





'''simple docstring'''







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


_lowercase       						=			logging.get_logger(__name__)


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

# See all LED models at https://huggingface.co/models?filter=LED
_lowercase       						=			{
    "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",
    },
}

_lowercase       						=			{
    "allenai/led-base-16384": 16_384,
}






@lru_cache()
# Copied from transformers.models.bart.tokenization_bart.bytes_to_unicode
def    __UpperCamelCase	(	) ->List[str]:
 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(_A     )
   cs.append(2**8 + n     )
   n += 1
 snake_case				=			[chr(_A     ) for n in cs]
 return dict(zip(_A					,   _A     )     )






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






class 			_lowercase						(       lowercase__					):
     _UpperCAmelCase										=					VOCAB_FILES_NAMES
     _UpperCAmelCase										=					PRETRAINED_VOCAB_FILES_MAP
     _UpperCAmelCase										=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     _UpperCAmelCase										=					['''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__    ,   ) ->	Any:
      snake_case				=			AddedToken(__lowerCamelCase    ,   lstrip=__lowerCamelCase    ,   rstrip=__lowerCamelCase    ) if isinstance(__lowerCamelCase    ,   __lowerCamelCase    ) else bos_token
      snake_case				=			AddedToken(__lowerCamelCase    ,   lstrip=__lowerCamelCase    ,   rstrip=__lowerCamelCase    ) if isinstance(__lowerCamelCase    ,   __lowerCamelCase    ) else eos_token
      snake_case				=			AddedToken(__lowerCamelCase    ,   lstrip=__lowerCamelCase    ,   rstrip=__lowerCamelCase    ) if isinstance(__lowerCamelCase    ,   __lowerCamelCase    ) else sep_token
      snake_case				=			AddedToken(__lowerCamelCase    ,   lstrip=__lowerCamelCase    ,   rstrip=__lowerCamelCase    ) if isinstance(__lowerCamelCase    ,   __lowerCamelCase    ) else cls_token
      snake_case				=			AddedToken(__lowerCamelCase    ,   lstrip=__lowerCamelCase    ,   rstrip=__lowerCamelCase    ) if isinstance(__lowerCamelCase    ,   __lowerCamelCase    ) else unk_token
      snake_case				=			AddedToken(__lowerCamelCase    ,   lstrip=__lowerCamelCase    ,   rstrip=__lowerCamelCase    ) if isinstance(__lowerCamelCase    ,   __lowerCamelCase    ) else pad_token

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

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

      with open(__lowerCamelCase    ,   encoding='''utf-8'''    ) as vocab_handle:
       snake_case				=			json.load(__lowerCamelCase    )
      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(__lowerCamelCase    ,   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(__lowerCamelCase    ,   range(len(__lowerCamelCase    )    )    )    )
      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     UpperCamelCase			( self    ) ->	Optional[int]:
      return len(self.encoder    )







     def     UpperCamelCase			( self    ) ->	Optional[Any]:
      return dict(self.encoder    ,   **self.added_tokens_encoder    )







     def     UpperCamelCase			( self    ,   A__    ) ->	List[Any]:



      if token in self.cache:
       return self.cache[token]
      snake_case				=			tuple(__lowerCamelCase    )
      snake_case				=			get_pairs(__lowerCamelCase    )

      if not pairs:
       return token

      while True:
       snake_case				=			min(__lowerCamelCase    ,   key=lambda A__    : self.bpe_ranks.get(__lowerCamelCase    ,   float('''inf'''    )    )    )
       if bigram not in self.bpe_ranks:
        break
       snake_case				=			bigram
       snake_case				=			[]
       snake_case				=			0
       while i < len(__lowerCamelCase    ):
        try:
         snake_case				=			word.index(__lowerCamelCase    ,   __lowerCamelCase    )
        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(__lowerCamelCase    ) - 1 and word[i + 1] == second:
         new_word.append(first + second    )
         i += 2
        else:
         new_word.append(word[i]    )
         i += 1
       snake_case				=			tuple(__lowerCamelCase    )
       snake_case				=			new_word
       if len(__lowerCamelCase    ) == 1:
        break
       else:
        snake_case				=			get_pairs(__lowerCamelCase    )
      snake_case				=			" ".join(__lowerCamelCase    )
      snake_case				=			word
      return word







