


'''simple docstring'''







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

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


lowerCAmelCase    :     Union[str, Any]					=						logging.get_logger(__name__)
class 	UpperCamelCase__					( SCREAMING_SNAKE_CASE__	):



     """simple docstring"""






     __magic_name__    			=    ["input_ids", "attention_mask"]







     def __init__( self      ,	snake_case__="</s>"      ,	snake_case__="<unk>"      ,	snake_case__="<pad>"      ,	snake_case__=125      ,	snake_case__=None      ,	**snake_case__      ,	):

            '''simple docstring'''

            if extra_ids > 0 and additional_special_tokens is None:
                   _lowerCAmelCase    :							Dict   			=       [F'<extra_id_{i}>' for i in range(_lowercase   )]
            elif extra_ids > 0 and additional_special_tokens is not None:
                   # Check that we have the right number of extra_id special tokens
                   _lowerCAmelCase    :							Optional[Any]   			=       len(set(filter(lambda snake_case__   : bool('extra_id' in str(_lowercase   )   )      ,	_lowercase   )   )   )
                   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'   )

            _lowerCAmelCase    :							List[Any]   			=       AddedToken(_lowercase      ,	lstrip=_lowercase      ,	rstrip=_lowercase   ) if isinstance(_lowercase      ,	_lowercase   ) else pad_token
            _lowerCAmelCase    :							Dict   			=       AddedToken(_lowercase      ,	lstrip=_lowercase      ,	rstrip=_lowercase   ) if isinstance(_lowercase      ,	_lowercase   ) else eos_token
            _lowerCAmelCase    :							str   			=       AddedToken(_lowercase      ,	lstrip=_lowercase      ,	rstrip=_lowercase   ) if isinstance(_lowercase      ,	_lowercase   ) else unk_token

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

            _lowerCAmelCase    :							List[str]   			=       extra_ids

            _lowerCAmelCase    :							Tuple   			=       2**8  # utf is 8 bits

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







     @property
     def a	( self   ):

            '''simple docstring'''

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







     def a	( self      ,	snake_case__      ,	snake_case__ = None      ,	snake_case__ = False   ):

            '''simple docstring'''

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

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







     def a	( self      ,	snake_case__   ):

            '''simple docstring'''

            if len(_lowercase   ) > 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 a	( self      ,	snake_case__      ,	snake_case__ = None   ):

            '''simple docstring'''

            _lowerCAmelCase    :							Optional[int]   			=       [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 a	( self      ,	snake_case__      ,	snake_case__ = None   ):

            '''simple docstring'''

            _lowerCAmelCase    :							List[str]   			=       self._add_eos_if_not_present(_lowercase   )
            if token_ids_a is None:
                   return token_ids_a
            else:
                   _lowerCAmelCase    :							List[Any]   			=       self._add_eos_if_not_present(_lowercase   )
                   return token_ids_a + token_ids_a







     def a	( self      ,	snake_case__   ):

            '''simple docstring'''

            _lowerCAmelCase    :							int   			=       [chr(_lowercase   ) for i in text.encode('utf-8'   )]
            return tokens







     def a	( self      ,	snake_case__   ):

            '''simple docstring'''

            if token in self.special_tokens_encoder:
                   _lowerCAmelCase    :							Tuple   			=       self.special_tokens_encoder[token]
            elif token in self.added_tokens_encoder:
                   _lowerCAmelCase    :							List[Any]   			=       self.added_tokens_encoder[token]
            elif len(_lowercase   ) != 1:
                   _lowerCAmelCase    :							List[Any]   			=       self.unk_token_id
            else:
                   _lowerCAmelCase    :							List[Any]   			=       ord(_lowercase   ) + self._num_special_tokens
            return token_id







     def a	( self      ,	snake_case__   ):

            '''simple docstring'''

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







     def a	( self      ,	snake_case__   ):

            '''simple docstring'''

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







     def a	( self      ,	snake_case__      ,	snake_case__ = None   ):

            '''simple docstring'''

            return ()





'''simple docstring'''







from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


lowerCAmelCase    :     str					=						logging.get_logger(__name__)

lowerCAmelCase    :     int					=						{
    """facebook/data2vec-text-base""": """https://huggingface.co/data2vec/resolve/main/config.json""",
}
class 	UpperCamelCase__					( SCREAMING_SNAKE_CASE_	):



     """simple docstring"""






     __magic_name__    			=    "data2vec-text"







     def __init__( self      ,	snake_case__=3_0522      ,	snake_case__=768      ,	snake_case__=12      ,	snake_case__=12      ,	snake_case__=3072      ,	snake_case__="gelu"      ,	snake_case__=0.1      ,	snake_case__=0.1      ,	snake_case__=512      ,	snake_case__=2      ,	snake_case__=0.02      ,	snake_case__=1E-12      ,	snake_case__=1      ,	snake_case__=0      ,	snake_case__=2      ,	snake_case__="absolute"      ,	snake_case__=True      ,	snake_case__=None      ,	**snake_case__      ,	):

            '''simple docstring'''

            super().__init__(pad_token_id=snake_case__      ,	bos_token_id=snake_case__      ,	eos_token_id=snake_case__      ,	**snake_case__   )

            _lowerCAmelCase    :							List[Any]   			=       vocab_size
            _lowerCAmelCase    :							Tuple   			=       hidden_size
            _lowerCAmelCase    :							Dict   			=       num_hidden_layers
            _lowerCAmelCase    :							int   			=       num_attention_heads
            _lowerCAmelCase    :							str   			=       hidden_act
            _lowerCAmelCase    :							Any   			=       intermediate_size
            _lowerCAmelCase    :							Any   			=       hidden_dropout_prob
            _lowerCAmelCase    :							Optional[int]   			=       attention_probs_dropout_prob
            _lowerCAmelCase    :							str   			=       max_position_embeddings
            _lowerCAmelCase    :							Any   			=       type_vocab_size
            _lowerCAmelCase    :							int   			=       initializer_range
            _lowerCAmelCase    :							List[str]   			=       layer_norm_eps
            _lowerCAmelCase    :							List[Any]   			=       position_embedding_type
            _lowerCAmelCase    :							str   			=       use_cache
            _lowerCAmelCase    :							Union[str, Any]   			=       classifier_dropout
class 	UpperCamelCase__					( SCREAMING_SNAKE_CASE_	):



     """simple docstring"""






     @property
     def a	( self   ):

            '''simple docstring'''

            if self.task == "multiple-choice":
                   _lowerCAmelCase    :							Union[str, Any]   			=       {0: 'batch', 1: 'choice', 2: 'sequence'}
            else:
                   _lowerCAmelCase    :							List[Any]   			=       {0: 'batch', 1: 'sequence'}
            return OrderedDict(
                [
                    ('input_ids', dynamic_axis),
                    ('attention_mask', dynamic_axis),
                ]   )

