


import os
import unittest

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

from ...test_tokenization_common import TokenizerTesterMixin


class 	a__						(    lowerCAmelCase_    ,							unittest.TestCase     ):
       lowerCamelCase__:  List[Any]				     =  BertweetTokenizer
       lowerCamelCase__:  str				     =  False

       def     UpperCAmelCase( self   :  Tuple     ):
            super().setUp()

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

            a_     :  Optional[Any]				      =     os.path.join(self.tmpdirname   ,				VOCAB_FILES_NAMES["""vocab_file"""]     )
            a_     :  List[str]				      =     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     UpperCAmelCase( self   :  List[str]   ,				**lowerCamelCase_   :  List[str]     ):
            kwargs.update(self.special_tokens_map     )
            return BertweetTokenizer.from_pretrained(self.tmpdirname   ,				**lowerCamelCase_     )

       def     UpperCAmelCase( self   :  Any   ,				lowerCamelCase_   :  int     ):
            a_     :  Dict				      =     """I am VinAI Research"""
            a_     :  Tuple				      =     """I <unk> m V<unk> <unk> <unk> I Re<unk> e<unk> <unk> <unk> <unk>"""
            return input_text, output_text

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

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

            a_     :  Union[str, 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(lowerCamelCase_     )   ,				lowerCamelCase_     )








"""simple docstring"""







from typing import TYPE_CHECKING

from ...utils import _LazyModule


UpperCAmelCase:  Union[str, Any]			     =				{"""tokenization_phobert""": ["""PhobertTokenizer"""]}


if TYPE_CHECKING:
		from .tokenization_phobert import PhobertTokenizer

else:
		import sys

		UpperCAmelCase:  Optional[int]			     =				_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)



