





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

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging


snake_case_           =      logging.get_logger(__name__)


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

# See all LED models at https://huggingface.co/models?filter=LED
snake_case_           =      {
    'vocab_file': {
        'allenai/led-base-16384': 'https://huggingface.co/allenai/led-base-16384/resolve/main/vocab.json',
    },
    'merges_file': {
        'allenai/led-base-16384': 'https://huggingface.co/allenai/led-base-16384/resolve/main/merges.txt',
    },
    'tokenizer_file': {
        'allenai/led-base-16384': 'https://huggingface.co/allenai/led-base-16384/resolve/main/tokenizer.json',
    },
}

snake_case_           =      {
    'allenai/led-base-16384': 16384,
}






@lru_cache()
# Copied from transformers.models.bart.tokenization_bart.bytes_to_unicode
def lowerCamelCase__   (							)				->    List[Any]:
   __snake_case								=       (
       list(range(ord('''!'''	)	,				ord('''~'''	) + 1	)	) + list(range(ord('''¡'''	)	,				ord('''¬'''	) + 1	)	) + list(range(ord('''®'''	)	,				ord('''ÿ'''	) + 1	)	)
   )
   __snake_case								=       bs[:]
   __snake_case								=       0
   for b in range(2**8	):
      if b not in bs:
         bs.append(snake_case_	)
         cs.append(2**8 + n	)
         n += 1
   __snake_case								=       [chr(snake_case_	) for n in cs]
   return dict(zip(snake_case_	,				snake_case_	)	)






def lowerCamelCase__   (							snake_case_     :  str	)				->    List[Any]:
   __snake_case								=       set()
   __snake_case								=       word[0]
   for char in word[1:]:
      pairs.add((prev_char, char)	)
      __snake_case								=       char
   return pairs







class 		SCREAMING_SNAKE_CASE__    (	_UpperCAmelCase  ):
      A_						:    List[Any]							=   VOCAB_FILES_NAMES
      A_						:    List[Any]							=   PRETRAINED_VOCAB_FILES_MAP
      A_						:    str							=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      A_						:    List[Any]							=   ['input_ids', 'attention_mask']


      def __init__(self	:				int    ,      a__	:				List[Any]    ,      a__	:				Dict    ,      a__	:				Optional[Any]="replace"    ,      a__	:				Dict="<s>"    ,      a__	:				Optional[int]="</s>"    ,      a__	:				int="</s>"    ,      a__	:				Optional[int]="<s>"    ,      a__	:				str="<unk>"    ,      a__	:				List[str]="<pad>"    ,      a__	:				Any="<mask>"    ,      a__	:				Union[str, Any]=False    ,      **a__	:				Optional[int]    ,      ):





         """simple docstring"""



         __snake_case								=       AddedToken(a__    ,      lstrip=a__    ,      rstrip=a__				) if isinstance(a__    ,      a__				) else bos_token
         __snake_case								=       AddedToken(a__    ,      lstrip=a__    ,      rstrip=a__				) if isinstance(a__    ,      a__				) else eos_token
         __snake_case								=       AddedToken(a__    ,      lstrip=a__    ,      rstrip=a__				) if isinstance(a__    ,      a__				) else sep_token
         __snake_case								=       AddedToken(a__    ,      lstrip=a__    ,      rstrip=a__				) if isinstance(a__    ,      a__				) else cls_token
         __snake_case								=       AddedToken(a__    ,      lstrip=a__    ,      rstrip=a__				) if isinstance(a__    ,      a__				) else unk_token
         __snake_case								=       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
         __snake_case								=       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:
            __snake_case								=       json.load(a__				)
         __snake_case								=       {v: k for k, v in self.encoder.items()}
         __snake_case								=       errors  # how to handle errors in decoding
         __snake_case								=       bytes_to_unicode()
         __snake_case								=       {v: k for k, v in self.byte_encoder.items()}
         with open(a__    ,      encoding='''utf-8'''				) as merges_handle:
            __snake_case								=       merges_handle.read().split('''\n'''				)[1:-1]
         __snake_case								=       [tuple(merge.split()				) for merge in bpe_merges]
         __snake_case								=       dict(zip(a__    ,      range(len(a__				)				)				)				)
         __snake_case								=       {}
         __snake_case								=       add_prefix_space

