


'''simple docstring'''


from typing import Optional, Union

from ...file_utils import TensorType
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, TruncationStrategy







class        __magic_name__  (					lowerCAmelCase   ):

     """simple docstring"""






     lowerCamelCase__						=							'MarkupLMFeatureExtractor'
     lowerCamelCase__						=							('MarkupLMTokenizer', 'MarkupLMTokenizerFast')
     lowerCamelCase__						=							True


     def __call__(      self ,    lowerCamelCase=None ,    lowerCamelCase=None ,    lowerCamelCase=None ,    lowerCamelCase=None ,    lowerCamelCase=None ,    lowerCamelCase = True ,    lowerCamelCase = False ,    lowerCamelCase = None ,    lowerCamelCase = None ,    lowerCamelCase = 0 ,    lowerCamelCase = None ,    lowerCamelCase = None ,    lowerCamelCase = None ,    lowerCamelCase = False ,    lowerCamelCase = False ,    lowerCamelCase = False ,    lowerCamelCase = False ,    lowerCamelCase = True ,    lowerCamelCase = None ,    **lowerCamelCase ,    ):


          '''simple docstring'''





          if self.parse_html:
               if html_strings is None:
                    raise ValueError("Make sure to pass HTML strings in case `parse_html` is set to `True`"		)

               if nodes is not None or xpaths is not None or node_labels is not None:
                    raise ValueError(
                        "Please don't pass nodes, xpaths nor node labels in case `parse_html` is set to `True`"		)

               __A  :					Dict						     =       self.feature_extractor(lowerCamelCase		)
               __A  :					Dict						     =       features["nodes"]
               __A  :					int						     =       features["xpaths"]
          else:
               if html_strings is not None:
                    raise ValueError("You have passed HTML strings but `parse_html` is set to `False`."		)
               if nodes is None or xpaths is None:
                    raise ValueError("Make sure to pass nodes and xpaths in case `parse_html` is set to `False`"		)

        # # second, apply the tokenizer
          if questions is not None and self.parse_html:
               if isinstance(lowerCamelCase ,    lowerCamelCase		):
                    __A  :					Optional[int]						     =       [questions]  # add batch dimension (as the feature extractor always adds a batch dimension)

          __A  :					Any						     =       self.tokenizer(
              text=questions if questions is not None else nodes ,    text_pair=nodes if questions is not None else None ,    xpaths=lowerCamelCase ,    node_labels=lowerCamelCase ,    add_special_tokens=lowerCamelCase ,    padding=lowerCamelCase ,    truncation=lowerCamelCase ,    max_length=lowerCamelCase ,    stride=lowerCamelCase ,    pad_to_multiple_of=lowerCamelCase ,    return_token_type_ids=lowerCamelCase ,    return_attention_mask=lowerCamelCase ,    return_overflowing_tokens=lowerCamelCase ,    return_special_tokens_mask=lowerCamelCase ,    return_offsets_mapping=lowerCamelCase ,    return_length=lowerCamelCase ,    verbose=lowerCamelCase ,    return_tensors=lowerCamelCase ,    **lowerCamelCase ,    )

          return encoded_inputs


     def lowerCAmelCase__     (      self ,    *lowerCamelCase ,    **lowerCamelCase		):


          '''simple docstring'''





          return self.tokenizer.batch_decode(*lowerCamelCase ,    **lowerCamelCase		)


     def lowerCAmelCase__     (      self ,    *lowerCamelCase ,    **lowerCamelCase		):


          '''simple docstring'''





          return self.tokenizer.decode(*lowerCamelCase ,    **lowerCamelCase		)


     @property
     def lowerCAmelCase__     (      self		):


          '''simple docstring'''





          __A  :					Dict						     =       self.tokenizer.model_input_names
          return tokenizer_input_names





'''simple docstring'''


from collections import defaultdict


def 		_lowercase   (SCREAMING_SNAKE_CASE = 5       ):




     '''simple docstring'''





     __A  :					int						     =       defaultdict(SCREAMING_SNAKE_CASE       )
     __A  :					Optional[Any]						     =       0

     while True:
          __A  :					List[str]						     =       get_digits(SCREAMING_SNAKE_CASE       )
          freqs[digits].append(SCREAMING_SNAKE_CASE       )

          if len(freqs[digits]       ) == max_base:
               __A  :					Optional[int]						     =       freqs[digits][0] ** 3
               return base

          num += 1


def 		_lowercase   (SCREAMING_SNAKE_CASE       ):




     '''simple docstring'''





     return "".join(sorted(str(num**3       )       )       )


if __name__ == "__main__":
      print(F"""{solution() = }""")

