

'''simple docstring'''
import os
import unittest

from transformers.models.bertweet.tokenization_bertweet import VOCAB_FILES_NAMES, BertweetTokenizer

from ...test_tokenization_common import TokenizerTesterMixin
class  _snake_case						(__SCREAMING_SNAKE_CASE       ,       unittest.TestCase):
			__A   :     Optional[Any]          =BertweetTokenizer
			__A   :     Optional[Any]          =False






			def 						UpperCamelCase__				(   self			):
				super().setUp()

				# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
				UpperCAmelCase_			:	List[Any]      =   ["I", "m", "V@@", "R@@", "r", "e@@"]
				UpperCAmelCase_			:	Any      =   dict(zip(_snake_case       ,range(len(_snake_case			)			)			)			)
				UpperCAmelCase_			:	Dict      =   ["#version: 0.2", "a m</w>"]
				UpperCAmelCase_			:	Optional[Any]      =   {"unk_token": "<unk>"}

				UpperCAmelCase_			:	Optional[Any]      =   os.path.join(self.tmpdirname       ,VOCAB_FILES_NAMES["vocab_file"]			)
				UpperCAmelCase_			:	Optional[Any]      =   os.path.join(self.tmpdirname       ,VOCAB_FILES_NAMES["merges_file"]			)
				with open(self.vocab_file       ,"w"       ,encoding="utf-8"			) as fp:
					for token in vocab_tokens:
						fp.write(f'''{token} {vocab_tokens[token]}\n'''			)
				with open(self.merges_file       ,"w"       ,encoding="utf-8"			) as fp:
					fp.write("\n".join(_snake_case			)			)






			def 						UpperCamelCase__				(   self       ,**_snake_case			):
				kwargs.update(self.special_tokens_map			)
				return BertweetTokenizer.from_pretrained(self.tmpdirname       ,**_snake_case			)






			def 						UpperCamelCase__				(   self       ,_snake_case			):
				UpperCAmelCase_			:	Any      =   "I am VinAI Research"
				UpperCAmelCase_			:	List[str]      =   "I <unk> m V<unk> <unk> <unk> I Re<unk> e<unk> <unk> <unk> <unk>"
				return input_text, output_text






			def 						UpperCamelCase__				(   self			):
				UpperCAmelCase_			:	Any      =   BertweetTokenizer(self.vocab_file       ,self.merges_file       ,**self.special_tokens_map			)
				UpperCAmelCase_			:	Optional[int]      =   "I am VinAI Research"
				UpperCAmelCase_			:	Union[str, Any]      =   "I a@@ m V@@ i@@ n@@ A@@ I R@@ e@@ s@@ e@@ a@@ r@@ c@@ h".split()
				UpperCAmelCase_			:	Optional[int]      =   tokenizer.tokenize(_snake_case			)
				self.assertListEqual(_snake_case       ,_snake_case			)

				UpperCAmelCase_			:	Union[str, Any]      =   tokens + [tokenizer.unk_token]

				UpperCAmelCase_			:	Optional[int]      =   [4, 3, 5, 6, 3, 3, 3, 4, 7, 9, 3, 9, 3, 3, 3, 3, 3]
				self.assertListEqual(tokenizer.convert_tokens_to_ids(_snake_case			)       ,_snake_case			)







'''simple docstring'''
from __future__ import annotations

import re


def       a__    (  _SCREAMING_SNAKE_CASE					:    list[str]							)			-> list[str]:


	"""simple docstring"""





	def alphanum_key(_SCREAMING_SNAKE_CASE					:    Optional[Any]							):
		return [int(_SCREAMING_SNAKE_CASE							) if s.isdigit() else s.lower() for s in re.split("([0-9]+)"     ,							_SCREAMING_SNAKE_CASE							)]

	return sorted(_SCREAMING_SNAKE_CASE     ,							key=_SCREAMING_SNAKE_CASE							)


if __name__ == "__main__":
					import doctest

					doctest.testmod()




