import collections
import os
from typing import List, Optional, Tuple

from transformers.utils import is_jieba_available, requires_backends


if is_jieba_available():
      import jieba

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


UpperCamelCase  							=						logging.get_logger(__name__)

UpperCamelCase  							=						{'''vocab_file''': '''vocab.txt'''}

UpperCamelCase  							=						{
    '''vocab_file''': {
        '''openbmb/cpm-ant-10b''': '''https://huggingface.co/openbmb/cpm-ant-10b/blob/main/vocab.txt''',
    },
}

UpperCamelCase  							=						{
    '''openbmb/cpm-ant-10b''': 1024,
}

def 			lowercase_				(			_lowerCamelCase							:       int):
    lowercase__ :   Tuple    					=				collections.OrderedDict()
    with open(_lowerCamelCase		,	"r"		,	encoding="utf-8") as reader:
        lowercase__ :   Tuple    					=				reader.readlines()
    for index, token in enumerate(_lowerCamelCase):
        lowercase__ :   Optional[int]    					=				token.rstrip("\n")
        lowercase__ :   Optional[int]    					=				index
    return vocab



class   snake_case_       (		__A       ):






   def __init__(      self				:     str	,						lowercase_				:     int	,						lowercase_				:     str="<unk>"	,						lowercase_				:     List[Any]=2_00  )					->						Union[str, Any]:
       lowercase__ :   Any    					=				vocab
       lowercase__ :   int    					=				unk_token
       lowercase__ :   Union[str, Any]    					=				max_input_chars_per_word







   def       __UpperCamelCase     (      self				:     Dict	,						lowercase_				:     Any  )					->						List[Any]:
       lowercase__ :   List[str]    					=				list(lowercase_  )
       if len(lowercase_  ) > self.max_input_chars_per_word:
           return [self.unk_token]

       lowercase__ :   int    					=				0
       lowercase__ :   Union[str, Any]    					=				[]
       while start < len(lowercase_  ):
           lowercase__ :   int    					=				len(lowercase_  )
           lowercase__ :   List[Any]    					=				None
           while start < end:
               lowercase__ :   int    					=				"".join(chars[start:end]  )
               if substr in self.vocab:
                   lowercase__ :   Tuple    					=				substr
                   break
               end -= 1
           if cur_substr is None:
               sub_tokens.append(self.unk_token  )
               start += 1
           else:
               sub_tokens.append(lowercase_  )
               lowercase__ :   Dict    					=				end

       return sub_tokens



class   snake_case_       (		__A       ):
   __A	:		List[str]         =				VOCAB_FILES_NAMES
   __A	:		str         =				PRETRAINED_VOCAB_FILES_MAP
   __A	:		Union[str, Any]         =				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   __A	:		int         =				["input_ids", "attention_mask"]
   __A	:		Optional[Any]         =				False






   def __init__(      self				:     Optional[Any]	,						lowercase_				:     str	,						lowercase_				:     str="<d>"	,						lowercase_				:     Dict="</d>"	,						lowercase_				:     str="<s>"	,						lowercase_				:     List[Any]="</s>"	,						lowercase_				:     Tuple="<pad>"	,						lowercase_				:     Optional[Any]="<unk>"	,						lowercase_				:     Optional[Any]="</n>"	,						lowercase_				:     int="</_>"	,						lowercase_				:     List[Any]="left"	,						**lowercase_				:     Union[str, Any]	,						)					->						Dict:
       requires_backends(self	,						["jieba"]  )
       super().__init__(
           bod_token=lowercase_	,						eod_token=lowercase_	,						bos_token=lowercase_	,						eos_token=lowercase_	,						pad_token=lowercase_	,						unk_token=lowercase_	,						line_token=lowercase_	,						space_token=lowercase_	,						padding_side=lowercase_	,						**lowercase_	,						)
       lowercase__ :   Dict    					=				bod_token
       lowercase__ :   List[Any]    					=				eod_token
       lowercase__ :   List[str]    					=				load_vocab(lowercase_  )
       lowercase__ :   Tuple    					=				self.encoder[space_token]
       lowercase__ :   Union[str, Any]    					=				self.encoder[line_token]

       del self.encoder[space_token]
       del self.encoder[line_token]

       lowercase__ :   Union[str, Any]    					=				collections.OrderedDict(sorted(self.encoder.items()	,						key=lambda lowercase_  : x[1]  )  )
       lowercase__ :   Optional[Any]    					=				{v: k for k, v in self.encoder.items()}

       lowercase__ :   Dict    					=				WordpieceTokenizer(vocab=self.encoder	,						unk_token=self.unk_token  )






   @property
   def       __UpperCamelCase     (      self				:     Optional[Any]  )					->						Optional[Any]:
       return self.encoder[self.bod_token]






   @property
   def       __UpperCamelCase     (      self				:     List[str]  )					->						List[Any]:
       return self.encoder[self.eod_token]






