





import collections
import os
from typing import List, Optional, Tuple

from transformers.utils import is_jieba_available, requires_backends


if is_jieba_available():
   import jieba

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


UpperCAmelCase     :     Union[str, Any]							=	logging.get_logger(__name__)

UpperCAmelCase     :     Any							=	{"""vocab_file""": """vocab.txt"""}

UpperCAmelCase     :     Tuple							=	{
    """vocab_file""": {
        """openbmb/cpm-ant-10b""": """https://huggingface.co/openbmb/cpm-ant-10b/blob/main/vocab.txt""",
    },
}

UpperCAmelCase     :     int							=	{
    """openbmb/cpm-ant-10b""": 1024,
}
def 					_A	(		SCREAMING_SNAKE_CASE					:       str						):





  """simple docstring"""



  a__     : List[str]  =collections.OrderedDict()
  with open(_snake_case	,	"r"	,	encoding="utf-8"						) as reader:
    a__     : Optional[Any]  =reader.readlines()
  for index, token in enumerate(_snake_case						):
    a__     : Union[str, Any]  =token.rstrip("\n"						)
    a__     : Tuple  =index
  return vocab







class     __lowerCAmelCase	(   __snake_case):







      def __init__(   self		,				lowerCAmelCase__		,				lowerCAmelCase__="<unk>"		,				lowerCAmelCase__=2_0_0							)       ->						Union[str, Any]:



        '''simple docstring'''




        a__     : Dict  =vocab
        a__     : Dict  =unk_token
        a__     : Optional[Any]  =max_input_chars_per_word







      def        _lowercase  (   self		,				lowerCAmelCase__							)       ->						List[Any]:



        '''simple docstring'''




        a__     : Any  =list(a_							)
        if len(a_							) > self.max_input_chars_per_word:
          return [self.unk_token]

        a__     : Union[str, Any]  =0
        a__     : Union[str, Any]  =[]
        while start < len(a_							):
          a__     : int  =len(a_							)
          a__     : List[Any]  =None
          while start < end:
            a__     : List[Any]  =''''''.join(chars[start:end]							)
            if substr in self.vocab:
              a__     : int  =substr
              break
            end -= 1
          if cur_substr is None:
            sub_tokens.append(self.unk_token							)
            start += 1
          else:
            sub_tokens.append(a_							)
            a__     : Tuple  =end

        return sub_tokens







class     __lowerCAmelCase	(   __snake_case):
      _lowercase    : int            =      VOCAB_FILES_NAMES
      _lowercase    : Any            =      PRETRAINED_VOCAB_FILES_MAP
      _lowercase    : int            =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      _lowercase    : List[str]            =      ["""input_ids""", """attention_mask"""]
      _lowercase    : str            =      False







      def __init__(   self		,				lowerCAmelCase__		,				lowerCAmelCase__="<d>"		,				lowerCAmelCase__="</d>"		,				lowerCAmelCase__="<s>"		,				lowerCAmelCase__="</s>"		,				lowerCAmelCase__="<pad>"		,				lowerCAmelCase__="<unk>"		,				lowerCAmelCase__="</n>"		,				lowerCAmelCase__="</_>"		,				lowerCAmelCase__="left"		,				**lowerCAmelCase__		,				)       ->						List[Any]:



        '''simple docstring'''




        requires_backends(self		,				["jieba"]							)
        super().__init__(
            bod_token=a_		,				eod_token=a_		,				bos_token=a_		,				eos_token=a_		,				pad_token=a_		,				unk_token=a_		,				line_token=a_		,				space_token=a_		,				padding_side=a_		,				**a_		,				)
        a__     : Dict  =bod_token
        a__     : Dict  =eod_token
        a__     : Optional[Any]  =load_vocab(a_							)
        a__     : Dict  =self.encoder[space_token]
        a__     : Union[str, Any]  =self.encoder[line_token]

        del self.encoder[space_token]
        del self.encoder[line_token]

        a__     : Optional[Any]  =collections.OrderedDict(sorted(self.encoder.items()		,				key=lambda lowerCAmelCase__							: x[1]							)							)
        a__     : Optional[int]  ={v: k for k, v in self.encoder.items()}

        a__     : Union[str, Any]  =WordpieceTokenizer(vocab=self.encoder		,				unk_token=self.unk_token							)







      @property
      def        _lowercase  (   self							)       ->						Optional[int]:



        '''simple docstring'''




        return self.encoder[self.bod_token]







      @property
      def        _lowercase  (   self							)       ->						Any:



        '''simple docstring'''




        return self.encoder[self.eod_token]







      @property
      def        _lowercase  (   self							)       ->						int:



        '''simple docstring'''




        return self.encoder["\n"]







      @property
      def        _lowercase  (   self							)       ->						Tuple:



        '''simple docstring'''




        return len(self.encoder							)







      def        _lowercase  (   self							)       ->						Union[str, Any]:



        '''simple docstring'''




        return dict(self.encoder		,				**self.added_tokens_encoder							)







      def        _lowercase  (   self		,				lowerCAmelCase__							)       ->						Optional[Any]:



