




import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple

import regex as re

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


__lowerCAmelCase						:							Dict			     =						logging.get_logger(__name__)

__lowerCAmelCase						:							List[Any]			     =						{
    'vocab_file': 'vocab.json',
    'merges_file': 'merges.txt',
}

__lowerCAmelCase						:							Optional[int]			     =						{
    'vocab_file': {
        'roberta-base': 'https://huggingface.co/roberta-base/resolve/main/vocab.json',
        'roberta-large': 'https://huggingface.co/roberta-large/resolve/main/vocab.json',
        'roberta-large-mnli': 'https://huggingface.co/roberta-large-mnli/resolve/main/vocab.json',
        'distilroberta-base': 'https://huggingface.co/distilroberta-base/resolve/main/vocab.json',
        'roberta-base-openai-detector': 'https://huggingface.co/roberta-base-openai-detector/resolve/main/vocab.json',
        'roberta-large-openai-detector': (
            'https://huggingface.co/roberta-large-openai-detector/resolve/main/vocab.json'
        ),
    },
    'merges_file': {
        'roberta-base': 'https://huggingface.co/roberta-base/resolve/main/merges.txt',
        'roberta-large': 'https://huggingface.co/roberta-large/resolve/main/merges.txt',
        'roberta-large-mnli': 'https://huggingface.co/roberta-large-mnli/resolve/main/merges.txt',
        'distilroberta-base': 'https://huggingface.co/distilroberta-base/resolve/main/merges.txt',
        'roberta-base-openai-detector': 'https://huggingface.co/roberta-base-openai-detector/resolve/main/merges.txt',
        'roberta-large-openai-detector': (
            'https://huggingface.co/roberta-large-openai-detector/resolve/main/merges.txt'
        ),
    },
}

__lowerCAmelCase						:							int			     =						{
    'roberta-base': 512,
    'roberta-large': 512,
    'roberta-large-mnli': 512,
    'distilroberta-base': 512,
    'roberta-base-openai-detector': 512,
    'roberta-large-openai-detector': 512,
}




@lru_cache()
def      __magic_name__							(					):






			'''simple docstring'''







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




def      __magic_name__							(					A						:   Union[str, Any]  ):






			'''simple docstring'''







			a       =     set()
			a       =     word[0]
			for char in word[1:]:
						pairs.add((prev_char, char)  )
						a       =     char
			return pairs






class        snake_case__				(a_  ):
				"""simple docstring"""



				SCREAMING_SNAKE_CASE_			:				Any									=   VOCAB_FILES_NAMES
				SCREAMING_SNAKE_CASE_			:				str									=   PRETRAINED_VOCAB_FILES_MAP
				SCREAMING_SNAKE_CASE_			:				Any									=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				SCREAMING_SNAKE_CASE_			:				Any									=   ['''input_ids''', '''attention_mask''']





				def __init__( self							:	str   , __lowerCamelCase							:	Union[str, Any]   , __lowerCamelCase							:	Dict   , __lowerCamelCase							:	Dict="replace"   , __lowerCamelCase							:	Union[str, Any]="<s>"   , __lowerCamelCase							:	Dict="</s>"   , __lowerCamelCase							:	Any="</s>"   , __lowerCamelCase							:	Any="<s>"   , __lowerCamelCase							:	Tuple="<unk>"   , __lowerCamelCase							:	Union[str, Any]="<pad>"   , __lowerCamelCase							:	List[str]="<mask>"   , __lowerCamelCase							:	int=False   , **__lowerCamelCase							:	Optional[Any]   , )   ->	Dict:
							a       =     AddedToken(_a   , lstrip=_a   , rstrip=_a				) if isinstance(_a   , _a				) else bos_token
							a       =     AddedToken(_a   , lstrip=_a   , rstrip=_a				) if isinstance(_a   , _a				) else eos_token
							a       =     AddedToken(_a   , lstrip=_a   , rstrip=_a				) if isinstance(_a   , _a				) else sep_token
							a       =     AddedToken(_a   , lstrip=_a   , rstrip=_a				) if isinstance(_a   , _a				) else cls_token
							a       =     AddedToken(_a   , lstrip=_a   , rstrip=_a				) if isinstance(_a   , _a				) else unk_token
							a       =     AddedToken(_a   , lstrip=_a   , rstrip=_a				) if isinstance(_a   , _a				) else pad_token

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

							super().__init__(
							    errors=_a   , bos_token=_a   , eos_token=_a   , unk_token=_a   , sep_token=_a   , cls_token=_a   , pad_token=_a   , mask_token=_a   , add_prefix_space=_a   , **_a   , )

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

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





				@property
				def 				__UpperCAmelCase				( self							:	Optional[int]				)   ->	int:
							return len(self.encoder				)