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


      @property
      # Copied from transformers.models.bart.tokenization_bart.BartTokenizer.vocab_size
      def        a			(self	:				Optional[int]				):





         """simple docstring"""



         return len(self.encoder				)


      def        a			(self	:				Dict				):





         """simple docstring"""



         return dict(self.encoder    ,      **self.added_tokens_encoder				)


      def        a			(self	:				Dict    ,      a__	:				str				):





         """simple docstring"""



         if token in self.cache:
            return self.cache[token]
         __snake_case								=       tuple(a__				)
         __snake_case								=       get_pairs(a__				)

         if not pairs:
            return token

         while True:
            __snake_case								=       min(a__    ,      key=lambda a__				: self.bpe_ranks.get(a__    ,      float('''inf'''				)				)				)
            if bigram not in self.bpe_ranks:
               break
            __snake_case	,     __snake_case								=       bigram
            __snake_case								=       []
            __snake_case								=       0
            while i < len(a__				):
               try:
                  __snake_case								=       word.index(a__    ,      a__				)
               except ValueError:
                  new_word.extend(word[i:]				)
                  break
               else:
                  new_word.extend(word[i:j]				)
                  __snake_case								=       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
            __snake_case								=       tuple(a__				)
            __snake_case								=       new_word
            if len(a__				) == 1:
               break
            else:
               __snake_case								=       get_pairs(a__				)
         __snake_case								=       ''' '''.join(a__				)
         __snake_case								=       word
         return word


      def        a			(self	:				str    ,      a__	:				Optional[int]				):





         """simple docstring"""



         __snake_case								=       []
         for token in re.findall(self.pat    ,      a__				):
            __snake_case								=       ''''''.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        a			(self	:				str    ,      a__	:				List[Any]				):





         """simple docstring"""



         return self.encoder.get(a__    ,      self.encoder.get(self.unk_token				)				)


      def        a			(self	:				Dict    ,      a__	:				Tuple				):





         """simple docstring"""



         return self.decoder.get(a__				)


      def        a			(self	:				List[str]    ,      a__	:				Any				):





         """simple docstring"""



         __snake_case								=       ''''''.join(a__				)
         __snake_case								=       bytearray([self.byte_decoder[c] for c in text]				).decode('''utf-8'''    ,      errors=self.errors				)
         return text


      def        a			(self	:				List[Any]    ,      a__	:				str    ,      a__	:				Optional[str] = None				):





         """simple docstring"""



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

         __snake_case								=       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 a__				: 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!'''				)
                  __snake_case								=       token_index
               writer.write(''' '''.join(a__				) + '''\n'''				)
               index += 1

         return vocab_file, merge_file


      def        a			(self	:				Optional[Any]    ,      a__	:				List[int]    ,      a__	:				Optional[List[int]] = None				):





         """simple docstring"""



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


      def        a			(self	:				Optional[int]    ,      a__	:				List[int]    ,      a__	:				Optional[List[int]] = None    ,      a__	:				bool = False				):





         """simple docstring"""



         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        a			(self	:				Optional[int]    ,      a__	:				List[int]    ,      a__	:				Optional[List[int]] = None				):





         """simple docstring"""



         __snake_case								=       [self.sep_token_id]
         __snake_case								=       [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        a			(self	:				Any    ,      a__	:				Any    ,      a__	:				str=False    ,      **a__	:				Any				):





         """simple docstring"""



         __snake_case								=       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()):
            __snake_case								=       ''' ''' + text
         return (text, kwargs)


      def        a			(self	:				List[str]    ,      a__	:				Union[Dict[str, EncodedInput], BatchEncoding]    ,      a__	:				Optional[int] = None    ,      a__	:				PaddingStrategy = PaddingStrategy.DO_NOT_PAD    ,      a__	:				Optional[int] = None    ,      a__	:				Optional[bool] = None    ,      ):





