




'''simple docstring'''






from functools import lru_cache

@lru_cache
def      __lowerCAmelCase   (       snake_case__		):
			if not isinstance(snake_case__   , snake_case__		):
						raise TypeError("k must be an integer."		)
			if k < 0:
						raise ValueError("k integer must be greater or equal to zero."		)
			if k == 0:
						return 0
			elif k == 1:
						return 1
			else:
						return fibonacci(k - 1		) + fibonacci(k - 2		)

def      __lowerCAmelCase   (       snake_case__   , snake_case__		):
			__UpperCamelCase :     int										=  len(snake_case__		)
			# Find m such that F_m >= n where F_i is the i_th fibonacci number.
			__UpperCamelCase :     Optional[int]										=  0
			while True:
						if fibonacci(snake_case__		) >= len_list:
									__UpperCamelCase :     int										=  i
									break
						i += 1
			__UpperCamelCase :     List[Any]										=  0
			while fibb_k > 0:
						__UpperCamelCase :     List[Any]										=  min(
						    offset + fibonacci(fibb_k - 1		)   , len_list - 1		)  # Prevent out of range
						__UpperCamelCase :     List[Any]										=  arr[index_k]
						if item_k_1 == val:
									return index_k
						elif val < item_k_1:
									fibb_k -= 1
						elif val > item_k_1:
									offset += fibonacci(fibb_k - 1		)
									fibb_k -= 2
			else:
						return -1


if __name__ == "__main__":
				import doctest

				doctest.testmod()









'''simple docstring'''






import os
import unittest

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

from ...test_tokenization_common import TokenizerTesterMixin



class    A						(					SCREAMING_SNAKE_CASE__     ,				unittest.TestCase						):




				'''simple docstring'''





				A       =							BertweetTokenizer
				A       =							False
				def 			a_			(self     )      ->			Any:
							super().setUp()

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

							__UpperCamelCase :     Any										=  os.path.join(self.tmpdirname					,    VOCAB_FILES_NAMES["vocab_file"]     )
							__UpperCamelCase :     Tuple										=  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(_UpperCAmelCase     )     )
				def 			a_			(self					,    **_UpperCAmelCase     )      ->			str:
							kwargs.update(self.special_tokens_map     )
							return BertweetTokenizer.from_pretrained(self.tmpdirname					,    **_UpperCAmelCase     )
				def 			a_			(self					,    _UpperCAmelCase     )      ->			Dict:
							__UpperCamelCase :     Dict										=  "I am VinAI Research"
							__UpperCamelCase :     Any										=  "I <unk> m V<unk> <unk> <unk> I Re<unk> e<unk> <unk> <unk> <unk>"
							return input_text, output_text





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

							__UpperCamelCase :     Optional[Any]										=  tokens + [tokenizer.unk_token]

							__UpperCamelCase :     Any										=  [4, 3, 5, 6, 3, 3, 3, 4, 7, 9, 3, 9, 3, 3, 3, 3, 3]
							self.assertListEqual(tokenizer.convert_tokens_to_ids(_UpperCAmelCase     )					,    _UpperCAmelCase     )