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





				def 				__UpperCAmelCase				( self							:	Union[str, Any]   , __lowerCamelCase							:	Dict				)   ->	Dict:
							if token in self.cache:
										return self.cache[token]
							a       =     tuple(_a				)
							a       =     get_pairs(_a				)

							if not pairs:
										return token

							while True:
										a       =     min(_a   , key=lambda __lowerCamelCase				: self.bpe_ranks.get(_a   , float("inf"				)				)				)
										if bigram not in self.bpe_ranks:
													break
										a       =     bigram
										a       =     []
										a       =     0
										while i < len(_a				):
													try:
																a       =     word.index(_a   , _a				)
													except ValueError:
																new_word.extend(word[i:]				)
																break
													else:
																new_word.extend(word[i:j]				)
																a       =     j

													if word[i] == first and i < len(_a				) - 1 and word[i + 1] == second:
																new_word.append(first + second				)
																i += 2
													else:
																new_word.append(word[i]				)
																i += 1
										a       =     tuple(_a				)
										a       =     new_word
										if len(_a				) == 1:
													break
										else:
													a       =     get_pairs(_a				)
							a       =     " ".join(_a				)
							a       =     word
							return word





				def 				__UpperCAmelCase				( self							:	Tuple   , __lowerCamelCase							:	Union[str, Any]				)   ->	List[Any]:
							a       =     []
							for token in re.findall(self.pat   , _a				):
										a       =     "".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(_a				).split(" "				)				)
							return bpe_tokens





				def 				__UpperCAmelCase				( self							:	List[str]   , __lowerCamelCase							:	List[str]				)   ->	int:
							return self.encoder.get(_a   , self.encoder.get(self.unk_token				)				)





				def 				__UpperCAmelCase				( self							:	str   , __lowerCamelCase							:	Optional[Any]				)   ->	List[Any]:
							return self.decoder.get(_a				)





				def 				__UpperCAmelCase				( self							:	Optional[Any]   , __lowerCamelCase							:	List[Any]				)   ->	str:
							a       =     "".join(_a				)
							a       =     bytearray([self.byte_decoder[c] for c in text]				).decode("utf-8"   , errors=self.errors				)
							return text





				def 				__UpperCAmelCase				( self							:	Optional[int]   , __lowerCamelCase							:	str   , __lowerCamelCase							:	Optional[str] = None				)   ->	Tuple[str]:
							if not os.path.isdir(_a				):
										logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""				)
										return
							a       =     os.path.join(
							    _a   , (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]				)
							a       =     os.path.join(
							    _a   , (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"]				)

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

							a       =     0
							with open(_a   , "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 __lowerCamelCase				: 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!"				)
																a       =     token_index
													writer.write(" ".join(_a				) + "\n"				)
													index += 1

							return vocab_file, merge_file





				def 				__UpperCAmelCase				( self							:	str   , __lowerCamelCase							:	List[int]   , __lowerCamelCase							:	Optional[List[int]] = None				)   ->	List[int]:
							if token_ids_a is None:
										return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
							a       =     [self.cls_token_id]
							a       =     [self.sep_token_id]
							return cls + token_ids_a + sep + sep + token_ids_a + sep





				def 				__UpperCAmelCase				( self							:	Any   , __lowerCamelCase							:	List[int]   , __lowerCamelCase							:	Optional[List[int]] = None   , __lowerCamelCase							:	bool = False				)   ->	List[int]:
							if already_has_special_tokens:
										return super().get_special_tokens_mask(
										    token_ids_a=_a   , token_ids_a=_a   , already_has_special_tokens=_a				)

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





				def 				__UpperCAmelCase				( self							:	List[Any]   , __lowerCamelCase							:	List[int]   , __lowerCamelCase							:	Optional[List[int]] = None				)   ->	List[int]:
							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 + sep + token_ids_a + sep				) * [0]





				def 				__UpperCAmelCase				( self							:	Any   , __lowerCamelCase							:	Union[str, Any]   , __lowerCamelCase							:	Union[str, Any]=False   , **__lowerCamelCase							:	Dict				)   ->	Optional[int]:
							a       =     kwargs.pop("add_prefix_space"   , self.add_prefix_space				)
							if (is_split_into_words or add_prefix_space) and (len(_a				) > 0 and not text[0].isspace()):
										a       =     " " + text
							return (text, kwargs)










from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


_snake_case				=			{
    "configuration_nystromformer": ["NYSTROMFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "NystromformerConfig"],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      _snake_case				=			[
          "NYSTROMFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
          "NystromformerForMaskedLM",
          "NystromformerForMultipleChoice",
          "NystromformerForQuestionAnswering",
          "NystromformerForSequenceClassification",
          "NystromformerForTokenClassification",
          "NystromformerLayer",
          "NystromformerModel",
          "NystromformerPreTrainedModel",
      ]


if TYPE_CHECKING:
      from .configuration_nystromformer import NYSTROMFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, NystromformerConfig

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_nystromformer import (
                NYSTROMFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
                NystromformerForMaskedLM,
                NystromformerForMultipleChoice,
                NystromformerForQuestionAnswering,
                NystromformerForSequenceClassification,
                NystromformerForTokenClassification,
                NystromformerLayer,
                NystromformerModel,
                NystromformerPreTrainedModel,
            )


else:
      import sys

      _snake_case				=			_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



