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


_SCREAMING_SNAKE_CASE										=						logging.get_logger(__name__)


_SCREAMING_SNAKE_CASE										=						{'vocab_file': 'vocab.json', 'merges_file': 'merges.txt'}

_SCREAMING_SNAKE_CASE										=						{
    'vocab_file': {
        'allenai/longformer-base-4096': 'https://huggingface.co/allenai/longformer-base-4096/resolve/main/vocab.json',
        'allenai/longformer-large-4096': (
            'https://huggingface.co/allenai/longformer-large-4096/resolve/main/vocab.json'
        ),
        'allenai/longformer-large-4096-finetuned-triviaqa': (
            'https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/vocab.json'
        ),
        'allenai/longformer-base-4096-extra.pos.embd.only': (
            'https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/vocab.json'
        ),
        'allenai/longformer-large-4096-extra.pos.embd.only': (
            'https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/vocab.json'
        ),
    },
    'merges_file': {
        'allenai/longformer-base-4096': 'https://huggingface.co/allenai/longformer-base-4096/resolve/main/merges.txt',
        'allenai/longformer-large-4096': (
            'https://huggingface.co/allenai/longformer-large-4096/resolve/main/merges.txt'
        ),
        'allenai/longformer-large-4096-finetuned-triviaqa': (
            'https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/merges.txt'
        ),
        'allenai/longformer-base-4096-extra.pos.embd.only': (
            'https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/merges.txt'
        ),
        'allenai/longformer-large-4096-extra.pos.embd.only': (
            'https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/merges.txt'
        ),
    },
}

_SCREAMING_SNAKE_CASE										=						{
    'allenai/longformer-base-4096': 4_096,
    'allenai/longformer-large-4096': 4_096,
    'allenai/longformer-large-4096-finetuned-triviaqa': 4_096,
    'allenai/longformer-base-4096-extra.pos.embd.only': 4_096,
    'allenai/longformer-large-4096-extra.pos.embd.only': 4_096,
}






@lru_cache()
# Copied from transformers.models.roberta.tokenization_roberta.bytes_to_unicode
def  snake_case  (       )						->   int:
       _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(SCREAMING_SNAKE_CASE__)
                     cs.append(2**8 + n)
                     n += 1
       _A        =  [chr(SCREAMING_SNAKE_CASE__) for n in cs]
       return dict(zip(SCREAMING_SNAKE_CASE__   ,	SCREAMING_SNAKE_CASE__))






def  snake_case  (       snake_case__			:Union[str, Any])						->   Any:
       _A        =  set()
       _A        =  word[0]
       for char in word[1:]:
              pairs.add((prev_char, char))
              _A        =  char
       return pairs







class 				a							(			_snake_case       ):







 """simple docstring"""






 lowerCamelCase	:List[Any]    			=		VOCAB_FILES_NAMES
 lowerCamelCase	:Tuple    			=		PRETRAINED_VOCAB_FILES_MAP
 lowerCamelCase	:Any    			=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 lowerCamelCase	:List[Any]    			=		["""input_ids""", """attention_mask"""]



 def __init__(					self		,				lowerCAmelCase_		,				lowerCAmelCase_		,				lowerCAmelCase_="replace"		,				lowerCAmelCase_="<s>"		,				lowerCAmelCase_="</s>"		,				lowerCAmelCase_="</s>"		,				lowerCAmelCase_="<s>"		,				lowerCAmelCase_="<unk>"		,				lowerCAmelCase_="<pad>"		,				lowerCAmelCase_="<mask>"		,				lowerCAmelCase_=False		,				**lowerCAmelCase_		,				)  ->					Tuple:
        _A        =  AddedToken(__snake_case		,				lstrip=__snake_case		,				rstrip=__snake_case							) if isinstance(__snake_case		,				__snake_case							) else bos_token
        _A        =  AddedToken(__snake_case		,				lstrip=__snake_case		,				rstrip=__snake_case							) if isinstance(__snake_case		,				__snake_case							) else eos_token
        _A        =  AddedToken(__snake_case		,				lstrip=__snake_case		,				rstrip=__snake_case							) if isinstance(__snake_case		,				__snake_case							) else sep_token
        _A        =  AddedToken(__snake_case		,				lstrip=__snake_case		,				rstrip=__snake_case							) if isinstance(__snake_case		,				__snake_case							) else cls_token
        _A        =  AddedToken(__snake_case		,				lstrip=__snake_case		,				rstrip=__snake_case							) if isinstance(__snake_case		,				__snake_case							) else unk_token
        _A        =  AddedToken(__snake_case		,				lstrip=__snake_case		,				rstrip=__snake_case							) if isinstance(__snake_case		,				__snake_case							) else pad_token

