"""simple docstring"""


import os
import unittest

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

from ...test_tokenization_common import TokenizerTesterMixin






class        __UpperCAmelCase						(     __lowerCAmelCase				,				unittest.TestCase     ):
				A__				:       Union[str, Any]  							=	BertweetTokenizer
				A__				:       Optional[Any]  							=	False

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

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

										lowerCamelCase__ =os.path.join(self.tmpdirname     ,			VOCAB_FILES_NAMES["vocab_file"]				)
										lowerCamelCase__ =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(_lowerCamelCase				)				)

				def 		_a     (				self     ,			**_lowerCamelCase				):
										kwargs.update(self.special_tokens_map				)
										return BertweetTokenizer.from_pretrained(self.tmpdirname     ,			**_lowerCamelCase				)

				def 		_a     (				self     ,			_lowerCamelCase				):
										lowerCamelCase__ ="I am VinAI Research"
										lowerCamelCase__ ="I <unk> m V<unk> <unk> <unk> I Re<unk> e<unk> <unk> <unk> <unk>"
										return input_text, output_text






				def 		_a     (				self				):
										lowerCamelCase__ =BertweetTokenizer(self.vocab_file     ,			self.merges_file     ,			**self.special_tokens_map				)
										lowerCamelCase__ ="I am VinAI Research"
										lowerCamelCase__ ="I a@@ m V@@ i@@ n@@ A@@ I R@@ e@@ s@@ e@@ a@@ r@@ c@@ h".split()
										lowerCamelCase__ =tokenizer.tokenize(_lowerCamelCase				)
										self.assertListEqual(_lowerCamelCase     ,			_lowerCamelCase				)

										lowerCamelCase__ =tokens + [tokenizer.unk_token]

										lowerCamelCase__ =[4, 3, 5, 6, 3, 3, 3, 4, 7, 9, 3, 9, 3, 3, 3, 3, 3]
										self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowerCamelCase				)     ,			_lowerCamelCase				)



"""simple docstring"""


from __future__ import annotations

from collections.abc import Generator





def       lowerCamelCase_			( __lowerCAmelCase    )							-> Generator[int, None, None]:




						'''simple docstring'''



						if not isinstance(__lowerCAmelCase       ,   __lowerCAmelCase    ) or n < 1:
												raise Exception("Sequence only defined for positive integers"    )

						yield n
						while n != 1:
												if n % 2 == 0:
																		n //= 2
												else:
																		lowerCamelCase__ =3 * n + 1
												yield n





def       lowerCamelCase_			( )							-> List[str]:




						'''simple docstring'''



						lowerCamelCase__ =43
						lowerCamelCase__ =tuple(collatz_sequence(__lowerCAmelCase    )    )
						print(__lowerCAmelCase    )
						print(F'''Collatz sequence from {n} took {len(__lowerCAmelCase    )} steps.'''    )


if __name__ == "__main__":
	main()


