCase     							=(DecodeType.CHARACTER, DecodeType.BPE, DecodeType.WORDPIECE)




class     a__      (   UpperCAmelCase__ ):
     lowerCamelCase  :     List[str]							=["image_processor", "char_tokenizer"]
     lowerCamelCase  :     List[Any]							="ViTImageProcessor"
     lowerCamelCase  :     Tuple							="MgpstrTokenizer"






     def __init__( self		:		int  ,				a		:		str=None  ,				a		:		int=None  ,				**a		:		List[Any]    ):





         """simple docstring"""



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

         __lowerCamelCase		=  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`.'''    )

         __lowerCamelCase		=  tokenizer
         __lowerCamelCase		=  AutoTokenizer.from_pretrained('''gpt2'''    )
         __lowerCamelCase		=  AutoTokenizer.from_pretrained('''bert-base-uncased'''    )

         super().__init__(a  ,				a    )






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





         """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:
             __lowerCamelCase		=  self.image_processor(a  ,				return_tensors=a  ,				**a    )
         if text is not None:
             __lowerCamelCase		=  self.char_tokenizer(a  ,				return_tensors=a  ,				**a    )

         if text is None:
             return inputs
         elif images is None:
             return encodings
         else:
             __lowerCamelCase		=  encodings['''input_ids''']
             return inputs






     def    SCREAMING_SNAKE_CASE__   ( self		:		Dict  ,				a		:		Optional[Any]    ):





         """simple docstring"""



         __lowerCamelCase	,  __lowerCamelCase	,  __lowerCamelCase		=  sequences
         __lowerCamelCase		=  char_preds.size(0    )

         __lowerCamelCase	,  __lowerCamelCase		=  self._decode_helper(a  ,				'''char'''    )
         __lowerCamelCase	,  __lowerCamelCase		=  self._decode_helper(a  ,				'''bpe'''    )
         __lowerCamelCase	,  __lowerCamelCase		=  self._decode_helper(a  ,				'''wp'''    )

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

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






     def    SCREAMING_SNAKE_CASE__   ( self		:		Dict  ,				a		:		Tuple  ,				a		:		List[str]    ):





         """simple docstring"""



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

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

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

         return dec_strs, conf_scores






     def    SCREAMING_SNAKE_CASE__   ( self		:		Union[str, Any]  ,				a		:		Tuple    ):





         """simple docstring"""



         __lowerCamelCase		=  [seq.replace(''' '''  ,				''''''    ) for seq in self.char_tokenizer.batch_decode(a    )]
         return decode_strs






     def    SCREAMING_SNAKE_CASE__   ( self		:		Union[str, Any]  ,				a		:		Union[str, Any]    ):





         """simple docstring"""



         return self.bpe_tokenizer.batch_decode(a    )






     def    SCREAMING_SNAKE_CASE__   ( self		:		Dict  ,				a		:		Tuple    ):





         """simple docstring"""



         __lowerCamelCase		=  [seq.replace(''' '''  ,				''''''    ) for seq in self.wp_tokenizer.batch_decode(a    )]
         return decode_strs







"""simple docstring"""





from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar

__A											=		TypeVar("""KEY""")
__A											=		TypeVar("""VAL""")






@dataclass(frozen=a  ,   slots=a       )
class 					_lowerCAmelCase   (     Generic[KEY, VAL]       ):
       """simple docstring"""




       __magic_name__     :KEY
       __magic_name__     :VAL






class 					_lowerCAmelCase   (     _Item       ):
       """simple docstring"""




       def __init__(    self      ):



         '''simple docstring'''

         super().__init__(__UpperCAmelCase    , __UpperCAmelCase      )






       def __bool__(    self      ):



         '''simple docstring'''

         return False






__A											=		_DeletedItem()






class 					_lowerCAmelCase   (     MutableMapping[KEY, VAL]       ):
       """simple docstring"""




       def __init__(    self    , __UpperCAmelCase = 8    , __UpperCAmelCase = 0.75      ):



         '''simple docstring'''

         lowerCAmelCase__			:List[str]											=							initial_block_size
         lowerCAmelCase__			:list[_Item | None]											=							[None] * initial_block_size
         assert 0.0 < capacity_factor < 1.0
         lowerCAmelCase__			:Tuple											=							capacity_factor
         lowerCAmelCase__			:str											=							0






       def      snake_case						(    self    , __UpperCAmelCase      ):



