


'''simple docstring'''







import os
from shutil import copyfile
from typing import Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
  from .tokenization_reformer import ReformerTokenizer
else:
  a__    :   Dict								=			None


a__    :   int								=			logging.get_logger(__name__)


a__    :   Optional[Any]								=			'▁'

a__    :   Union[str, Any]								=			{'vocab_file': 'spiece.model', 'tokenizer_file': 'tokenizer.json'}

a__    :   List[str]								=			{
    'vocab_file': {
        'google/reformer-crime-and-punishment': (
            'https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/spiece.model'
        )
    },
    'tokenizer_file': {
        'google/reformer-crime-and-punishment': (
            'https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/tokenizer.json'
        )
    },
}

a__    :   Dict								=			{
    'google/reformer-crime-and-punishment': 5_2_4_2_8_8,
}
class    lowercase_	(       a__  ):
    __UpperCAmelCase       =      VOCAB_FILES_NAMES
    __UpperCAmelCase       =      PRETRAINED_VOCAB_FILES_MAP
    __UpperCAmelCase       =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    __UpperCAmelCase       =      ['input_ids', 'attention_mask']
    __UpperCAmelCase       =      ReformerTokenizer


    def __init__(	self    ,   a=None    ,   a=None    ,   a="</s>"    ,   a="<unk>"    ,   a=[]    ,   **a    ,   ):
          super().__init__(
              a    ,   tokenizer_file=a    ,   eos_token=a    ,   unk_token=a    ,   additional_special_tokens=a    ,   **a    ,   )

          UpperCamelCase__      =							vocab_file
          UpperCamelCase__      =							False if not self.vocab_file else True


    def   __a				(	self    ,   a    ,   a = None       ):
          if not self.can_save_slow_tokenizer:
                raise ValueError(
                    "Your fast tokenizer does not have the necessary information to save the vocabulary for a slow "
                    "tokenizer."       )

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

          if os.path.abspath(self.vocab_file       ) != os.path.abspath(a       ):
                copyfile(self.vocab_file    ,   a       )

          return (out_vocab_file,)









'''simple docstring'''







from __future__ import annotations

# Define the Gravitational Constant G and the function
a__    :   Optional[int]								=			6.67_43E-11  # unit of G : m^3 * kg^-1 * s^-2







def _UpperCamelCase			(	__A ,     __A ,     __A ,     __A       )				->						dict[str, float]:


      '''simple docstring'''



      UpperCamelCase__      =							mass_a * mass_a

      if (force, mass_a, mass_a, distance).count(0       ) != 1:
            raise ValueError("One and only one argument must be 0"       )
      if force < 0:
            raise ValueError("Gravitational force can not be negative"       )
      if distance < 0:
            raise ValueError("Distance can not be negative"       )
      if mass_a < 0 or mass_a < 0:
            raise ValueError("Mass can not be negative"       )
      if force == 0:
            UpperCamelCase__      =							GRAVITATIONAL_CONSTANT * product_of_mass / (distance**2)
            return {"force": force}
      elif mass_a == 0:
            UpperCamelCase__      =							(force) * (distance**2) / (GRAVITATIONAL_CONSTANT * mass_a)
            return {"mass_1": mass_a}
      elif mass_a == 0:
            UpperCamelCase__      =							(force) * (distance**2) / (GRAVITATIONAL_CONSTANT * mass_a)
            return {"mass_2": mass_a}
      elif distance == 0:
            UpperCamelCase__      =							(GRAVITATIONAL_CONSTANT * product_of_mass / (force)) ** 0.5
            return {"distance": distance}
      raise ValueError("One and only one argument must be 0"       )


# Run doctest
if __name__ == "__main__":
  import doctest

  doctest.testmod()





