






"""simple docstring"""



import warnings
from typing import Dict, List, Optional, Tuple

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


A_    =							logging.get_logger(__name__)






class 							__SCREAMING_SNAKE_CASE						(				UpperCamelCase		):
							snake_case_     =							['input_ids', 'attention_mask']


							def __init__(			self      :						Optional[int]			,    snake_case      :						Any="</s>"			,    snake_case      :						List[Any]="<unk>"			,    snake_case      :						Tuple="<pad>"			,    snake_case      :						str=125			,    snake_case      :						List[str]=None			,    **snake_case      :						Any			,    ):
													'''simple docstring'''





													if extra_ids > 0 and additional_special_tokens is None:
																			A__						:  str		  =  [F'<extra_id_{i}>' for i in range(snake_case							)]
													elif extra_ids > 0 and additional_special_tokens is not None:
																			# Check that we have the right number of extra_id special tokens
																			A__						:  int		  =  len(set(filter(lambda snake_case							: bool("""extra_id""" in str(snake_case							)							)			,    snake_case							)							)							)
																			if extra_tokens != extra_ids:
																									raise ValueError(
																									    F'Both extra_ids ({extra_ids}) and additional_special_tokens ({additional_special_tokens}) are'
																									    """ provided to ByT5Tokenizer. In this case the additional_special_tokens must include the"""
																									    """ extra_ids tokens"""							)

													A__						:  int		  =  AddedToken(snake_case			,    lstrip=snake_case			,    rstrip=snake_case							) if isinstance(snake_case			,    snake_case							) else pad_token
													A__						:  Dict		  =  AddedToken(snake_case			,    lstrip=snake_case			,    rstrip=snake_case							) if isinstance(snake_case			,    snake_case							) else eos_token
													A__						:  Dict		  =  AddedToken(snake_case			,    lstrip=snake_case			,    rstrip=snake_case							) if isinstance(snake_case			,    snake_case							) else unk_token

													super().__init__(
													    eos_token=snake_case			,    unk_token=snake_case			,    pad_token=snake_case			,    extra_ids=snake_case			,    additional_special_tokens=snake_case			,    **snake_case			,    )

													A__						:  Dict		  =  extra_ids

													A__						:  Any		  =  2**8  # utf is 8 bits

													# define special tokens dict
													A__						:  Dict[int, str]		  =  {
													    self.pad_token: 0,
													    self.eos_token: 1,
													    self.unk_token: 2,
													}
													A__						:  str		  =  len(self.special_tokens_encoder							)
													A__						:  Tuple		  =  len(snake_case							)
													for i, token in enumerate(snake_case							):
																			A__						:  List[str]		  =  self.vocab_size + i - n
													A__						:  Dict[str, int]		  =  {v: k for k, v in self.special_tokens_encoder.items()}


							@property
							def 						_UpperCamelCase       (			self      :						List[Any]							):
													'''simple docstring'''





													return self._utf_vocab_size + self._num_special_tokens + self._extra_ids


							def 						_UpperCamelCase       (			self      :						Tuple			,    snake_case      :						List[int]			,    snake_case      :						Optional[List[int]] = None			,    snake_case      :						bool = False							):
													'''simple docstring'''





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

													# normal case: some special tokens
													if token_ids_a is None:
																			return ([0] * len(snake_case							)) + [1]
													return ([0] * len(snake_case							)) + [1] + ([0] * len(snake_case							)) + [1]


							def 						_UpperCamelCase       (			self      :						Union[str, Any]			,    snake_case      :						List[int]							):
													'''simple docstring'''





													if len(snake_case							) > 0 and token_ids[-1] == self.eos_token_id:
																			warnings.warn(
																			    F'This sequence already has {self.eos_token}. In future versions this behavior may lead to duplicated'
																			    """ eos tokens being added."""							)
																			return token_ids
													else:
																			return token_ids + [self.eos_token_id]


							def 						_UpperCamelCase       (			self      :						Dict			,    snake_case      :						List[int]			,    snake_case      :						Optional[List[int]] = None							):
													'''simple docstring'''





													A__						:  Union[str, Any]		  =  [self.eos_token_id]

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


							def 						_UpperCamelCase       (			self      :						List[Any]			,    snake_case      :						List[int]			,    snake_case      :						Optional[List[int]] = None							):
													'''simple docstring'''





													A__						:  Optional[Any]		  =  self._add_eos_if_not_present(snake_case							)
													if token_ids_a is None:
																			return token_ids_a
													else:
																			A__						:  Tuple		  =  self._add_eos_if_not_present(snake_case							)
																			return token_ids_a + token_ids_a


							def 						_UpperCamelCase       (			self      :						List[str]			,    snake_case      :						str							):
													'''simple docstring'''