         '''simple docstring'''

         return hash(__UpperCAmelCase      ) % len(self._buckets      )






       def      snake_case						(    self    , __UpperCAmelCase      ):



         '''simple docstring'''

         return (ind + 1) % len(self._buckets      )






       def      snake_case						(    self    , __UpperCAmelCase    , __UpperCAmelCase    , __UpperCAmelCase      ):



         '''simple docstring'''

         lowerCAmelCase__			:Any											=							self._buckets[ind]
         if not stored:
           lowerCAmelCase__			:Dict											=							_Item(__UpperCAmelCase    , __UpperCAmelCase      )
           self._len += 1
           return True
         elif stored.key == key:
           lowerCAmelCase__			:Optional[Any]											=							_Item(__UpperCAmelCase    , __UpperCAmelCase      )
           return True
         else:
           return False






       def      snake_case						(    self      ):



         '''simple docstring'''

         lowerCAmelCase__			:int											=							len(self._buckets      ) * self._capacity_factor
         return len(self      ) >= int(__UpperCAmelCase      )






       def      snake_case						(    self      ):



         '''simple docstring'''

         if len(self._buckets      ) <= self._initial_block_size:
           return False
         lowerCAmelCase__			:Optional[Any]											=							len(self._buckets      ) * self._capacity_factor / 2
         return len(self      ) < limit






       def      snake_case						(    self    , __UpperCAmelCase      ):



         '''simple docstring'''

         lowerCAmelCase__			:Optional[int]											=							self._buckets
         lowerCAmelCase__			:Tuple											=							[None] * new_size
         lowerCAmelCase__			:List[Any]											=							0
         for item in old_buckets:
           if item:
             self._add_item(item.key    , item.val      )






       def      snake_case						(    self      ):



         '''simple docstring'''

         self._resize(len(self._buckets      ) * 2      )






       def      snake_case						(    self      ):



         '''simple docstring'''

         self._resize(len(self._buckets      ) // 2      )






       def      snake_case						(    self    , __UpperCAmelCase      ):



         '''simple docstring'''

         lowerCAmelCase__			:Optional[Any]											=							self._get_bucket_index(__UpperCAmelCase      )
         for _ in range(len(self._buckets      )      ):
           yield ind
           lowerCAmelCase__			:Tuple											=							self._get_next_ind(__UpperCAmelCase      )






       def      snake_case						(    self    , __UpperCAmelCase    , __UpperCAmelCase      ):



         '''simple docstring'''

         for ind in self._iterate_buckets(__UpperCAmelCase      ):
           if self._try_set(__UpperCAmelCase    , __UpperCAmelCase    , __UpperCAmelCase      ):
             break






       def __setitem__(    self    , __UpperCAmelCase    , __UpperCAmelCase      ):



         '''simple docstring'''

         if self._is_full():
           self._size_up()

         self._add_item(__UpperCAmelCase    , __UpperCAmelCase      )






       def __delitem__(    self    , __UpperCAmelCase      ):



         '''simple docstring'''

         for ind in self._iterate_buckets(__UpperCAmelCase      ):
           lowerCAmelCase__			:int											=							self._buckets[ind]
           if item is None:
             raise KeyError(__UpperCAmelCase      )
           if item is _deleted:
             continue
           if item.key == key:
             lowerCAmelCase__			:List[str]											=							_deleted
             self._len -= 1
             break
         if self._is_sparse():
           self._size_down()






       def __getitem__(    self    , __UpperCAmelCase      ):



         '''simple docstring'''

         for ind in self._iterate_buckets(__UpperCAmelCase      ):
           lowerCAmelCase__			:str											=							self._buckets[ind]
           if item is None:
             break
           if item is _deleted:
             continue
           if item.key == key:
             return item.val
         raise KeyError(__UpperCAmelCase      )






       def __len__(    self      ):



         '''simple docstring'''

         return self._len






       def __iter__(    self      ):



         '''simple docstring'''

         yield from (item.key for item in self._buckets if item)






       def __repr__(    self      ):



         '''simple docstring'''

         lowerCAmelCase__			:Tuple											=							' ,'.join(
             F"{item.key}: {item.val}" for item in self._buckets if item      )
         return F"HashMap({val_string})"
