
'''simple docstring'''






import json
from typing import Iterator, List, Union

from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.processors import TemplateProcessing




class     __snake_case		(   a__):
					def __init__(     self,    A = "▁",    A = True,    A = "<unk>",    A = "</s>",    A = "<pad>",    ):

									"""simple docstring"""


									lowerCamelCase					:			List[Any]									= {
									    'pad': {'id': 0, 'token': pad_token},
									    'eos': {'id': 1, 'token': eos_token},
									    'unk': {'id': 2, 'token': unk_token},
									}

									lowerCamelCase					:			Dict									= [None] * len(self.special_tokens      )
									for token_dict in self.special_tokens.values():
													lowerCamelCase					:			str									= token_dict['token']

									lowerCamelCase					:			List[str]									= Tokenizer(Unigram()      )

									lowerCamelCase					:			Dict									= normalizers.Sequence(
									    [
									        normalizers.Nmt(),
									        normalizers.NFKC(),
									        normalizers.Replace(Regex(' {2,}'      ),    ' '      ),
									        normalizers.Lowercase(),
									    ]      )
									lowerCamelCase					:			Optional[int]									= pre_tokenizers.Sequence(
									    [
									        pre_tokenizers.Metaspace(replacement=A,    add_prefix_space=A      ),
									        pre_tokenizers.Digits(individual_digits=A      ),
									        pre_tokenizers.Punctuation(),
									    ]      )
									lowerCamelCase					:			List[Any]									= decoders.Metaspace(replacement=A,    add_prefix_space=A      )

									lowerCamelCase					:			str									= TemplateProcessing(
									    single=F'''$A {self.special_tokens['eos']['token']}''',    special_tokens=[(self.special_tokens['eos']['token'], self.special_tokens['eos']['id'])],    )

									lowerCamelCase					:			Union[str, Any]									= {
									    'model': 'SentencePieceUnigram',
									    'replacement': replacement,
									    'add_prefix_space': add_prefix_space,
									}

									super().__init__(A,    A      )
					def     UpperCAmelCase_							(     self,    A,    A = 8000,    A = True,    ):

									"""simple docstring"""


									lowerCamelCase					:			Any									= trainers.UnigramTrainer(
									    vocab_size=A,    special_tokens=self.special_tokens_list,    show_progress=A,    )

									if isinstance(A,    A      ):
													lowerCamelCase					:			Union[str, Any]									= [files]
									self._tokenizer.train(A,    trainer=A      )

									self.add_unk_id()
					def     UpperCAmelCase_							(     self,    A,    A = 8000,    A = True,    ):

									"""simple docstring"""


									lowerCamelCase					:			str									= trainers.UnigramTrainer(
									    vocab_size=A,    special_tokens=self.special_tokens_list,    show_progress=A,    )

									self._tokenizer.train_from_iterator(A,    trainer=A      )

									self.add_unk_id()




					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									lowerCamelCase					:			Optional[Any]									= json.loads(self._tokenizer.to_str()      )

									lowerCamelCase					:			List[str]									= self.special_tokens['unk']['id']

									lowerCamelCase					:			Any									= Tokenizer.from_str(json.dumps(A      )      )


'''simple docstring'''






import numpy as np





def    UpperCAmelCase							(  UpperCAmelCase__							:							np.array):
				return 1 / (1 + np.exp(-vector))


if __name__ == "__main__":
					import doctest

					doctest.testmod()
