






"""simple docstring"""


from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_clip import CLIPTokenizer


_UpperCamelCase :    Optional[Any]      =			logging.get_logger(__name__)

_UpperCamelCase :    List[str]      =			{'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', 'tokenizer_file': 'tokenizer.json'}

_UpperCamelCase :    Union[str, Any]      =			{
    'vocab_file': {
        'openai/clip-vit-base-patch32': 'https://huggingface.co/openai/clip-vit-base-patch32/resolve/main/vocab.json',
    },
    'merges_file': {
        'openai/clip-vit-base-patch32': 'https://huggingface.co/openai/clip-vit-base-patch32/resolve/main/merges.txt',
    },
    'tokenizer_file': {
        'openai/clip-vit-base-patch32': (
            'https://huggingface.co/openai/clip-vit-base-patch32/resolve/main/tokenizer.json'
        ),
    },
}

_UpperCamelCase :    Optional[Any]      =			{
    'openai/clip-vit-base-patch32': 77,
}






class __a ( SCREAMING_SNAKE_CASE__					):
  __lowercase     :     List[Any]       						=       VOCAB_FILES_NAMES
  __lowercase     :     Dict       						=       PRETRAINED_VOCAB_FILES_MAP
  __lowercase     :     Optional[int]       						=       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  __lowercase     :     List[Any]       						=       ['input_ids', 'attention_mask']
  __lowercase     :     str       						=       CLIPTokenizer



  def __init__(self	:		Dict					,      lowercase_	:		Optional[int]=None					,      lowercase_	:		Tuple=None					,      lowercase_	:		int=None					,      lowercase_	:		str="<|endoftext|>"					,      lowercase_	:		List[str]="<|startoftext|>"					,      lowercase_	:		str="<|endoftext|>"					,      lowercase_	:		Tuple="<|endoftext|>"					,      **lowercase_	:		List[Any]					,      )		->				Any:
   super().__init__(
       lowercase_					,      lowercase_					,      tokenizer_file=lowercase_					,      unk_token=lowercase_					,      bos_token=lowercase_					,      eos_token=lowercase_					,      pad_token=lowercase_					,      **lowercase_					,      )

   if not isinstance(self.backend_tokenizer.pre_tokenizer					,      pre_tokenizers.Sequence ):
    raise ValueError(
        'The `backend_tokenizer` provided does not match the expected format. The CLIP tokenizer has been'
        ' heavily modified from transformers version 4.17.0. You need to convert the tokenizer you are using'
        ' to be compatible with this version.The easiest way to do so is'
        ' `CLIPTokenizerFast.from_pretrained("path_to_local_folder_or_hub_repo, from_slow=True)`. If you want'
        ' to use your existing tokenizer, you will have to revert to a version prior to 4.17.0 of'
        ' transformers.' )

   self._wrap_decode_method_backend_tokenizer()



  def     A_					(self	:		Optional[int] )		->				List[str]:
   __A						:							Tuple      =						self.backend_tokenizer.decode

   def new_decode_method(*lowercase_	:		str					,      **lowercase_	:		Optional[Any] ):
    __A						:							List[Any]      =						orig_decode_method(*lowercase_					,      **lowercase_ )
    __A						:							Any      =						text.replace(self.backend_tokenizer.model.end_of_word_suffix					,      ' ' ).strip()
    return text

   __A						:							Optional[int]      =						new_decode_method



  def     A_					(self	:		Optional[int]					,      lowercase_	:		List[int]					,      lowercase_	:		Optional[List[int]] = None )		->				List[int]:
   __A						:							List[str]      =						[self.bos_token_id]
   __A						:							Any      =						[self.eos_token_id]

   if token_ids_a is None:
    return bos_token + token_ids_a + eos_token
   return bos_token + token_ids_a + eos_token + eos_token + token_ids_a + eos_token



  def     A_					(self	:		str					,      lowercase_	:		List[int]					,      lowercase_	:		Optional[List[int]] = None )		->				List[int]:
   __A						:							Optional[int]      =						[self.bos_token_id]
   __A						:							int      =						[self.eos_token_id]

   if token_ids_a is None:
    return len(bos_token + token_ids_a + eos_token ) * [0]
   return len(bos_token + token_ids_a + eos_token + eos_token + token_ids_a + eos_token ) * [0]



  def     A_					(self	:		int					,      lowercase_	:		str					,      lowercase_	:		Optional[str] = None )		->				Tuple[str]:
   __A						:							Union[str, Any]      =						self._tokenizer.model.save(lowercase_					,      name=lowercase_ )
   return tuple(lowercase_ )










"""simple docstring"""




from __future__ import annotations

# Define the Gravitational Constant G and the function
_UpperCamelCase:					Tuple     				=	6.6_7_4_3e-1_1  # unit of G : m^3 * kg^-1 * s^-2


def 	lowercase__  (      _UpperCAmelCase						,   _UpperCAmelCase						,   _UpperCAmelCase						,   _UpperCAmelCase					)  ->      dict[str, float]:






      '''simple docstring'''


      lowercase	:   str											= 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:
            lowercase	:   str											= GRAVITATIONAL_CONSTANT * product_of_mass / (distance**2)
            return {"force": force}
      elif mass_a == 0:
            lowercase	:   Optional[int]											= (force) * (distance**2) / (GRAVITATIONAL_CONSTANT * mass_a)
            return {"mass_1": mass_a}
      elif mass_a == 0:
            lowercase	:   Optional[int]											= (force) * (distance**2) / (GRAVITATIONAL_CONSTANT * mass_a)
            return {"mass_2": mass_a}
      elif distance == 0:
            lowercase	:   List[Any]											= (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()
