






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


__lowerCamelCase	:		List[str]										=   logging.get_logger(__name__)


__lowerCamelCase	:		Tuple										=   {"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt"""}

# See all LED models at https://huggingface.co/models?filter=LED
__lowerCamelCase	:		List[Any]										=   {
    """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""",
    },
}

__lowerCamelCase	:		str										=   {
    """allenai/led-base-16384""": 1_63_84,
}







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





 '''simple docstring'''







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







def 			A__							(      _a  :					Optional[Any]	):





 '''simple docstring'''







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







class  _lowercase   (   _A						):
      _a							:						Optional[Any]										=							VOCAB_FILES_NAMES
      _a							:						Any										=							PRETRAINED_VOCAB_FILES_MAP
      _a							:						List[str]										=							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      _a							:						str										=							['input_ids', 'attention_mask']
      def __init__(     self				,			a				,			a				,			a="replace"				,			a="<s>"				,			a="</s>"				,			a="</s>"				,			a="<s>"				,			a="<unk>"				,			a="<pad>"				,			a="<mask>"				,			a=False				,			**a				,			):
       snake_case__  :    Optional[Any]							       =AddedToken(a				,			lstrip=a				,			rstrip=a   ) if isinstance(a				,			a   ) else bos_token
       snake_case__  :    Any							       =AddedToken(a				,			lstrip=a				,			rstrip=a   ) if isinstance(a				,			a   ) else eos_token
       snake_case__  :    Optional[int]							       =AddedToken(a				,			lstrip=a				,			rstrip=a   ) if isinstance(a				,			a   ) else sep_token
       snake_case__  :    int							       =AddedToken(a				,			lstrip=a				,			rstrip=a   ) if isinstance(a				,			a   ) else cls_token
       snake_case__  :    List[str]							       =AddedToken(a				,			lstrip=a				,			rstrip=a   ) if isinstance(a				,			a   ) else unk_token
       snake_case__  :    str							       =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__  :    Optional[Any]							       =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__  :    Any							       =json.load(a   )
       snake_case__  :    Tuple							       ={v: k for k, v in self.encoder.items()}
       snake_case__  :    str							       =errors  # how to handle errors in decoding
       snake_case__  :    Dict							       =bytes_to_unicode()
       snake_case__  :    str							       ={v: k for k, v in self.byte_encoder.items()}
       with open(a				,			encoding="""utf-8"""   ) as merges_handle:
        snake_case__  :    List[Any]							       =merges_handle.read().split("""\n"""   )[1:-1]
       snake_case__  :    List[Any]							       =[tuple(merge.split()   ) for merge in bpe_merges]
       snake_case__  :    str							       =dict(zip(a				,			range(len(a   )   )   )   )
       snake_case__  :    Optional[int]							       ={}
       snake_case__  :    List[str]							       =add_prefix_space

       # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
       snake_case__  :    List[str]							       =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 						lowercase__					(     self   ):
       return len(self.encoder   )
      def 						lowercase__					(     self   ):
       return dict(self.encoder				,			**self.added_tokens_encoder   )
      def 						lowercase__					(     self				,			a   ):
       if token in self.cache:
        return self.cache[token]
       snake_case__  :    List[str]							       =tuple(a   )
       snake_case__  :    Optional[int]							       =get_pairs(a   )

