



import json
import os
from typing import TYPE_CHECKING, List, Optional, Tuple

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


if TYPE_CHECKING:
		from transformers.pipelines.conversational import Conversation

lowerCAmelCase					:				str   	=logging.get_logger(__name__)

lowerCAmelCase					:				int   	={"vocab_file": "vocab.json", "merges_file": "merges.txt"}

lowerCAmelCase					:				Optional[Any]   	={
    "vocab_file": {
        "microsoft/deberta-base": "https://huggingface.co/microsoft/deberta-base/resolve/main/vocab.json",
        "microsoft/deberta-large": "https://huggingface.co/microsoft/deberta-large/resolve/main/vocab.json",
        "microsoft/deberta-xlarge": "https://huggingface.co/microsoft/deberta-xlarge/resolve/main/vocab.json",
        "microsoft/deberta-base-mnli": "https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/vocab.json",
        "microsoft/deberta-large-mnli": "https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/vocab.json",
        "microsoft/deberta-xlarge-mnli": (
            "https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/vocab.json"
        ),
    },
    "merges_file": {
        "microsoft/deberta-base": "https://huggingface.co/microsoft/deberta-base/resolve/main/merges.txt",
        "microsoft/deberta-large": "https://huggingface.co/microsoft/deberta-large/resolve/main/merges.txt",
        "microsoft/deberta-xlarge": "https://huggingface.co/microsoft/deberta-xlarge/resolve/main/merges.txt",
        "microsoft/deberta-base-mnli": "https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/merges.txt",
        "microsoft/deberta-large-mnli": "https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/merges.txt",
        "microsoft/deberta-xlarge-mnli": (
            "https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/merges.txt"
        ),
    },
}

lowerCAmelCase					:				Tuple   	={
    "microsoft/deberta-base": 512,
    "microsoft/deberta-large": 512,
    "microsoft/deberta-xlarge": 512,
    "microsoft/deberta-base-mnli": 512,
    "microsoft/deberta-large-mnli": 512,
    "microsoft/deberta-xlarge-mnli": 512,
}

lowerCAmelCase					:				Optional[Any]   	={
    "microsoft/deberta-base": {"do_lower_case": False},
    "microsoft/deberta-large": {"do_lower_case": False},
}







def  _UpperCAmelCase  (				):


						'''simple docstring'''




						lowerCAmelCase	:   str					     =					(
						    list(range(ord("""!"""  )			,ord("""~"""  ) + 1  )  ) + list(range(ord("""¡"""  )			,ord("""¬"""  ) + 1  )  ) + list(range(ord("""®"""  )			,ord("""ÿ"""  ) + 1  )  )
						)
						lowerCAmelCase	:   Union[str, Any]					     =					bs[:]
						lowerCAmelCase	:   str					     =					0
						for b in range(2**8  ):
												if b not in bs:
																		bs.append(__SCREAMING_SNAKE_CASE  )
																		cs.append(2**8 + n  )
																		n += 1
						lowerCAmelCase	:   Optional[int]					     =					[chr(__SCREAMING_SNAKE_CASE  ) for n in cs]
						return dict(zip(__SCREAMING_SNAKE_CASE			,__SCREAMING_SNAKE_CASE  )  )







def  _UpperCAmelCase  (				SCREAMING_SNAKE_CASE__  ):


						'''simple docstring'''




						lowerCAmelCase	:   List[str]					     =					set()
						lowerCAmelCase	:   Union[str, Any]					     =					word[0]
						for char in word[1:]:
												pairs.add((prev_char, char)  )
												lowerCAmelCase	:   Tuple					     =					char
						return pairs






class 	_a			(      lowerCamelCase_  ):
			_UpperCamelCase:   Optional[int]	     =		VOCAB_FILES_NAMES
			_UpperCamelCase:   Tuple	     =		PRETRAINED_VOCAB_FILES_MAP
			_UpperCamelCase:   Tuple	     =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			_UpperCamelCase:   List[Any]	     =		["input_ids", "attention_mask", "token_type_ids"]






