






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""": 16_384,
}


@lru_cache()
# Copied from transformers.models.bart.tokenization_bart.bytes_to_unicode
def 	lowerCamelCase__      (  ):

  """simple docstring"""






  SCREAMING_SNAKE_CASE							:   Dict						    =     (
      list(range(ord("!"					)    ,  ord("~"					) + 1					)					) + list(range(ord("¡"					)    ,  ord("¬"					) + 1					)					) + list(range(ord("®"					)    ,  ord("ÿ"					) + 1					)					)
  )
  SCREAMING_SNAKE_CASE							:   Optional[int]						    =     bs[:]
  SCREAMING_SNAKE_CASE							:   Optional[int]						    =     0
  for b in range(2**8					):
    if b not in bs:
      bs.append(lowercase					)
      cs.append(2**8 + n					)
      n += 1
  SCREAMING_SNAKE_CASE							:   Union[str, Any]						    =     [chr(lowercase					) for n in cs]
  return dict(zip(lowercase    ,  lowercase					)					)


def 	lowerCamelCase__      (  lowercase					):

  """simple docstring"""






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


class 			SCREAMING_SNAKE_CASE      (      lowerCAmelCase       ):
     '''simple docstring'''


     UpperCamelCase_				:		Dict								=						VOCAB_FILES_NAMES
     UpperCamelCase_				:		int								=						PRETRAINED_VOCAB_FILES_MAP
     UpperCamelCase_				:		Optional[int]								=						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     UpperCamelCase_				:		Tuple								=						['''input_ids''', '''attention_mask''']


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

       # Mask token behave like a normal word, i.e. include the space before it
       SCREAMING_SNAKE_CASE							:   List[str]						    =     AddedToken(UpperCAmelCase_       ,			lstrip=UpperCAmelCase_       ,			rstrip=UpperCAmelCase_   ) if isinstance(UpperCAmelCase_       ,			UpperCAmelCase_   ) else mask_token

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

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

       # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
       SCREAMING_SNAKE_CASE							:   Optional[Any]						    =     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							:						List[Any]   ):
       return len(self.encoder   )


     def 					_A							(					self							:						str   ):
       return dict(self.encoder       ,			**self.added_tokens_encoder   )


     def 					_A							(					self							:						str       ,			UpperCAmelCase_							:						Dict   ):
       if token in self.cache:
         return self.cache[token]
       SCREAMING_SNAKE_CASE							:   Optional[int]						    =     tuple(UpperCAmelCase_   )
       SCREAMING_SNAKE_CASE							:   str						    =     get_pairs(UpperCAmelCase_   )

       if not pairs:
         return token

       while True:
         SCREAMING_SNAKE_CASE							:   Union[str, Any]						    =     min(UpperCAmelCase_       ,			key=lambda UpperCAmelCase_   : self.bpe_ranks.get(UpperCAmelCase_       ,			float("inf"   )   )   )
         if bigram not in self.bpe_ranks:
           break
         SCREAMING_SNAKE_CASE    ,	SCREAMING_SNAKE_CASE							:   Optional[int]						    =     bigram
         SCREAMING_SNAKE_CASE							:   List[Any]						    =     []
         SCREAMING_SNAKE_CASE							:   Optional[Any]						    =     0
         while i < len(UpperCAmelCase_   ):
           try:
             SCREAMING_SNAKE_CASE							:   List[Any]						    =     word.index(UpperCAmelCase_       ,			UpperCAmelCase_   )
           except ValueError:
             new_word.extend(word[i:]   )
             break
           else:
             new_word.extend(word[i:j]   )
             SCREAMING_SNAKE_CASE							:   str						    =     j

           if word[i] == first and i < len(UpperCAmelCase_   ) - 1 and word[i + 1] == second:
             new_word.append(first + second   )
             i += 2
           else:
             new_word.append(word[i]   )
             i += 1
         SCREAMING_SNAKE_CASE							:   Union[str, Any]						    =     tuple(UpperCAmelCase_   )
         SCREAMING_SNAKE_CASE							:   Any						    =     new_word
         if len(UpperCAmelCase_   ) == 1:
           break
         else:
           SCREAMING_SNAKE_CASE							:   Tuple						    =     get_pairs(UpperCAmelCase_   )
       SCREAMING_SNAKE_CASE							:   str						    =     " ".join(UpperCAmelCase_   )
       SCREAMING_SNAKE_CASE							:   List[Any]						    =     word
       return word


     def 					_A							(					self							:						str       ,			UpperCAmelCase_							:						Optional[int]   ):
       SCREAMING_SNAKE_CASE							:   List[Any]						    =     []
       for token in re.findall(self.pat       ,			UpperCAmelCase_   ):
         SCREAMING_SNAKE_CASE							:   Any						    =     "".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(UpperCAmelCase_   ).split(" "   )   )
       return bpe_tokens


     def 					_A							(					self							:						List[Any]       ,			UpperCAmelCase_							:						int   ):
       return self.encoder.get(UpperCAmelCase_       ,			self.encoder.get(self.unk_token   )   )


     def 					_A							(					self							:						str       ,			UpperCAmelCase_							:						int   ):
       return self.decoder.get(UpperCAmelCase_   )