													A__						:  Optional[int]		  =  [chr(snake_case							) for i in text.encode("""utf-8"""							)]
													return tokens


							def 						_UpperCamelCase       (			self      :						Optional[Any]			,    snake_case      :						Optional[Any]							):
													'''simple docstring'''





													if token in self.special_tokens_encoder:
																			A__						:  Dict		  =  self.special_tokens_encoder[token]
													elif token in self.added_tokens_encoder:
																			A__						:  Union[str, Any]		  =  self.added_tokens_encoder[token]
													elif len(snake_case							) != 1:
																			A__						:  Dict		  =  self.unk_token_id
													else:
																			A__						:  List[Any]		  =  ord(snake_case							) + self._num_special_tokens
													return token_id


							def 						_UpperCamelCase       (			self      :						Dict			,    snake_case      :						Dict							):
													'''simple docstring'''





													if index in self.special_tokens_decoder:
																			A__						:  Any		  =  self.special_tokens_decoder[index]
													else:
																			A__						:  int		  =  chr(index - self._num_special_tokens							)
													return token


							def 						_UpperCamelCase       (			self      :						Optional[int]			,    snake_case      :						Union[str, Any]							):
													'''simple docstring'''





													A__						:  Union[str, Any]		  =  b""""""
													for token in tokens:
																			if token in self.special_tokens_decoder:
																									A__						:  Dict		  =  self.special_tokens_decoder[token].encode("""utf-8"""							)
																			elif token in self.added_tokens_decoder:
																									A__						:  Dict		  =  self.special_tokens_decoder[token].encode("""utf-8"""							)
																			elif token in self.special_tokens_encoder:
																									A__						:  str		  =  token.encode("""utf-8"""							)
																			elif token in self.added_tokens_encoder:
																									A__						:  int		  =  token.encode("""utf-8"""							)
																			else:
																									A__						:  List[Any]		  =  bytes([ord(snake_case							)]							)
																			bstring += tok_string
													A__						:  Dict		  =  bstring.decode("""utf-8"""			,    errors="""ignore"""							)
													return string


							def 						_UpperCamelCase       (			self      :						Tuple			,    snake_case      :						str			,    snake_case      :						Optional[str] = None							):
													'''simple docstring'''





													return ()














"""simple docstring"""



from ...configuration_utils import PretrainedConfig
from ...utils import logging


A_    =							logging.get_logger(__name__)

A_    =							{
    '''weiweishi/roc-bert-base-zh''': '''https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.json''',
}






class 							__SCREAMING_SNAKE_CASE						(				UpperCamelCase		):
							snake_case_     =							'roc_bert'


							def __init__(			self      :						Tuple			,    snake_case      :						Union[str, Any]=3_0522			,    snake_case      :						Optional[Any]=768			,    snake_case      :						Any=12			,    snake_case      :						Tuple=12			,    snake_case      :						Any=3072			,    snake_case      :						Tuple="gelu"			,    snake_case      :						Optional[int]=0.1			,    snake_case      :						List[str]=0.1			,    snake_case      :						List[str]=512			,    snake_case      :						int=2			,    snake_case      :						Optional[Any]=0.02			,    snake_case      :						str=1e-12			,    snake_case      :						int=True			,    snake_case      :						Optional[Any]=0			,    snake_case      :						str="absolute"			,    snake_case      :						int=None			,    snake_case      :						int=True			,    snake_case      :						Optional[int]=True			,    snake_case      :						List[Any]=768			,    snake_case      :						Dict=910			,    snake_case      :						Tuple=512			,    snake_case      :						Tuple=2_4858			,    snake_case      :						Optional[Any]=True			,    **snake_case      :						Any			,    ):
													'''simple docstring'''





													A__						:  Optional[Any]		  =  vocab_size
													A__						:  Union[str, Any]		  =  max_position_embeddings
													A__						:  Any		  =  hidden_size
													A__						:  Optional[int]		  =  num_hidden_layers
													A__						:  Optional[Any]		  =  num_attention_heads
													A__						:  int		  =  intermediate_size
													A__						:  Optional[Any]		  =  hidden_act
													A__						:  Any		  =  hidden_dropout_prob
													A__						:  Tuple		  =  attention_probs_dropout_prob
													A__						:  Union[str, Any]		  =  initializer_range
													A__						:  str		  =  type_vocab_size
													A__						:  Any		  =  layer_norm_eps
													A__						:  List[str]		  =  use_cache
													A__						:  List[str]		  =  enable_pronunciation
													A__						:  int		  =  enable_shape
													A__						:  Tuple		  =  pronunciation_embed_dim
													A__						:  str		  =  pronunciation_vocab_size
													A__						:  Optional[Any]		  =  shape_embed_dim
													A__						:  str		  =  shape_vocab_size
													A__						:  List[str]		  =  concat_input
													A__						:  str		  =  position_embedding_type
													A__						:  str		  =  classifier_dropout
													super().__init__(pad_token_id=snake_case			,    **snake_case							)