			def __init__(    self    ,  lowercase_    ,  lowercase_    ,  lowercase_="replace"    ,  lowercase_="[CLS]"    ,  lowercase_="[SEP]"    ,  lowercase_="[SEP]"    ,  lowercase_="[CLS]"    ,  lowercase_="[UNK]"    ,  lowercase_="[PAD]"    ,  lowercase_="[MASK]"    ,  lowercase_=False    ,  lowercase_=False    ,  **lowercase_    ,  )	->					Tuple:
									lowerCAmelCase	:   List[str]					     =					AddedToken(__SCREAMING_SNAKE_CASE    ,  lstrip=__SCREAMING_SNAKE_CASE    ,  rstrip=__SCREAMING_SNAKE_CASE ) if isinstance(__SCREAMING_SNAKE_CASE    ,  __SCREAMING_SNAKE_CASE ) else bos_token
									lowerCAmelCase	:   List[Any]					     =					AddedToken(__SCREAMING_SNAKE_CASE    ,  lstrip=__SCREAMING_SNAKE_CASE    ,  rstrip=__SCREAMING_SNAKE_CASE ) if isinstance(__SCREAMING_SNAKE_CASE    ,  __SCREAMING_SNAKE_CASE ) else eos_token
									lowerCAmelCase	:   Union[str, Any]					     =					AddedToken(__SCREAMING_SNAKE_CASE    ,  lstrip=__SCREAMING_SNAKE_CASE    ,  rstrip=__SCREAMING_SNAKE_CASE ) if isinstance(__SCREAMING_SNAKE_CASE    ,  __SCREAMING_SNAKE_CASE ) else sep_token
									lowerCAmelCase	:   Optional[int]					     =					AddedToken(__SCREAMING_SNAKE_CASE    ,  lstrip=__SCREAMING_SNAKE_CASE    ,  rstrip=__SCREAMING_SNAKE_CASE ) if isinstance(__SCREAMING_SNAKE_CASE    ,  __SCREAMING_SNAKE_CASE ) else cls_token
									lowerCAmelCase	:   Optional[Any]					     =					AddedToken(__SCREAMING_SNAKE_CASE    ,  lstrip=__SCREAMING_SNAKE_CASE    ,  rstrip=__SCREAMING_SNAKE_CASE ) if isinstance(__SCREAMING_SNAKE_CASE    ,  __SCREAMING_SNAKE_CASE ) else unk_token
									lowerCAmelCase	:   Dict					     =					AddedToken(__SCREAMING_SNAKE_CASE    ,  lstrip=__SCREAMING_SNAKE_CASE    ,  rstrip=__SCREAMING_SNAKE_CASE ) if isinstance(__SCREAMING_SNAKE_CASE    ,  __SCREAMING_SNAKE_CASE ) else pad_token

									# Mask token behave like a normal word, i.e. include the space before it
									lowerCAmelCase	:   Dict					     =					AddedToken(__SCREAMING_SNAKE_CASE    ,  lstrip=__SCREAMING_SNAKE_CASE    ,  rstrip=__SCREAMING_SNAKE_CASE ) if isinstance(__SCREAMING_SNAKE_CASE    ,  __SCREAMING_SNAKE_CASE ) else mask_token

									super().__init__(
									    errors=__SCREAMING_SNAKE_CASE    ,  bos_token=__SCREAMING_SNAKE_CASE    ,  eos_token=__SCREAMING_SNAKE_CASE    ,  unk_token=__SCREAMING_SNAKE_CASE    ,  sep_token=__SCREAMING_SNAKE_CASE    ,  cls_token=__SCREAMING_SNAKE_CASE    ,  pad_token=__SCREAMING_SNAKE_CASE    ,  mask_token=__SCREAMING_SNAKE_CASE    ,  add_prefix_space=__SCREAMING_SNAKE_CASE    ,  add_bos_token=__SCREAMING_SNAKE_CASE    ,  **__SCREAMING_SNAKE_CASE    ,  )
									lowerCAmelCase	:   int					     =					add_bos_token