     def 					_A							(					self							:						Dict       ,			UpperCAmelCase_							:						List[Any]   ):
       SCREAMING_SNAKE_CASE							:   Optional[Any]						    =     "".join(UpperCAmelCase_   )
       SCREAMING_SNAKE_CASE							:   Tuple						    =     bytearray([self.byte_decoder[c] for c in text]   ).decode("utf-8"       ,			errors=self.errors   )
       return text


     def 					_A							(					self							:						Optional[Any]       ,			UpperCAmelCase_							:						str       ,			UpperCAmelCase_							:						Optional[str] = None   ):
       if not os.path.isdir(UpperCAmelCase_   ):
         logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''   )
         return
       SCREAMING_SNAKE_CASE							:   Dict						    =     os.path.join(
           UpperCAmelCase_       ,			(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]   )
       SCREAMING_SNAKE_CASE							:   str						    =     os.path.join(
           UpperCAmelCase_       ,			(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"]   )

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

       SCREAMING_SNAKE_CASE							:   Any						    =     0
       with open(UpperCAmelCase_       ,			"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 UpperCAmelCase_   : 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!"   )
             SCREAMING_SNAKE_CASE							:   List[Any]						    =     token_index
           writer.write(" ".join(UpperCAmelCase_   ) + "\n"   )
           index += 1

       return vocab_file, merge_file


     def 					_A							(					self							:						Dict       ,			UpperCAmelCase_							:						List[int]       ,			UpperCAmelCase_							:						Optional[List[int]] = None   ):
       if token_ids_a is None:
         return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
       SCREAMING_SNAKE_CASE							:   Optional[int]						    =     [self.cls_token_id]
       SCREAMING_SNAKE_CASE							:   List[str]						    =     [self.sep_token_id]
       return cls + token_ids_a + sep + sep + token_ids_a + sep


     def 					_A							(					self							:						Optional[Any]       ,			UpperCAmelCase_							:						List[int]       ,			UpperCAmelCase_							:						Optional[List[int]] = None       ,			UpperCAmelCase_							:						bool = False   ):
       if already_has_special_tokens:
         return super().get_special_tokens_mask(
             token_ids_a=UpperCAmelCase_       ,			token_ids_a=UpperCAmelCase_       ,			already_has_special_tokens=UpperCAmelCase_   )

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


     def 					_A							(					self							:						List[str]       ,			UpperCAmelCase_							:						List[int]       ,			UpperCAmelCase_							:						Optional[List[int]] = None   ):
       SCREAMING_SNAKE_CASE							:   int						    =     [self.sep_token_id]
       SCREAMING_SNAKE_CASE							:   List[str]						    =     [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							:						List[Any]       ,			UpperCAmelCase_							:						Optional[int]       ,			UpperCAmelCase_							:						int=False       ,			**UpperCAmelCase_							:						Optional[int]   ):
       SCREAMING_SNAKE_CASE							:   Union[str, Any]						    =     kwargs.pop("add_prefix_space"       ,			self.add_prefix_space   )
       if (is_split_into_words or add_prefix_space) and (len(UpperCAmelCase_   ) > 0 and not text[0].isspace()):
         SCREAMING_SNAKE_CASE							:   Any						    =     " " + text
       return (text, kwargs)






     def 					_A							(					self							:						int       ,			UpperCAmelCase_							:						Union[Dict[str, EncodedInput], BatchEncoding]       ,			UpperCAmelCase_							:						Optional[int] = None       ,			UpperCAmelCase_							:						PaddingStrategy = PaddingStrategy.DO_NOT_PAD       ,			UpperCAmelCase_							:						Optional[int] = None       ,			UpperCAmelCase_							:						Optional[bool] = None       ,			):
       SCREAMING_SNAKE_CASE							:   int						    =     super()._pad(
           encoded_inputs=UpperCAmelCase_       ,			max_length=UpperCAmelCase_       ,			padding_strategy=UpperCAmelCase_       ,			pad_to_multiple_of=UpperCAmelCase_       ,			return_attention_mask=UpperCAmelCase_       ,			)

       # Load from model defaults
       if return_attention_mask is None:
         SCREAMING_SNAKE_CASE							:   List[Any]						    =     "attention_mask" in self.model_input_names

       if return_attention_mask and "global_attention_mask" in encoded_inputs:
         SCREAMING_SNAKE_CASE							:   Optional[Any]						    =     encoded_inputs[self.model_input_names[0]]
         # `global_attention_mask` need to have the same length as other (sequential) inputs.
         SCREAMING_SNAKE_CASE							:   Dict						    =     len(encoded_inputs["global_attention_mask"]   ) != len(UpperCAmelCase_   )

         if needs_to_be_padded:
           SCREAMING_SNAKE_CASE							:   int						    =     len(UpperCAmelCase_   ) - 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`
             SCREAMING_SNAKE_CASE							:   Any						    =     (
                 encoded_inputs["global_attention_mask"] + [-1] * difference
             )
           elif self.padding_side == "left":
             SCREAMING_SNAKE_CASE							:   List[Any]						    =     [-1] * difference + encoded_inputs[
                 "global_attention_mask"
             ]
           else:
             raise ValueError("Invalid padding strategy:" + str(self.padding_side   )   )

       return encoded_inputs











'''simple docstring'''

from diffusers.utils.testing_utils import require_onnxruntime






@require_onnxruntime
class 						a_		:
							pass




