


"""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      (  _UpperCamelCase):







		def __init__(					self      :       Optional[Any]    ,   a__      :       str = "▁"    ,   a__      :       bool = True    ,   a__      :       Union[str, AddedToken] = "<unk>"    ,   a__      :       Union[str, AddedToken] = "</s>"    ,   a__      :       Union[str, AddedToken] = "<pad>"    ,   )       ->						int:





						'''simple docstring'''







						_A					  =			{
						    "pad": {"id": 0, "token": pad_token},
						    "eos": {"id": 1, "token": eos_token},
						    "unk": {"id": 2, "token": unk_token},
						}

						_A					  =			[None] * len(self.special_tokens		)
						for token_dict in self.special_tokens.values():
										_A					  =			token_dict["token"]

						_A					  =			Tokenizer(Unigram()		)

						_A					  =			normalizers.Sequence(
						    [
						        normalizers.Nmt(),
						        normalizers.NFKC(),
						        normalizers.Replace(Regex(" {2,}"		)    ,   " "		),
						        normalizers.Lowercase(),
						    ]		)
						_A					  =			pre_tokenizers.Sequence(
						    [
						        pre_tokenizers.Metaspace(replacement=a__    ,   add_prefix_space=a__		),
						        pre_tokenizers.Digits(individual_digits=a__		),
						        pre_tokenizers.Punctuation(),
						    ]		)
						_A					  =			decoders.Metaspace(replacement=a__    ,   add_prefix_space=a__		)

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

						_A					  =			{
						    "model": "SentencePieceUnigram",
						    "replacement": replacement,
						    "add_prefix_space": add_prefix_space,
						}

						super().__init__(a__    ,   a__		)







		def  a_ (					self      :       Optional[Any]    ,   a__      :       Union[str, List[str]]    ,   a__      :       int = 80_00    ,   a__      :       bool = True    ,   )       ->						List[Any]:





						'''simple docstring'''







						_A					  =			trainers.UnigramTrainer(
						    vocab_size=a__    ,   special_tokens=self.special_tokens_list    ,   show_progress=a__    ,   )

						if isinstance(a__    ,   a__		):
										_A					  =			[files]
						self._tokenizer.train(a__    ,   trainer=a__		)

						self.add_unk_id()







		def  a_ (					self      :       str    ,   a__      :       Union[Iterator[str], Iterator[Iterator[str]]]    ,   a__      :       int = 80_00    ,   a__      :       bool = True    ,   )       ->						Union[str, Any]:





						'''simple docstring'''







						_A					  =			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  a_ (					self      :       Any		)       ->						Optional[int]:





						'''simple docstring'''







						_A					  =			json.loads(self._tokenizer.to_str()		)

						_A					  =			self.special_tokens["unk"]["id"]

						_A					  =			Tokenizer.from_str(json.dumps(a__		)		)








"""simple docstring"""


import unittest

from transformers import load_tool

from .test_tools_common import ToolTesterMixin
class snake_case      (  unittest.TestCase     ,				_UpperCamelCase):







		def  a_ (					self      :       Optional[Any]		)       ->						List[str]:





						'''simple docstring'''







						_A					  =			load_tool("text-classification"		)
						self.tool.setup()
						_A					  =			load_tool("text-classification"    ,   remote=a__		)







		def  a_ (					self      :       Optional[int]		)       ->						Dict:





						'''simple docstring'''







						_A					  =			self.tool("That's quite cool"    ,   ["positive", "negative"]		)
						self.assertEqual(a__    ,   "positive"		)







		def  a_ (					self      :       Optional[Any]		)       ->						Dict:





						'''simple docstring'''







						_A					  =			self.remote_tool("That's quite cool"    ,   ["positive", "negative"]		)
						self.assertEqual(a__    ,   "positive"		)







		def  a_ (					self      :       Dict		)       ->						Optional[int]:





						'''simple docstring'''







						_A					  =			self.tool(text="That's quite cool"    ,   labels=["positive", "negative"]		)
						self.assertEqual(a__    ,   "positive"		)







		def  a_ (					self      :       Dict		)       ->						Any:





						'''simple docstring'''







						_A					  =			self.remote_tool(text="That's quite cool"    ,   labels=["positive", "negative"]		)
						self.assertEqual(a__    ,   "positive"		)