									with open(__SCREAMING_SNAKE_CASE    ,  encoding="""utf-8""" ) as vocab_handle:
															lowerCAmelCase	:   Tuple					     =					json.load(__SCREAMING_SNAKE_CASE )
									lowerCAmelCase	:   Union[str, Any]					     =					{v: k for k, v in self.encoder.items()}
									lowerCAmelCase	:   Any					     =					errors  # how to handle errors in decoding
									lowerCAmelCase	:   List[Any]					     =					bytes_to_unicode()
									lowerCAmelCase	:   Any					     =					{v: k for k, v in self.byte_encoder.items()}
									with open(__SCREAMING_SNAKE_CASE    ,  encoding="""utf-8""" ) as merges_handle:
															lowerCAmelCase	:   int					     =					merges_handle.read().split("""\n""" )[1:-1]
									lowerCAmelCase	:   Optional[Any]					     =					[tuple(merge.split() ) for merge in bpe_merges]
									lowerCAmelCase	:   Optional[int]					     =					dict(zip(__SCREAMING_SNAKE_CASE    ,  range(len(__SCREAMING_SNAKE_CASE ) ) ) )
									lowerCAmelCase	:   List[str]					     =					{}
									lowerCAmelCase	:   Optional[int]					     =					add_prefix_space

									# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
									lowerCAmelCase	:   List[Any]					     =					re.compile(R"""\'s|\'t|\'re|\'ve|\'m|\'ll|\'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+""" )






			@property
			# Copied from transformers.models.gpt2.tokenization_gpt2.GPT2Tokenizer.vocab_size
			def 							_snake_case   (    self )	->					Union[str, Any]:
									return len(self.encoder )






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






			def 							_snake_case   (    self    ,  lowercase_ )	->					Any:





									if token in self.cache:
															return self.cache[token]
									lowerCAmelCase	:   Union[str, Any]					     =					tuple(__SCREAMING_SNAKE_CASE )
									lowerCAmelCase	:   List[Any]					     =					get_pairs(__SCREAMING_SNAKE_CASE )

									if not pairs:
															return token

									while True:
															lowerCAmelCase	:   Tuple					     =					min(__SCREAMING_SNAKE_CASE    ,  key=lambda lowercase_ : self.bpe_ranks.get(__SCREAMING_SNAKE_CASE    ,  float("""inf""" ) ) )
															if bigram not in self.bpe_ranks:
																					break
															lowerCAmelCase	:   Tuple					     =					bigram
															lowerCAmelCase	:   str					     =					[]
															lowerCAmelCase	:   List[Any]					     =					0
															while i < len(__SCREAMING_SNAKE_CASE ):
																					try:
																											lowerCAmelCase	:   Tuple					     =					word.index(__SCREAMING_SNAKE_CASE    ,  __SCREAMING_SNAKE_CASE )
																					except ValueError:
																											new_word.extend(word[i:] )
																											break
																					else:
																											new_word.extend(word[i:j] )
																											lowerCAmelCase	:   List[str]					     =					j

																					if word[i] == first and i < len(__SCREAMING_SNAKE_CASE ) - 1 and word[i + 1] == second:
																											new_word.append(first + second )
																											i += 2
																					else:
																											new_word.append(word[i] )
																											i += 1
															lowerCAmelCase	:   Tuple					     =					tuple(__SCREAMING_SNAKE_CASE )
															lowerCAmelCase	:   Dict					     =					new_word
															if len(__SCREAMING_SNAKE_CASE ) == 1:
																					break
															else:
																					lowerCAmelCase	:   List[str]					     =					get_pairs(__SCREAMING_SNAKE_CASE )
									lowerCAmelCase	:   Tuple					     =					''' '''.join(__SCREAMING_SNAKE_CASE )
									lowerCAmelCase	:   Union[str, Any]					     =					word
									return word






			def 							_snake_case   (    self    ,  lowercase_    ,  lowercase_ = None )	->					Tuple:





									if token_ids_a is None:
															return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
									lowerCAmelCase	:   List[Any]					     =					[self.cls_token_id]
									lowerCAmelCase	:   Dict					     =					[self.sep_token_id]
									return cls + token_ids_a + sep + token_ids_a + sep






			def 							_snake_case   (    self    ,  lowercase_    ,  lowercase_ = None    ,  lowercase_ = False )	->					int:





