






import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
  from .tokenization_big_bird import BigBirdTokenizer
else:
  __a   :							List[Any]						= None

__a   :							Tuple						= logging.get_logger(__name__)
__a   :							int						= {"vocab_file": "spiece.model", "tokenizer_file": "tokenizer.json"}

__a   :							List[str]						= {
    "vocab_file": {
        "google/bigbird-roberta-base": "https://huggingface.co/google/bigbird-roberta-base/resolve/main/spiece.model",
        "google/bigbird-roberta-large": (
            "https://huggingface.co/google/bigbird-roberta-large/resolve/main/spiece.model"
        ),
        "google/bigbird-base-trivia-itc": (
            "https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/spiece.model"
        ),
    },
    "tokenizer_file": {
        "google/bigbird-roberta-base": (
            "https://huggingface.co/google/bigbird-roberta-base/resolve/main/tokenizer.json"
        ),
        "google/bigbird-roberta-large": (
            "https://huggingface.co/google/bigbird-roberta-large/resolve/main/tokenizer.json"
        ),
        "google/bigbird-base-trivia-itc": (
            "https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/tokenizer.json"
        ),
    },
}

__a   :							Dict						= {
    "google/bigbird-roberta-base": 4096,
    "google/bigbird-roberta-large": 4096,
    "google/bigbird-base-trivia-itc": 4096,
}


__a   :							Union[str, Any]						= "▁"


class    __lowercase   (						lowercase_	):







     '''simple docstring'''
     SCREAMING_SNAKE_CASE     =					VOCAB_FILES_NAMES
     SCREAMING_SNAKE_CASE     =					PRETRAINED_VOCAB_FILES_MAP
     SCREAMING_SNAKE_CASE     =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     SCREAMING_SNAKE_CASE     =					BigBirdTokenizer
     SCREAMING_SNAKE_CASE     =					["input_ids", "attention_mask"]
     SCREAMING_SNAKE_CASE     =					[]




     def __init__(					self							:      Optional[int]			,						UpperCamelCase_							:      int=None			,						UpperCamelCase_							:      Optional[Any]=None			,						UpperCamelCase_							:      Tuple="<unk>"			,						UpperCamelCase_							:      Optional[Any]="<s>"			,						UpperCamelCase_							:      Optional[Any]="</s>"			,						UpperCamelCase_							:      List[Any]="<pad>"			,						UpperCamelCase_							:      List[Any]="[SEP]"			,						UpperCamelCase_							:      Optional[Any]="[MASK]"			,						UpperCamelCase_							:      Tuple="[CLS]"			,						**UpperCamelCase_							:      Optional[int]			,						):


         """simple docstring"""



         __A       =						AddedToken(UpperCamelCase_			,						lstrip=UpperCamelCase_			,						rstrip=UpperCamelCase_					) if isinstance(UpperCamelCase_			,						UpperCamelCase_					) else bos_token
         __A       =						AddedToken(UpperCamelCase_			,						lstrip=UpperCamelCase_			,						rstrip=UpperCamelCase_					) if isinstance(UpperCamelCase_			,						UpperCamelCase_					) else eos_token
         __A       =						AddedToken(UpperCamelCase_			,						lstrip=UpperCamelCase_			,						rstrip=UpperCamelCase_					) if isinstance(UpperCamelCase_			,						UpperCamelCase_					) else unk_token
         __A       =						AddedToken(UpperCamelCase_			,						lstrip=UpperCamelCase_			,						rstrip=UpperCamelCase_					) if isinstance(UpperCamelCase_			,						UpperCamelCase_					) else pad_token
         __A       =						AddedToken(UpperCamelCase_			,						lstrip=UpperCamelCase_			,						rstrip=UpperCamelCase_					) if isinstance(UpperCamelCase_			,						UpperCamelCase_					) else cls_token
         __A       =						AddedToken(UpperCamelCase_			,						lstrip=UpperCamelCase_			,						rstrip=UpperCamelCase_					) if isinstance(UpperCamelCase_			,						UpperCamelCase_					) else sep_token

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

         super().__init__(
             UpperCamelCase_			,						tokenizer_file=UpperCamelCase_			,						bos_token=UpperCamelCase_			,						eos_token=UpperCamelCase_			,						unk_token=UpperCamelCase_			,						sep_token=UpperCamelCase_			,						pad_token=UpperCamelCase_			,						cls_token=UpperCamelCase_			,						mask_token=UpperCamelCase_			,						**UpperCamelCase_			,						)

