


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


SCREAMING_SNAKE_CASE			: str				   =					logging.get_logger(__name__)

SCREAMING_SNAKE_CASE			: List[str]				   =					{"vocab_file": "vocab.txt"}

SCREAMING_SNAKE_CASE			: Optional[int]				   =					{
    "vocab_file": {
        "openbmb/cpm-ant-10b": "https://huggingface.co/openbmb/cpm-ant-10b/blob/main/vocab.txt",
    },
}

SCREAMING_SNAKE_CASE			: Any				   =					{
    "openbmb/cpm-ant-10b": 1024,
}



def 							UpperCamelCase_( lowerCamelCase_					)       ->		List[str]:
    _lowercase			:				List[str] 						=						collections.OrderedDict()
    with open(lowerCamelCase_				,					'r'				,					encoding='utf-8'					) as reader:
        _lowercase			:				Tuple 						=						reader.readlines()
    for index, token in enumerate(lowerCamelCase_					):
        _lowercase			:				Dict 						=						token.rstrip('\n'					)
        _lowercase			:				List[Any] 						=						index
    return vocab






class _lowerCamelCase(		_a  ):
       def __init__(   self, lowerCamelCase, lowerCamelCase="<unk>", lowerCamelCase=2_00)			->  List[str]:




           """simple docstring"""

           _lowercase			:				Any 						=						vocab
           _lowercase			:				Tuple 						=						unk_token
           _lowercase			:				Any 						=						max_input_chars_per_word




       def      UpperCamelCase	(   self, lowerCamelCase)			->  Any:




           """simple docstring"""

           _lowercase			:				Dict 						=						list(lowerCamelCase)
           if len(lowerCamelCase) > self.max_input_chars_per_word:
               return [self.unk_token]

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

           return sub_tokens






class _lowerCamelCase(		_a  ):
       lowercase_					:      Any       					=     VOCAB_FILES_NAMES
       lowercase_					:      List[str]       					=     PRETRAINED_VOCAB_FILES_MAP
       lowercase_					:      Dict       					=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       lowercase_					:      str       					=     ["""input_ids""", """attention_mask"""]
       lowercase_					:      int       					=     False
       def __init__(   self, lowerCamelCase, lowerCamelCase="<d>", lowerCamelCase="</d>", lowerCamelCase="<s>", lowerCamelCase="</s>", lowerCamelCase="<pad>", lowerCamelCase="<unk>", lowerCamelCase="</n>", lowerCamelCase="</_>", lowerCamelCase="left", **lowerCamelCase, )			->  List[str]:




           """simple docstring"""

           requires_backends(self, ['jieba'])
           super().__init__(
               bod_token=lowerCamelCase, eod_token=lowerCamelCase, bos_token=lowerCamelCase, eos_token=lowerCamelCase, pad_token=lowerCamelCase, unk_token=lowerCamelCase, line_token=lowerCamelCase, space_token=lowerCamelCase, padding_side=lowerCamelCase, **lowerCamelCase, )
           _lowercase			:				int 						=						bod_token
           _lowercase			:				Tuple 						=						eod_token
           _lowercase			:				Optional[int] 						=						load_vocab(lowerCamelCase)
           _lowercase			:				List[Any] 						=						self.encoder[space_token]
           _lowercase			:				Any 						=						self.encoder[line_token]

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

           _lowercase			:				Tuple 						=						collections.OrderedDict(sorted(self.encoder.items(), key=lambda lowerCamelCase: x[1]))
           _lowercase			:				Tuple 						=						{v: k for k, v in self.encoder.items()}

           _lowercase			:				Union[str, Any] 						=						WordpieceTokenizer(vocab=self.encoder, unk_token=self.unk_token)
       @property
       def      UpperCamelCase	(   self)			->  Union[str, Any]:




           """simple docstring"""

           return self.encoder[self.bod_token]
       @property
       def      UpperCamelCase	(   self)			->  int:




           """simple docstring"""

           return self.encoder[self.eod_token]
       @property
       def      UpperCamelCase	(   self)			->  List[str]:




           """simple docstring"""

           return self.encoder["\n"]
       @property
       def      UpperCamelCase	(   self)			->  int:




           """simple docstring"""

           return len(self.encoder)
       def      UpperCamelCase	(   self)			->  Optional[int]:




           """simple docstring"""

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




           """simple docstring"""

           _lowercase			:				Optional[Any] 						=						[]
           for x in jieba.cut(lowerCamelCase, cut_all=lowerCamelCase):
               output_tokens.extend(self.wordpiece_tokenizer.tokenize(lowerCamelCase))
           return output_tokens
       def      UpperCamelCase	(   self, lowerCamelCase, **lowerCamelCase)			->  Union[str, Any]:




           """simple docstring"""

           _lowercase			:				List[str] 						=						[i for i in token_ids if i >= 0]
           _lowercase			:				List[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(lowerCamelCase, **lowerCamelCase)
       def      UpperCamelCase	(   self, lowerCamelCase)			->  int:




           """simple docstring"""

           return token in self.encoder
       def      UpperCamelCase	(   self, lowerCamelCase)			->  str:




           """simple docstring"""

           return "".join(lowerCamelCase)
       def      UpperCamelCase	(   self, lowerCamelCase)			->  Optional[Any]:




           """simple docstring"""

           return self.encoder.get(lowerCamelCase, self.encoder.get(self.unk_token))
       def      UpperCamelCase	(   self, lowerCamelCase)			->  Tuple:




           """simple docstring"""

           return self.decoder.get(lowerCamelCase, self.unk_token)
       def      UpperCamelCase	(   self, lowerCamelCase, lowerCamelCase = None)			->  Tuple[str]:




           """simple docstring"""

           if os.path.isdir(lowerCamelCase):
               _lowercase			:				Tuple 						=						os.path.join(
                   lowerCamelCase, (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'])
           else:
               _lowercase			:				Optional[Any] 						=						(filename_prefix + '-' if filename_prefix else '') + save_directory
           _lowercase			:				List[Any] 						=						0
           if " " in self.encoder:
               _lowercase			:				Optional[int] 						=						self.encoder[' ']
               del self.encoder[" "]
           if "\n" in self.encoder:
               _lowercase			:				List[str] 						=						self.encoder['\n']
               del self.encoder["\n"]
           _lowercase			:				Union[str, Any] 						=						collections.OrderedDict(sorted(self.encoder.items(), key=lambda lowerCamelCase: x[1]))
           with open(lowerCamelCase, '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!')
                       _lowercase			:				str 						=						token_index
                   writer.write(token + '\n')
                   index += 1
           return (vocab_file,)
       def      UpperCamelCase	(   self, lowerCamelCase, lowerCamelCase = None)			->  List[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      UpperCamelCase	(   self, lowerCamelCase, lowerCamelCase = None, lowerCamelCase = False)			->  List[int]:




           """simple docstring"""

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






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
SCREAMING_SNAKE_CASE			: Union[str, Any]				   =					1.0_5457_1817E-34  # unit of ℏ : J * s

SCREAMING_SNAKE_CASE			: int				   =					3E8  # unit of c : m * s^-1



def 							UpperCamelCase_( lowerCamelCase_				,					lowerCamelCase_				,					lowerCamelCase_					)       ->		dict[str, float]:

    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:
        _lowercase			:				int 						=						(REDUCED_PLANCK_CONSTANT * SPEED_OF_LIGHT * pi**2 * area) / (
            240 * (distance) ** 4
        )
        return {"force": force}
    elif area == 0:
        _lowercase			:				List[Any] 						=						(240 * force * (distance) ** 4) / (
            REDUCED_PLANCK_CONSTANT * SPEED_OF_LIGHT * pi**2
        )
        return {"area": area}
    elif distance == 0:
        _lowercase			:				List[Any] 						=						(
            (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()