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

									if token_ids_a is None:
															return [1] + ([0] * len(__SCREAMING_SNAKE_CASE )) + [1]
									return [1] + ([0] * len(__SCREAMING_SNAKE_CASE )) + [1] + ([0] * len(__SCREAMING_SNAKE_CASE )) + [1]






			def 							_snake_case   (    self    ,  lowercase_    ,  lowercase_ = None )	->					Any:
									lowerCAmelCase	:   Dict					     =					[self.sep_token_id]
									lowerCAmelCase	:   int					     =					[self.cls_token_id]

									if token_ids_a is None:
															return len(cls + token_ids_a + sep ) * [0]
									return len(cls + token_ids_a + sep ) * [0] + len(token_ids_a + sep ) * [1]






			def 							_snake_case   (    self    ,  lowercase_ )	->					str:
									lowerCAmelCase	:   Optional[Any]					     =					[]
									for token in re.findall(self.pat    ,  __SCREAMING_SNAKE_CASE ):
															lowerCAmelCase	:   List[str]					     =					''''''.join(
															    self.byte_encoder[b] for b in token.encode("""utf-8""" ) )  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
															bpe_tokens.extend(bpe_token for bpe_token in self.bpe(__SCREAMING_SNAKE_CASE ).split(""" """ ) )
									return bpe_tokens






			def 							_snake_case   (    self    ,  lowercase_ )	->					Optional[Any]:
									return self.encoder.get(__SCREAMING_SNAKE_CASE    ,  self.encoder.get(self.unk_token ) )






			def 							_snake_case   (    self    ,  lowercase_ )	->					Any:
									return self.decoder.get(__SCREAMING_SNAKE_CASE )






			def 							_snake_case   (    self    ,  lowercase_ )	->					int:
									lowerCAmelCase	:   Any					     =					''''''.join(__SCREAMING_SNAKE_CASE )
									lowerCAmelCase	:   int					     =					bytearray([self.byte_decoder[c] for c in text] ).decode("""utf-8"""    ,  errors=self.errors )
									return text






			def 							_snake_case   (    self    ,  lowercase_    ,  lowercase_ = None )	->					List[str]:





									if not os.path.isdir(__SCREAMING_SNAKE_CASE ):
															logger.error(f"""Vocabulary path ({save_directory}) should be a directory""" )
															return
									lowerCAmelCase	:   Tuple					     =					os.path.join(
									    __SCREAMING_SNAKE_CASE    ,  (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""] )
									lowerCAmelCase	:   Any					     =					os.path.join(
									    __SCREAMING_SNAKE_CASE    ,  (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""merges_file"""] )

									with open(__SCREAMING_SNAKE_CASE    ,  """w"""    ,  encoding="""utf-8""" ) as f:
															f.write(json.dumps(self.encoder    ,  indent=2    ,  sort_keys=__SCREAMING_SNAKE_CASE    ,  ensure_ascii=__SCREAMING_SNAKE_CASE ) + """\n""" )

									lowerCAmelCase	:   Optional[Any]					     =					0
									with open(__SCREAMING_SNAKE_CASE    ,  """w"""    ,  encoding="""utf-8""" ) as writer:
															writer.write("""#version: 0.2\n""" )
															for bpe_tokens, token_index in sorted(self.bpe_ranks.items()    ,  key=lambda lowercase_ : kv[1] ):
																					if index != token_index:
																											logger.warning(
																											    f"""Saving vocabulary to {merge_file}: BPE merge indices are not consecutive."""
																											    """ Please check that the tokenizer is not corrupted!""" )
																											lowerCAmelCase	:   int					     =					token_index
																					writer.write(""" """.join(__SCREAMING_SNAKE_CASE ) + """\n""" )
																					index += 1