     def     UpperCamelCase			( self    ,   A__    ) ->	str:
      snake_case				=			[]
      for token in re.findall(self.pat    ,   __lowerCamelCase    ):
       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(__lowerCamelCase    ).split(''' '''    )    )
      return bpe_tokens







     def     UpperCamelCase			( self    ,   A__    ) ->	Dict:
      return self.encoder.get(__lowerCamelCase    ,   self.encoder.get(self.unk_token    )    )







     def     UpperCamelCase			( self    ,   A__    ) ->	List[str]:
      return self.decoder.get(__lowerCamelCase    )







     def     UpperCamelCase			( self    ,   A__    ) ->	Any:
      snake_case				=			"".join(__lowerCamelCase    )
      snake_case				=			bytearray([self.byte_decoder[c] for c in text]    ).decode('''utf-8'''    ,   errors=self.errors    )
      return text







     def     UpperCamelCase			( self    ,   A__    ,   A__ = None    ) ->	Optional[Any]:



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

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

      snake_case				=			0
      with open(__lowerCamelCase    ,   '''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(__lowerCamelCase    ) + '''\n'''    )
        index += 1

      return vocab_file, merge_file







     def     UpperCamelCase			( self    ,   A__    ,   A__ = None    ) ->	List[str]:



      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     UpperCamelCase			( self    ,   A__    ,   A__ = None    ,   A__ = False    ) ->	Any:



      if already_has_special_tokens:
       return super().get_special_tokens_mask(
           token_ids_a=__lowerCamelCase    ,   token_ids_a=__lowerCamelCase    ,   already_has_special_tokens=__lowerCamelCase    )

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







     def     UpperCamelCase			( self    ,   A__    ,   A__ = None    ) ->	Optional[Any]:
      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     UpperCamelCase			( self    ,   A__    ,   A__=False    ,   **A__    ) ->	List[Any]:
      snake_case				=			kwargs.pop('''add_prefix_space'''    ,   self.add_prefix_space    )
      if (is_split_into_words or add_prefix_space) and (len(__lowerCamelCase    ) > 0 and not text[0].isspace()):
       snake_case				=			" " + text
      return (text, kwargs)







     def     UpperCamelCase			( self    ,   A__    ,   A__ = None    ,   A__ = PaddingStrategy.DO_NOT_PAD    ,   A__ = None    ,   A__ = None    ,   ) ->	Any:
      snake_case				=			super()._pad(
          encoded_inputs=__lowerCamelCase    ,   max_length=__lowerCamelCase    ,   padding_strategy=__lowerCamelCase    ,   pad_to_multiple_of=__lowerCamelCase    ,   return_attention_mask=__lowerCamelCase    ,   )

      # 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(__lowerCamelCase    )

       if needs_to_be_padded:
        snake_case				=			len(__lowerCamelCase    ) - 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








'''simple docstring'''







from collections import Counter
from pathlib import Path
from typing import Optional, Tuple

import yaml
class 			_lowercase						(       yaml.SafeLoader					):







     def     UpperCamelCase			( self    ,   A__    ) ->	List[str]:
      snake_case				=			[self.constructed_objects[key_node] for key_node, _ in node.value]
      snake_case				=			[tuple(A__    ) if isinstance(A__    ,   A__    ) else key for key in keys]
      snake_case				=			Counter(A__    )
      snake_case				=			[key for key in counter if counter[key] > 1]
      if duplicate_keys:
       raise TypeError(F"""Got duplicate yaml keys: {duplicate_keys}"""    )







     def     UpperCamelCase			( self    ,   A__    ,   A__=False    ) ->	List[Any]:
      snake_case				=			super().construct_mapping(A__    ,   deep=A__    )
      self._check_no_duplicates_on_constructed_node(A__    )
      return mapping




def    __UpperCamelCase	(	a    : str     ) ->Tuple[Optional[str], str]:
 snake_case				=			list(readme_content.splitlines()     )
 if full_content and full_content[0] == "---" and "---" in full_content[1:]:
  snake_case				=			full_content[1:].index('''---'''     ) + 1
  snake_case				=			'''\n'''.join(full_content[1:sep_idx]     )
  return yamlblock, "\n".join(full_content[sep_idx + 1 :]     )

 return None, "\n".join(a     )
class 			_lowercase						(       __a					):
     # class attributes
     _UpperCAmelCase										=					{'''train_eval_index'''}  # train-eval-index in the YAML metadata