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

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

        with open(__snake_case		,				encoding="""utf-8"""							) as vocab_handle:
               _A        =  json.load(__snake_case							)
        _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(__snake_case		,				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(__snake_case		,				range(len(__snake_case							)							)							)							)
        _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							)  ->					Dict:
        return len(self.encoder							)



 def      UpperCAmelCase							(					self							)  ->					Tuple:
        return dict(self.encoder		,				**self.added_tokens_encoder							)



 def      UpperCAmelCase							(					self		,				lowerCAmelCase_							)  ->					Any:
        if token in self.cache:
               return self.cache[token]
        _A        =  tuple(__snake_case							)
        _A        =  get_pairs(__snake_case							)

        if not pairs:
               return token

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

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



 def      UpperCAmelCase							(					self		,				lowerCAmelCase_							)  ->					Union[str, Any]:
        _A        =  []
        for token in re.findall(self.pat		,				__snake_case							):
               _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(__snake_case							).split(""" """							)							)
        return bpe_tokens



 def      UpperCAmelCase							(					self		,				lowerCAmelCase_							)  ->					Union[str, Any]:
        return self.encoder.get(__snake_case		,				self.encoder.get(self.unk_token							)							)



 def      UpperCAmelCase							(					self		,				lowerCAmelCase_							)  ->					int:
        return self.decoder.get(__snake_case							)



 def      UpperCAmelCase							(					self		,				lowerCAmelCase_							)  ->					Tuple:
        _A        =  """""".join(__snake_case							)
        _A        =  bytearray([self.byte_decoder[c] for c in text]							).decode("""utf-8"""		,				errors=self.errors							)
        return text



 def      UpperCAmelCase							(					self		,				lowerCAmelCase_		,				lowerCAmelCase_ = None							)  ->					int:
        if not os.path.isdir(__snake_case							):
               logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''							)
               return
        _A        =  os.path.join(
            __snake_case		,				(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]							)
        _A        =  os.path.join(
            __snake_case		,				(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""merges_file"""]							)

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

        _A        =  0
        with open(__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 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(__snake_case							) + """\n"""							)
                      index += 1

        return vocab_file, merge_file



 def      UpperCAmelCase							(					self		,				lowerCAmelCase_		,				lowerCAmelCase_ = None							)  ->					Tuple:
        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		,				lowerCAmelCase_		,				lowerCAmelCase_ = None		,				lowerCAmelCase_ = False							)  ->					Optional[Any]:
        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							)

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



 def      UpperCAmelCase							(					self		,				lowerCAmelCase_		,				lowerCAmelCase_ = None							)  ->					Optional[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		,				lowerCAmelCase_		,				lowerCAmelCase_=False		,				**lowerCAmelCase_							)  ->					Optional[int]:
        _A        =  kwargs.pop("""add_prefix_space"""		,				self.add_prefix_space							)
        if (is_split_into_words or add_prefix_space) and (len(__snake_case							) > 0 and not text[0].isspace()):
               _A        =  """ """ + text
        return (text, kwargs)








'''simple docstring'''


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


UpperCAmelCase_		:   Dict							   =		logging.get_logger(__name__)

UpperCAmelCase_		:   Optional[int]							   =		{
    'google/canine-s': 'https://huggingface.co/google/canine-s/resolve/main/config.json',
    # See all CANINE models at https://huggingface.co/models?filter=canine
}





class     lowercase__  (						_snake_case					):





							'''simple docstring'''


							A_							:      Optional[int]      	=  """canine"""






							def __init__(    self    ,					__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=1_6384    ,					__snake_case=16    ,					__snake_case=0.02    ,					__snake_case=1e-12    ,					__snake_case=0    ,					__snake_case=0XE000    ,					__snake_case=0XE001    ,					__snake_case=4    ,					__snake_case=4    ,					__snake_case=8    ,					__snake_case=1_6384    ,					__snake_case=128    ,					**__snake_case    ,					):
											super().__init__(pad_token_id=__snake_case    ,					bos_token_id=__snake_case    ,					eos_token_id=__snake_case    ,					**__snake_case  )

											_SCREAMING_SNAKE_CASE :       str     		=      max_position_embeddings
											_SCREAMING_SNAKE_CASE :       Any     		=      hidden_size
											_SCREAMING_SNAKE_CASE :       Dict     		=      num_hidden_layers
											_SCREAMING_SNAKE_CASE :       Tuple     		=      num_attention_heads
											_SCREAMING_SNAKE_CASE :       List[str]     		=      intermediate_size
											_SCREAMING_SNAKE_CASE :       Tuple     		=      hidden_act
											_SCREAMING_SNAKE_CASE :       Union[str, Any]     		=      hidden_dropout_prob
											_SCREAMING_SNAKE_CASE :       str     		=      attention_probs_dropout_prob
											_SCREAMING_SNAKE_CASE :       Dict     		=      initializer_range
											_SCREAMING_SNAKE_CASE :       Optional[int]     		=      type_vocab_size
											_SCREAMING_SNAKE_CASE :       Optional[Any]     		=      layer_norm_eps

											# Character config:
											_SCREAMING_SNAKE_CASE :       Any     		=      downsampling_rate
											_SCREAMING_SNAKE_CASE :       List[str]     		=      upsampling_kernel_size
											_SCREAMING_SNAKE_CASE :       Union[str, Any]     		=      num_hash_functions
											_SCREAMING_SNAKE_CASE :       Optional[Any]     		=      num_hash_buckets
											_SCREAMING_SNAKE_CASE :       Union[str, Any]     		=      local_transformer_stride