									return vocab_file, merge_file






			def 							_snake_case   (    self    ,  lowercase_    ,  lowercase_=False    ,  **lowercase_ )	->					Optional[int]:
									lowerCAmelCase	:   Tuple					     =					kwargs.pop("""add_prefix_space"""    ,  self.add_prefix_space )
									if (is_split_into_words or add_prefix_space) and (len(__SCREAMING_SNAKE_CASE ) > 0 and not text[0].isspace()):
															lowerCAmelCase	:   int					     =					''' ''' + text
									return (text, kwargs)






			def 							_snake_case   (    self    ,  lowercase_ )	->					str:
									lowerCAmelCase	:   Tuple					     =					[]
									for is_user, text in conversation.iter_texts():
															input_ids.extend(self.encode(__SCREAMING_SNAKE_CASE    ,  add_special_tokens=__SCREAMING_SNAKE_CASE ) + [self.eos_token_id] )
									if len(__SCREAMING_SNAKE_CASE ) > self.model_max_length:
															lowerCAmelCase	:   List[Any]					     =					input_ids[-self.model_max_length :]
									return input_ids



'''simple docstring'''







from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding






class 					lowerCAmelCase__  (    lowerCamelCase_	):
					lowerCAmelCase_	  =	['''image_processor''', '''tokenizer''']
					lowerCAmelCase_	  =	'''EfficientNetImageProcessor'''
					lowerCAmelCase_	  =	('''BertTokenizer''', '''BertTokenizerFast''')






					def __init__(  self							,				__SCREAMING_SNAKE_CASE							,				__SCREAMING_SNAKE_CASE						):


											"""simple docstring"""





											super().__init__(__SCREAMING_SNAKE_CASE							,				__SCREAMING_SNAKE_CASE						)






					def __call__(  self							,				__SCREAMING_SNAKE_CASE=None							,				__SCREAMING_SNAKE_CASE=None							,				__SCREAMING_SNAKE_CASE="max_length"							,				__SCREAMING_SNAKE_CASE=64							,				__SCREAMING_SNAKE_CASE=None							,				**__SCREAMING_SNAKE_CASE						):


											"""simple docstring"""





											if text is None and images is None:
																	raise ValueError('''You have to specify either text or images. Both cannot be none.'''						)

											if text is not None:
																	lowercase_      :	str						=			self.tokenizer(
																	    __SCREAMING_SNAKE_CASE							,				padding=__SCREAMING_SNAKE_CASE							,				max_length=__SCREAMING_SNAKE_CASE							,				return_tensors=__SCREAMING_SNAKE_CASE							,				**__SCREAMING_SNAKE_CASE						)

											if images is not None:
																	lowercase_      :	int						=			self.image_processor(__SCREAMING_SNAKE_CASE							,				return_tensors=__SCREAMING_SNAKE_CASE							,				**__SCREAMING_SNAKE_CASE						)

											if text is not None and images is not None:
																	lowercase_      :	Any						=			image_features.pixel_values
																	return encoding
											elif text is not None:
																	return encoding
											else:
																	return BatchEncoding(data=dict(**__SCREAMING_SNAKE_CASE						)							,				tensor_type=__SCREAMING_SNAKE_CASE						)






					def       _snake_case       (  self							,				*__SCREAMING_SNAKE_CASE							,				**__SCREAMING_SNAKE_CASE						):


											"""simple docstring"""





											return self.tokenizer.batch_decode(*__SCREAMING_SNAKE_CASE							,				**__SCREAMING_SNAKE_CASE						)






					def       _snake_case       (  self							,				*__SCREAMING_SNAKE_CASE							,				**__SCREAMING_SNAKE_CASE						):


											"""simple docstring"""





											return self.tokenizer.decode(*__SCREAMING_SNAKE_CASE							,				**__SCREAMING_SNAKE_CASE						)






					@property
					def       _snake_case       (  self						):


											"""simple docstring"""





											lowercase_      :	Dict						=			self.tokenizer.model_input_names
											lowercase_      :	Optional[int]						=			self.image_processor.model_input_names
											return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names						)						)