        '''simple docstring'''




        a__     : str  =[]
        for x in jieba.cut(a_		,				cut_all=a_							):
          output_tokens.extend(self.wordpiece_tokenizer.tokenize(a_							)							)
        return output_tokens







      def        _lowercase  (   self		,				lowerCAmelCase__		,				**lowerCAmelCase__							)       ->						Any:



        '''simple docstring'''




        a__     : Union[str, Any]  =[i for i in token_ids if i >= 0]
        a__     : Optional[Any]  =[
            x for x in token_ids if x != self.pad_token_id and x != self.eos_token_id and x != self.bos_token_id
        ]
        return super()._decode(a_		,				**a_							)







      def        _lowercase  (   self		,				lowerCAmelCase__							)       ->						Union[str, Any]:



        '''simple docstring'''




        return token in self.encoder







      def        _lowercase  (   self		,				lowerCAmelCase__							)       ->						Optional[int]:



        '''simple docstring'''




        return "".join(a_							)







      def        _lowercase  (   self		,				lowerCAmelCase__							)       ->						Union[str, Any]:



        '''simple docstring'''




        return self.encoder.get(a_		,				self.encoder.get(self.unk_token							)							)







      def        _lowercase  (   self		,				lowerCAmelCase__							)       ->						Union[str, Any]:



        '''simple docstring'''




        return self.decoder.get(a_		,				self.unk_token							)







      def        _lowercase  (   self		,				lowerCAmelCase__		,				lowerCAmelCase__ = None							)       ->						Optional[int]:



        '''simple docstring'''




        if os.path.isdir(a_							):
          a__     : Any  =os.path.join(
              a_		,				(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]							)
        else:
          a__     : Dict  =(filename_prefix + '''-''' if filename_prefix else '''''') + save_directory
        a__     : Any  =0
        if " " in self.encoder:
          a__     : Any  =self.encoder[''' ''']
          del self.encoder[" "]
        if "\n" in self.encoder:
          a__     : List[str]  =self.encoder['''\n''']
          del self.encoder["\n"]
        a__     : str  =collections.OrderedDict(sorted(self.encoder.items()		,				key=lambda lowerCAmelCase__							: x[1]							)							)
        with open(a_		,				"w"		,				encoding="utf-8"							) as writer:
          for token, token_index in self.encoder.items():
            if index != token_index:
              logger.warning(
                  F'''Saving vocabulary to {vocab_file}: vocabulary indices are not consecutive.'''
                  " Please check that the vocabulary is not corrupted!"							)
              a__     : Tuple  =token_index
            writer.write(token + "\n"							)
            index += 1
        return (vocab_file,)







      def        _lowercase  (   self		,				lowerCAmelCase__		,				lowerCAmelCase__ = None							)       ->						Optional[int]:



        '''simple docstring'''




        if token_ids_a is None:
          return [self.bos_token_id] + token_ids_a
        return [self.bos_token_id] + token_ids_a + [self.bos_token_id] + token_ids_a







      def        _lowercase  (   self		,				lowerCAmelCase__		,				lowerCAmelCase__ = None		,				lowerCAmelCase__ = False							)       ->						Optional[int]:



        '''simple docstring'''




        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 not None:
          return [1] + ([0] * len(a_							)) + [1] + ([0] * len(a_							))
        return [1] + ([0] * len(a_							))













from __future__ import annotations

from math import pi

# Define the Reduced Planck Constant ℏ (H bar), speed of light C, value of
# Pi and the function
UpperCAmelCase     :     Union[str, Any]							=	1.054571817E-34  # unit of ℏ : J * s

UpperCAmelCase     :     Union[str, Any]							=	3E8  # unit of c : m * s^-1
def 					_A	(		SCREAMING_SNAKE_CASE					:       float	,	SCREAMING_SNAKE_CASE					:       float	,	SCREAMING_SNAKE_CASE					:       float						):





  """simple docstring"""



  if (force, area, distance).count(0						) != 1:
    raise ValueError("One and only one argument must be 0"						)
  if force < 0:
    raise ValueError("Magnitude of force can not be negative"						)
  if distance < 0:
    raise ValueError("Distance can not be negative"						)
  if area < 0:
    raise ValueError("Area can not be negative"						)
  if force == 0:
    a__     : Tuple  =(REDUCED_PLANCK_CONSTANT * SPEED_OF_LIGHT * pi**2 * area) / (
        240 * (distance) ** 4
    )
    return {"force": force}
  elif area == 0:
    a__     : Any  =(240 * force * (distance) ** 4) / (
        REDUCED_PLANCK_CONSTANT * SPEED_OF_LIGHT * pi**2
    )
    return {"area": area}
  elif distance == 0:
    a__     : List[str]  =(
        (REDUCED_PLANCK_CONSTANT * SPEED_OF_LIGHT * pi**2 * area) / (240 * force)
    ) ** (1 / 4)
    return {"distance": distance}
  raise ValueError("One and only one argument must be 0"						)


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

     doctest.testmod()






