
import os
import unittest

from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer

from ...test_tokenization_common import TokenizerTesterMixin





class 			_lowerCAmelCase      (			SCREAMING_SNAKE_CASE__      ,   unittest.TestCase ):
				_lowercase    	=PhobertTokenizer
				_lowercase    	=False




				def   __a		(      self  )       ->   Tuple:
					super().setUp()

					# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
					lowerCAmelCase_      			=			["T@@", "i", "I", "R@@", "r", "e@@"]
					lowerCAmelCase_      			=			dict(zip(snake_case__       ,       range(len(snake_case__  )  )  )  )
					lowerCAmelCase_      			=			["#version: 0.2", "l à</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(snake_case__  )  )




				def   __a		(      self       ,       **_UpperCamelCase  )       ->   Any:
					kwargs.update(self.special_tokens_map  )
					return PhobertTokenizer.from_pretrained(self.tmpdirname       ,       **snake_case__  )




				def   __a		(      self       ,       _UpperCamelCase  )       ->   Optional[int]:
					lowerCAmelCase_      			=			"Tôi là VinAI Research"
					lowerCAmelCase_      			=			"T<unk> i <unk> <unk> <unk> <unk> <unk> <unk> I Re<unk> e<unk> <unk> <unk> <unk>"
					return input_text, output_text




				def   __a		(      self  )       ->   List[str]:
					lowerCAmelCase_      			=			PhobertTokenizer(self.vocab_file       ,       self.merges_file       ,       **self.special_tokens_map  )
					lowerCAmelCase_      			=			"Tôi là VinAI Research"
					lowerCAmelCase_      			=			"T@@ ô@@ i l@@ à V@@ i@@ n@@ A@@ I R@@ e@@ s@@ e@@ a@@ r@@ c@@ h".split()
					lowerCAmelCase_      			=			tokenizer.tokenize(snake_case__  )
					print(snake_case__  )
					self.assertListEqual(snake_case__       ,       snake_case__  )

					lowerCAmelCase_      			=			tokens + [tokenizer.unk_token]

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





import functools






def      lowerCamelCase__       (       __lowerCAmelCase						:						str					,							__lowerCAmelCase						:						str       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			len(__lowerCAmelCase       )
			lowerCAmelCase_      			=			len(__lowerCAmelCase       )

			@functools.cache
			def min_distance(__lowerCAmelCase						:						int					,							__lowerCAmelCase						:						int       ) -> int:
						# if first word index is overflow - delete all from the second word
						if indexa >= len_worda:
									return len_worda - indexa
						# if second word index is overflow - delete all from the first word
						if indexa >= len_worda:
									return len_worda - indexa
						lowerCAmelCase_      			=			int(worda[indexa] != worda[indexa]       )  # current letters not identical
						return min(
						    1 + min_distance(indexa + 1					,							__lowerCAmelCase       )					,							1 + min_distance(__lowerCAmelCase					,							indexa + 1       )					,							diff + min_distance(indexa + 1					,							indexa + 1       )					,							)

			return min_distance(0					,							0       )


if __name__ == "__main__":
			import doctest

			doctest.testmod()



