





def        _lowercase   (  _UpperCAmelCase			)  ->					List[str]:
				lowerCamelCase			=[0] * len(lowercase__			)

				for i in range(1     , len(lowercase__			)			):
								# use last results for better performance - dynamic programming
								lowerCamelCase			=prefix_result[i - 1]
								while j > 0 and input_string[i] != input_string[j]:
												lowerCamelCase			=prefix_result[j - 1]

								if input_string[i] == input_string[j]:
												j += 1
								lowerCamelCase			=j

				return prefix_result





def        _lowercase   (  _UpperCAmelCase			)  ->					int:
				return max(prefix_function(lowercase__			)			)


if __name__ == "__main__":
							import doctest

							doctest.testmod()












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  __A       (  a      ,   unittest.TestCase      ):
				__A								=			BioGptTokenizer
				__A								=			False


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

								# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
								lowerCamelCase			=[
								    """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>""",
								]
								lowerCamelCase			=dict(zip(UpperCAmelCase_				,	range(len(UpperCAmelCase_							)							)							)							)
								lowerCamelCase			=["""l o 123""", """lo w 1456""", """e r</w> 1789""", """"""]

								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"""							) as fp:
												fp.write(json.dumps(UpperCAmelCase_							)							)
								with open(self.merges_file				,	"""w"""							) as fp:
												fp.write("""\n""".join(UpperCAmelCase_							)							)


				def _snake_case    (						self				,	UpperCAmelCase_							):
								lowerCamelCase			="""lower newer"""
								lowerCamelCase			="""lower newer"""
								return input_text, output_text


				def _snake_case    (						self							):
								lowerCamelCase			=BioGptTokenizer(self.vocab_file				,	self.merges_file							)

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

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


				@slow
				def _snake_case    (						self							):
								lowerCamelCase			=BioGptTokenizer.from_pretrained("""microsoft/biogpt"""							)

								lowerCamelCase			=tokenizer.encode("""sequence builders"""				,	add_special_tokens=UpperCAmelCase_							)
								lowerCamelCase			=tokenizer.encode("""multi-sequence build"""				,	add_special_tokens=UpperCAmelCase_							)

								lowerCamelCase			=tokenizer.build_inputs_with_special_tokens(UpperCAmelCase_							)
								lowerCamelCase			=tokenizer.build_inputs_with_special_tokens(UpperCAmelCase_				,	UpperCAmelCase_							)

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





