import os
import unittest

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

from ...test_tokenization_common import TokenizerTesterMixin






class   __lowercase       (     lowercase_							,  unittest.TestCase     ):
						lowercase       			=  PhobertTokenizer
						lowercase       			=  False

						def 							__a		(						self					:   Tuple )				->		Any:


									'''simple docstring'''

									super().setUp()

									# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
									lowercase       		=		['''T@@''', '''i''', '''I''', '''R@@''', '''r''', '''e@@''']
									lowercase       		=		dict(zip(UpperCamelCase_				,				range(len(UpperCamelCase_ ) ) ) )
									lowercase       		=		['''#version: 0.2''', '''l à</w>''']
									lowercase       		=		{'''unk_token''': '''<unk>'''}

									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'''				,				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					:   int				,				**__lowerCamelCase					:   str )				->		int:


									'''simple docstring'''

									kwargs.update(self.special_tokens_map )
									return PhobertTokenizer.from_pretrained(self.tmpdirname				,				**UpperCamelCase_ )

						def 							__a		(						self					:   List[Any]				,				__lowerCamelCase					:   List[str] )				->		List[str]:


									'''simple docstring'''

									lowercase       		=		'''Tôi là VinAI Research'''
									lowercase       		=		'''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					:   Tuple )				->		List[str]:


									'''simple docstring'''

									lowercase       		=		PhobertTokenizer(self.vocab_file				,				self.merges_file				,				**self.special_tokens_map )
									lowercase       		=		'''Tôi là VinAI Research'''
									lowercase       		=		'''T@@ ô@@ i l@@ à V@@ i@@ n@@ A@@ I R@@ e@@ s@@ e@@ a@@ r@@ c@@ h'''.split()
									lowercase       		=		tokenizer.tokenize(UpperCamelCase_ )
									print(UpperCamelCase_ )
									self.assertListEqual(UpperCamelCase_				,				UpperCamelCase_ )

									lowercase       		=		tokens + [tokenizer.unk_token]

									lowercase       		=		[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(UpperCamelCase_ )				,				UpperCamelCase_ )













import warnings

from ...utils import logging
from .image_processing_deit import DeiTImageProcessor


__a   :							Any						= logging.get_logger(__name__)


class    __lowercase   (						lowercase_	):







     '''simple docstring'''




     def __init__(					self							:      Union[str, Any]			,						*UpperCamelCase_							:      Tuple			,						**UpperCamelCase_							:      Tuple					):


         """simple docstring"""



         warnings.warn(
             """The class DeiTFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"""
             """ use DeiTImageProcessor instead."""			,						UpperCamelCase_			,						)
         super().__init__(*UpperCamelCase_			,						**UpperCamelCase_					)