     @classmethod
     def     UpperCamelCase			( cls    ,   A__    ) ->	"DatasetMetadata":
      with open(A__    ,   encoding='''utf-8'''    ) as readme_file:
       snake_case				,		snake_case				=			_split_yaml_from_readme(readme_file.read()    )
      if yaml_string is not None:
       return cls.from_yaml_string(A__    )
      else:
       return cls()







     def     UpperCamelCase			( self    ,   A__    ) ->	str:
      if path.exists():
       with open(A__    ,   encoding='''utf-8'''    ) as readme_file:
        snake_case				=			readme_file.read()
      else:
       snake_case				=			None
      snake_case				=			self._to_readme(A__    )
      with open(A__    ,   '''w'''    ,   encoding='''utf-8'''    ) as readme_file:
       readme_file.write(A__    )







     def     UpperCamelCase			( self    ,   A__ = None    ) ->	str:
      if readme_content is not None:
       snake_case				,		snake_case				=			_split_yaml_from_readme(A__    )
       snake_case				=			'''---\n''' + self.to_yaml_string() + '''---\n''' + content
      else:
       snake_case				=			'''---\n''' + self.to_yaml_string() + '''---\n'''
      return full_content







     @classmethod
     def     UpperCamelCase			( cls    ,   A__    ) ->	"DatasetMetadata":
      snake_case				=			yaml.load(A__    ,   Loader=_NoDuplicateSafeLoader    ) or {}

      # Convert the YAML keys to DatasetMetadata fields
      snake_case				=			{
          (key.replace('''-'''    ,   '''_'''    ) if key.replace('''-'''    ,   '''_'''    ) in cls._FIELDS_WITH_DASHES else key): value
          for key, value in metadata_dict.items()
      }
      return cls(**A__    )







     def     UpperCamelCase			( self    ) ->	str:
      return yaml.safe_dump(
          {
              (key.replace('''_'''    ,   '''-'''    ) if key in self._FIELDS_WITH_DASHES else key): value
              for key, value in self.items()
          }    ,   sort_keys=A__    ,   allow_unicode=A__    ,   encoding='''utf-8'''    ,   ).decode('''utf-8'''    )




_lowercase       						=			{
    'image-classification': [],
    'translation': [],
    'image-segmentation': [],
    'fill-mask': [],
    'automatic-speech-recognition': [],
    'token-classification': [],
    'sentence-similarity': [],
    'audio-classification': [],
    'question-answering': [],
    'summarization': [],
    'zero-shot-classification': [],
    'table-to-text': [],
    'feature-extraction': [],
    'other': [],
    'multiple-choice': [],
    'text-classification': [],
    'text-to-image': [],
    'text2text-generation': [],
    'zero-shot-image-classification': [],
    'tabular-classification': [],
    'tabular-regression': [],
    'image-to-image': [],
    'tabular-to-text': [],
    'unconditional-image-generation': [],
    'text-retrieval': [],
    'text-to-speech': [],
    'object-detection': [],
    'audio-to-audio': [],
    'text-generation': [],
    'conversational': [],
    'table-question-answering': [],
    'visual-question-answering': [],
    'image-to-text': [],
    'reinforcement-learning': [],
    'voice-activity-detection': [],
    'time-series-forecasting': [],
    'document-question-answering': [],
}


if __name__ == "__main__":
   from argparse import ArgumentParser

   _lowercase       						=			ArgumentParser(usage='Validate the yaml metadata block of a README.md file.')
   ap.add_argument('readme_filepath')
   _lowercase       						=			ap.parse_args()

   _lowercase       						=			Path(args.readme_filepath)
   _lowercase       						=			DatasetMetadata.from_readme(readme_filepath)
   print(dataset_metadata)
   dataset_metadata.to_readme(readme_filepath)