         """simple docstring"""



         __snake_case								=       super()._pad(
             encoded_inputs=a__    ,      max_length=a__    ,      padding_strategy=a__    ,      pad_to_multiple_of=a__    ,      return_attention_mask=a__    ,      )

         # Load from model defaults
         if return_attention_mask is None:
            __snake_case								=       '''attention_mask''' in self.model_input_names

         if return_attention_mask and "global_attention_mask" in encoded_inputs:
            __snake_case								=       encoded_inputs[self.model_input_names[0]]
            # `global_attention_mask` need to have the same length as other (sequential) inputs.
            __snake_case								=       len(encoded_inputs['''global_attention_mask''']				) != len(a__				)

            if needs_to_be_padded:
               __snake_case								=       len(a__				) - len(encoded_inputs['''global_attention_mask''']				)

               if self.padding_side == "right":
                  # Use `-1` since `0` in `global_attention_mask` means `local attention` instead of `not to attend`
                  __snake_case								=       (
                      encoded_inputs['''global_attention_mask'''] + [-1] * difference
                  )
               elif self.padding_side == "left":
                  __snake_case								=       [-1] * difference + encoded_inputs[
                      '''global_attention_mask'''
                  ]
               else:
                  raise ValueError('''Invalid padding strategy:''' + str(self.padding_side				)				)

         return encoded_inputs








from typing import List, Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer


snake_case_           =      logging.get_logger(__name__)

snake_case_           =      {'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', 'tokenizer_file': 'tokenizer.json'}

snake_case_           =      {
    'vocab_file': {
        'allegro/herbert-base-cased': 'https://huggingface.co/allegro/herbert-base-cased/resolve/main/vocab.json'
    },
    'merges_file': {
        'allegro/herbert-base-cased': 'https://huggingface.co/allegro/herbert-base-cased/resolve/main/merges.txt'
    },
}

snake_case_           =      {'allegro/herbert-base-cased': 514}
snake_case_           =      {}

class 		SCREAMING_SNAKE_CASE__    (	_UpperCAmelCase  ):
      A_						:    Dict							=   VOCAB_FILES_NAMES
      A_						:    Optional[Any]							=   PRETRAINED_VOCAB_FILES_MAP
      A_						:    Optional[int]							=   PRETRAINED_INIT_CONFIGURATION
      A_						:    int							=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      A_						:    Any							=   HerbertTokenizer


      def __init__(self	:				Dict    ,      a__	:				Tuple=None    ,      a__	:				Optional[int]=None    ,      a__	:				List[str]=None    ,      a__	:				Optional[int]="<s>"    ,      a__	:				Optional[Any]="<unk>"    ,      a__	:				Any="<pad>"    ,      a__	:				List[Any]="<mask>"    ,      a__	:				Any="</s>"    ,      **a__	:				Tuple    ,      ):





         """simple docstring"""



         super().__init__(
             a__    ,      a__    ,      tokenizer_file=a__    ,      cls_token=a__    ,      unk_token=a__    ,      pad_token=a__    ,      mask_token=a__    ,      sep_token=a__    ,      **a__    ,      )


      def        a			(self	:				List[str]    ,      a__	:				List[int]    ,      a__	:				Optional[List[int]] = None				):





         """simple docstring"""



         __snake_case								=       [self.cls_token_id]
         __snake_case								=       [self.sep_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        a			(self	:				List[str]    ,      a__	:				List[int]    ,      a__	:				Optional[List[int]] = None    ,      a__	:				bool = False				):





         """simple docstring"""



         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] + ([0] * len(a__				)) + [1]


      def        a			(self	:				Optional[int]    ,      a__	:				List[int]    ,      a__	:				Optional[List[int]] = None				):





         """simple docstring"""



         __snake_case								=       [self.sep_token_id]
         __snake_case								=       [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        a			(self	:				int    ,      a__	:				str    ,      a__	:				Optional[str] = None				):





         """simple docstring"""



         __snake_case								=       self._tokenizer.model.save(a__    ,      name=a__				)
         return tuple(a__				)