         __A       =						vocab_file
         __A       =						False if not self.vocab_file else True




     def 		lowerCAmelCase_  (					self							:      Any			,						UpperCamelCase_							:      List[int]			,						UpperCamelCase_							:      Optional[List[int]] = None					):


         """simple docstring"""



         __A       =						[self.sep_token_id]
         __A       =						[self.cls_token_id]
         if token_ids_a is None:
             return cls + token_ids_a + sep
         return cls + token_ids_a + sep + token_ids_a + sep




     def 		lowerCAmelCase_  (					self							:      Union[str, Any]			,						UpperCamelCase_							:      List[int]			,						UpperCamelCase_							:      Optional[List[int]] = None			,						UpperCamelCase_							:      bool = False					):


         """simple docstring"""



         if already_has_special_tokens:
             if token_ids_a is not None:
                 raise ValueError(
                     """You should not supply a second sequence if the provided sequence of """
                     """ids is already formatted with special tokens for the model."""					)
             return [1 if x in [self.sep_token_id, self.cls_token_id] else 0 for x in token_ids_a]

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




     def 		lowerCAmelCase_  (					self							:      Union[str, Any]			,						UpperCamelCase_							:      List[int]			,						UpperCamelCase_							:      Optional[List[int]] = None					):


         """simple docstring"""



         __A       =						[self.sep_token_id]
         __A       =						[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 		lowerCAmelCase_  (					self							:      int			,						UpperCamelCase_							:      str			,						UpperCamelCase_							:      Optional[str] = None					):


         """simple docstring"""



         if not self.can_save_slow_tokenizer:
             raise ValueError(
                 """Your fast tokenizer does not have the necessary information to save the vocabulary for a slow """
                 """tokenizer."""					)

         if not os.path.isdir(UpperCamelCase_					):
             logger.error(F"Vocabulary path ({save_directory}) should be a directory"					)
             return
         __A       =						os.path.join(
             UpperCamelCase_			,						(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]					)

         if os.path.abspath(self.vocab_file					) != os.path.abspath(UpperCamelCase_					):
             copyfile(self.vocab_file			,						UpperCamelCase_					)

         return (out_vocab_file,)












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


__a   :							List[Any]						= logging.get_logger(__name__)

# TODO: upload to AWS
__a   :							Union[str, Any]						= {
    "yjernite/retribert-base-uncased": (
        "https://huggingface.co/yjernite/retribert-base-uncased/resolve/main/config.json"
    ),
}


class    __lowercase   (						lowercase_	):







     '''simple docstring'''
     SCREAMING_SNAKE_CASE     =					"retribert"




     def __init__(					self							:      Any			,						UpperCamelCase_							:      int=30_522			,						UpperCamelCase_							:      Optional[int]=768			,						UpperCamelCase_							:      Union[str, Any]=8			,						UpperCamelCase_							:      Tuple=12			,						UpperCamelCase_							:      List[Any]=3_072			,						UpperCamelCase_							:      Tuple="gelu"			,						UpperCamelCase_							:      str=0.1			,						UpperCamelCase_							:      Dict=0.1			,						UpperCamelCase_							:      List[str]=512			,						UpperCamelCase_							:      Optional[int]=2			,						UpperCamelCase_							:      Tuple=0.02			,						UpperCamelCase_							:      List[str]=1e-12			,						UpperCamelCase_							:      Any=True			,						UpperCamelCase_							:      List[Any]=128			,						UpperCamelCase_							:      Union[str, Any]=0			,						**UpperCamelCase_							:      List[str]			,						):


         """simple docstring"""



         super().__init__(pad_token_id=UpperCamelCase_			,						**UpperCamelCase_					)

         __A       =						vocab_size
         __A       =						hidden_size
         __A       =						num_hidden_layers
         __A       =						num_attention_heads
         __A       =						hidden_act
         __A       =						intermediate_size
         __A       =						hidden_dropout_prob
         __A       =						attention_probs_dropout_prob
         __A       =						max_position_embeddings
         __A       =						type_vocab_size
         __A       =						initializer_range
         __A       =						layer_norm_eps
         __A       =						share_encoders
         __A       =						projection_dim