       if not pairs:
        return token

       while True:
        snake_case__  :    Optional[int]							       =min(a				,			key=lambda a   : self.bpe_ranks.get(a				,			float("""inf"""   )   )   )
        if bigram not in self.bpe_ranks:
         break
        snake_case__       ,   snake_case__  :    int							       =bigram
        snake_case__  :    List[Any]							       =[]
        snake_case__  :    int							       =0
        while i < len(a   ):
         try:
          snake_case__  :    Tuple							       =word.index(a				,			a   )
         except ValueError:
          new_word.extend(word[i:]   )
          break
         else:
          new_word.extend(word[i:j]   )
          snake_case__  :    List[str]							       =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__  :    Dict							       =tuple(a   )
        snake_case__  :    Dict							       =new_word
        if len(a   ) == 1:
         break
        else:
         snake_case__  :    int							       =get_pairs(a   )
       snake_case__  :    List[Any]							       =""" """.join(a   )
       snake_case__  :    Union[str, Any]							       =word
       return word
      def 						lowercase__					(     self				,			a   ):
       snake_case__  :    Optional[int]							       =[]
       for token in re.findall(self.pat				,			a   ):
        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(a   ).split(""" """   )   )
       return bpe_tokens
      def 						lowercase__					(     self				,			a   ):
       return self.encoder.get(a				,			self.encoder.get(self.unk_token   )   )
      def 						lowercase__					(     self				,			a   ):
       return self.decoder.get(a   )
      def 						lowercase__					(     self				,			a   ):
       snake_case__  :    Tuple							       ="""""".join(a   )
       snake_case__  :    List[str]							       =bytearray([self.byte_decoder[c] for c in text]   ).decode("""utf-8"""				,			errors=self.errors   )
       return text
      def 						lowercase__					(     self				,			a				,			a = None   ):
       if not os.path.isdir(a   ):
        logger.error(F"Vocabulary path ({save_directory}) should be a directory"   )
        return
       snake_case__  :    List[Any]							       =os.path.join(
           a				,			(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]   )
       snake_case__  :    Optional[Any]							       =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__  :    List[str]							       =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__  :    List[Any]							       =token_index
         writer.write(""" """.join(a   ) + """\n"""   )
         index += 1

       return vocab_file, merge_file
      def 						lowercase__					(     self				,			a				,			a = None   ):
       if token_ids_a is None:
        return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
       snake_case__  :    str							       =[self.cls_token_id]
       snake_case__  :    Optional[Any]							       =[self.sep_token_id]
       return cls + token_ids_a + sep + sep + token_ids_a + sep
      def 						lowercase__					(     self				,			a				,			a = None				,			a = False   ):
       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 						lowercase__					(     self				,			a				,			a = None   ):
       snake_case__  :    Optional[Any]							       =[self.sep_token_id]
       snake_case__  :    Optional[Any]							       =[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 						lowercase__					(     self				,			a				,			a=False				,			**a   ):
       snake_case__  :    Tuple							       =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__  :    List[Any]							       =""" """ + text
       return (text, kwargs)



      def 						lowercase__					(     self				,			a				,			a = None				,			a = PaddingStrategy.DO_NOT_PAD				,			a = None				,			a = None				,			):
       snake_case__  :    str							       =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__  :    List[str]							       ="""attention_mask""" in self.model_input_names

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

        if needs_to_be_padded:
         snake_case__  :    Optional[Any]							       =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__  :    List[Any]							       =(
              encoded_inputs["""global_attention_mask"""] + [-1] * difference
          )
         elif self.padding_side == "left":
          snake_case__  :    Union[str, Any]							       =[-1] * difference + encoded_inputs[
              """global_attention_mask"""
          ]
         else:
          raise ValueError("""Invalid padding strategy:""" + str(self.padding_side   )   )

       return encoded_inputs













__lowerCamelCase	:		dict[str, float]										=   {
    "km/h": 1.0,
    "m/s": 3.6,
    "mph": 1.60_93_44,
    "knot": 1.8_52,
}

__lowerCamelCase	:		dict[str, float]										=   {
    "km/h": 1.0,
    "m/s": 0.2_77_77_77_78,
    "mph": 0.6_21_37_11_92,
    "knot": 0.5_39_95_68_03,
}







def 			A__							(      _a  :					float		,  _a  :					str		,  _a  :					str	):





 '''simple docstring'''







 if unit_to not in speed_chart or unit_from not in speed_chart_inverse:
  snake_case__  :    Tuple							       =(
      f"Incorrect 'from_type' or 'to_type' value: {unit_from!r}, {unit_to!r}\n"
      f"Valid values are: {', '.join(_a	)}"
  )
  raise ValueError(_a	)
 return round(speed * speed_chart[unit_from] * speed_chart_inverse[unit_to]		,  3	)


if __name__ == "__main__":
       import doctest

       doctest.testmod()