   @property
   def       __UpperCamelCase     (      self				:     Optional[Any]  )					->						int:
       return self.encoder["\n"]






   @property
   def       __UpperCamelCase     (      self				:     Any  )					->						int:
       return len(self.encoder  )






   def       __UpperCamelCase     (      self				:     List[str]  )					->						List[str]:
       return dict(self.encoder	,						**self.added_tokens_encoder  )






   def       __UpperCamelCase     (      self				:     Union[str, Any]	,						lowercase_				:     int  )					->						Tuple:
       lowercase__ :   Any    					=				[]
       for x in jieba.cut(lowercase_	,						cut_all=lowercase_  ):
           output_tokens.extend(self.wordpiece_tokenizer.tokenize(lowercase_  )  )
       return output_tokens






   def       __UpperCamelCase     (      self				:     Any	,						lowercase_				:     Union[str, Any]	,						**lowercase_				:     str  )					->						Dict:
       lowercase__ :   str    					=				[i for i in token_ids if i >= 0]
       lowercase__ :   List[str]    					=				[
           x for x in token_ids if x != self.pad_token_id and x != self.eos_token_id and x != self.bos_token_id
       ]
       return super()._decode(lowercase_	,						**lowercase_  )






   def       __UpperCamelCase     (      self				:     List[str]	,						lowercase_				:     Dict  )					->						int:
       return token in self.encoder






   def       __UpperCamelCase     (      self				:     str	,						lowercase_				:     List[str]  )					->						str:
       return "".join(lowercase_  )






   def       __UpperCamelCase     (      self				:     Optional[Any]	,						lowercase_				:     Union[str, Any]  )					->						List[str]:
       return self.encoder.get(lowercase_	,						self.encoder.get(self.unk_token  )  )






   def       __UpperCamelCase     (      self				:     Any	,						lowercase_				:     List[str]  )					->						Optional[int]:
       return self.decoder.get(lowercase_	,						self.unk_token  )






   def       __UpperCamelCase     (      self				:     Union[str, Any]	,						lowercase_				:     str	,						lowercase_				:     Optional[str] = None  )					->						Tuple[str]:
       if os.path.isdir(lowercase_  ):
           lowercase__ :   Dict    					=				os.path.join(
               lowercase_	,						(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]  )
       else:
           lowercase__ :   Optional[Any]    					=				(filename_prefix + "-" if filename_prefix else "") + save_directory
       lowercase__ :   int    					=				0
       if " " in self.encoder:
           lowercase__ :   Tuple    					=				self.encoder[" "]
           del self.encoder[" "]
       if "\n" in self.encoder:
           lowercase__ :   List[str]    					=				self.encoder["\n"]
           del self.encoder["\n"]
       lowercase__ :   Optional[Any]    					=				collections.OrderedDict(sorted(self.encoder.items()	,						key=lambda lowercase_  : x[1]  )  )
       with open(lowercase_	,						"w"	,						encoding="utf-8"  ) as writer:
           for token, token_index in self.encoder.items():
               if index != token_index:
                   logger.warning(
                       F'''Saving vocabulary to {vocab_file}: vocabulary indices are not consecutive.'''
                       " Please check that the vocabulary is not corrupted!"  )
                   lowercase__ :   Union[str, Any]    					=				token_index
               writer.write(token + "\n"  )
               index += 1
       return (vocab_file,)






   def       __UpperCamelCase     (      self				:     Union[str, Any]	,						lowercase_				:     List[int]	,						lowercase_				:     List[int] = None  )					->						List[int]:
       if token_ids_a is None:
           return [self.bos_token_id] + token_ids_a
       return [self.bos_token_id] + token_ids_a + [self.bos_token_id] + token_ids_a







   def       __UpperCamelCase     (      self				:     List[Any]	,						lowercase_				:     List[int]	,						lowercase_				:     Optional[List[int]] = None	,						lowercase_				:     bool = False  )					->						List[int]:

       if already_has_special_tokens:
           return super().get_special_tokens_mask(
               token_ids_a=lowercase_	,						token_ids_a=lowercase_	,						already_has_special_tokens=lowercase_  )

       if token_ids_a is not None:
           return [1] + ([0] * len(lowercase_  )) + [1] + ([0] * len(lowercase_  ))
       return [1] + ([0] * len(lowercase_  ))







'''simple docstring'''




import warnings

from ...utils import logging
from .image_processing_flava import FlavaImageProcessor


__snake_case    						=logging.get_logger(__name__)

class 		UpperCAmelCase_      (  __lowercase		):





     def __init__( self       :      Dict    ,      *UpperCAmelCase__       :      Dict    ,      **UpperCAmelCase__       :      List[str]    )				->  None:
        warnings.warn(
            'The class FlavaFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'
            ' use FlavaImageProcessor instead.'    ,      UpperCAmelCase__    ,      )
        super().__init__(*UpperCAmelCase__    ,      **UpperCAmelCase__    )





