


import json
import os
from typing import Optional, Tuple

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


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

A			:						Optional[Any]        =  {'vocab_file': 'vocab.json'}

A			:						Optional[int]        =  {
    'vocab_file': {
        'mgp-str': 'https://huggingface.co/alibaba-damo/mgp-str-base/blob/main/vocab.json',
    }
}

A			:						Optional[int]        =  {'mgp-str': 2_7}



class 				A       (			UpperCAmelCase__				):
					'''simple docstring'''






					A__     =					VOCAB_FILES_NAMES
					A__     =					PRETRAINED_VOCAB_FILES_MAP
					A__     =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES

					def __init__(self       :		Dict ,   _UpperCAmelCase       :		Union[str, Any] ,   _UpperCAmelCase       :		Optional[int]="[GO]" ,   _UpperCAmelCase       :		Optional[Any]="[GO]" ,   _UpperCAmelCase       :		str="[s]" ,   _UpperCAmelCase       :		int="[GO]" ,   **_UpperCAmelCase       :		Tuple						)		->  List[Any]:




							"""simple docstring"""


							super().__init__(
							    unk_token=_UpperCAmelCase ,   bos_token=_UpperCAmelCase ,   eos_token=_UpperCAmelCase ,   pad_token=_UpperCAmelCase ,   **_UpperCAmelCase ,   )

							with open(_UpperCAmelCase ,   encoding="""utf-8"""						) as vocab_handle:
									lowercase__	     =						json.load(_UpperCAmelCase						)
							lowercase__	     =						{v: k for k, v in self.vocab.items()}

					@property
					def     lowerCamelCase__	(self       :		List[Any]						)		->  int:




							"""simple docstring"""


							return len(self.vocab						)

					def     lowerCamelCase__	(self       :		List[Any]						)		->  Dict:




							"""simple docstring"""


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

					def     lowerCamelCase__	(self       :		List[str] ,   _UpperCAmelCase       :		int						)		->  Dict:




							"""simple docstring"""


							lowercase__	     =						[]
							for s in text:
									char_tokens.extend(_UpperCAmelCase						)
							return char_tokens

					def     lowerCamelCase__	(self       :		str ,   _UpperCAmelCase       :		List[Any]						)		->  List[Any]:




							"""simple docstring"""


							return self.vocab.get(_UpperCAmelCase ,   self.vocab.get(self.unk_token						)						)

					def     lowerCamelCase__	(self       :		List[str] ,   _UpperCAmelCase       :		Union[str, Any]						)		->  Optional[int]:




							"""simple docstring"""


							return self.decoder.get(_UpperCAmelCase						)


					def     lowerCamelCase__	(self       :		Union[str, Any] ,   _UpperCAmelCase       :		str ,   _UpperCAmelCase       :		Optional[str] = None						)		->  Tuple[str]:




							"""simple docstring"""


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

							with open(_UpperCAmelCase ,   """w""" ,   encoding="""utf-8"""						) as f:
									f.write(json.dumps(self.vocab ,   indent=2 ,   sort_keys=_UpperCAmelCase ,   ensure_ascii=_UpperCAmelCase						) + """\n"""						)

							return (vocab_file,)





from math import log

from scipy.constants import Boltzmann, physical_constants

A			:						Any        =  3_0_0  # TEMPERATURE (unit = K)






def 					UpperCamelCase   (      __magic_name__	:				float       ,       __magic_name__	:				float       ,       __magic_name__	:				float       ,       )  ->    float:
		"""simple docstring"""




		if donor_conc <= 0:
				raise ValueError("""Donor concentration should be positive"""	)
		elif acceptor_conc <= 0:
				raise ValueError("""Acceptor concentration should be positive"""	)
		elif intrinsic_conc <= 0:
				raise ValueError("""Intrinsic concentration should be positive"""	)
		elif donor_conc <= intrinsic_conc:
				raise ValueError(
				    """Donor concentration should be greater than intrinsic concentration"""	)
		elif acceptor_conc <= intrinsic_conc:
				raise ValueError(
				    """Acceptor concentration should be greater than intrinsic concentration"""	)
		else:
				return (
				    Boltzmann
				    * T
				    * log((donor_conc * acceptor_conc) / intrinsic_conc**2	)
				    / physical_constants["electron volt"][0]
				)


if __name__ == "__main__":
	import doctest

	doctest.testmod()

