






import json
import os
import unittest

from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin


class        __UpperCamelCase    (     _lowerCAmelCase   ,			unittest.TestCase   ):
	__snake_case	:int   =       BioGptTokenizer
	__snake_case	:List[Any]   =       False







	def  _a   (  self      :							List[str]			)		-> Tuple:
		"""simple docstring"""







		super().setUp()

		# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
		__lowercase             =  [
		    """l""",
		    """o""",
		    """w""",
		    """e""",
		    """r""",
		    """s""",
		    """t""",
		    """i""",
		    """d""",
		    """n""",
		    """w</w>""",
		    """r</w>""",
		    """t</w>""",
		    """lo""",
		    """low""",
		    """er</w>""",
		    """low</w>""",
		    """lowest</w>""",
		    """newer</w>""",
		    """wider</w>""",
		    """<unk>""",
		]
		__lowercase             =  dict(zip(_lowerCAmelCase       ,				range(len(_lowerCAmelCase			)			)			)			)
		__lowercase             =  ["""l o 123""", """lo w 1456""", """e r</w> 1789""", """"""]

		__lowercase             =  os.path.join(self.tmpdirname       ,				VOCAB_FILES_NAMES["""vocab_file"""]			)
		__lowercase             =  os.path.join(self.tmpdirname       ,				VOCAB_FILES_NAMES["""merges_file"""]			)
		with open(self.vocab_file       ,				"""w"""			) as fp:
			fp.write(json.dumps(_lowerCAmelCase			)			)
		with open(self.merges_file       ,				"""w"""			) as fp:
			fp.write("""\n""".join(_lowerCAmelCase			)			)







	def  _a   (  self      :							List[str]       ,				_lowerCAmelCase      :							Any			)		-> Dict:
		"""simple docstring"""







		__lowercase             =  """lower newer"""
		__lowercase             =  """lower newer"""
		return input_text, output_text







	def  _a   (  self      :							Tuple			)		-> List[Any]:
		"""simple docstring"""







		__lowercase             =  BioGptTokenizer(self.vocab_file       ,				self.merges_file			)

		__lowercase             =  """lower"""
		__lowercase             =  ["""low""", """er</w>"""]
		__lowercase             =  tokenizer.tokenize(_lowerCAmelCase			)
		self.assertListEqual(_lowerCAmelCase       ,				_lowerCAmelCase			)

		__lowercase             =  tokens + ["""<unk>"""]
		__lowercase             =  [14, 15, 20]
		self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowerCAmelCase			)       ,				_lowerCAmelCase			)







	@slow
	def  _a   (  self      :							Any			)		-> Dict:
		"""simple docstring"""







		__lowercase             =  BioGptTokenizer.from_pretrained("""microsoft/biogpt"""			)

		__lowercase             =  tokenizer.encode("""sequence builders"""       ,				add_special_tokens=_lowerCAmelCase			)
		__lowercase             =  tokenizer.encode("""multi-sequence build"""       ,				add_special_tokens=_lowerCAmelCase			)

		__lowercase             =  tokenizer.build_inputs_with_special_tokens(_lowerCAmelCase			)
		__lowercase             =  tokenizer.build_inputs_with_special_tokens(_lowerCAmelCase       ,				_lowerCAmelCase			)

		self.assertTrue(encoded_sentence == [2] + text			)
		self.assertTrue(encoded_pair == [2] + text + [2] + text_a			)














def 				snake_case  (     lowerCamelCase					):




	'''simple docstring'''







	if not isinstance(lowerCamelCase				,  lowerCamelCase					):
		raise ValueError("""check_bouncy() accepts only integer arguments"""					)
	__lowercase             =  str(lowerCamelCase					)
	__lowercase             =  """""".join(sorted(lowerCamelCase					)					)
	return sorted_str_n != str_n and sorted_str_n[::-1] != str_n





def 				snake_case  (     lowerCamelCase = 99					):




	'''simple docstring'''







	if not 0 < percent < 100:
		raise ValueError("""solution() only accepts values from 0 to 100"""					)
	__lowercase             =  0
	__lowercase             =  1

	while True:
		if check_bouncy(lowerCamelCase					):
			bouncy_num += 1
		if (bouncy_num / num) * 100 >= percent:
			return num
		num += 1


if __name__ == "__main__":
						from doctest import testmod

						testmod()
						print(F'''{solution(99)}''')

