


import os
import unittest

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

from ...test_tokenization_common import TokenizerTesterMixin



class 							A					( UpperCAmelCase__				,						unittest.TestCase							):
					'''simple docstring'''






					A__    =				BertweetTokenizer
					A__    =				False

					def 						lowerCamelCase__  (self					:		List[Any]	)		->     Union[str, Any]:




							"""simple docstring"""


							super().setUp()

							# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
							lowercase__      =	["""I""", """m""", """V@@""", """R@@""", """r""", """e@@"""]
							lowercase__      =	dict(zip(_UpperCAmelCase   ,      range(len(_UpperCAmelCase	)	)	)	)
							lowercase__      =	["""#version: 0.2""", """a m</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 						lowerCamelCase__  (self					:		str   ,      **_UpperCAmelCase					:		List[Any]	)		->     Optional[int]:




							"""simple docstring"""


							kwargs.update(self.special_tokens_map	)
							return BertweetTokenizer.from_pretrained(self.tmpdirname   ,      **_UpperCAmelCase	)

					def 						lowerCamelCase__  (self					:		Dict   ,      _UpperCAmelCase					:		Dict	)		->     Optional[int]:




							"""simple docstring"""


							lowercase__      =	"""I am VinAI Research"""
							lowercase__      =	"""I <unk> m V<unk> <unk> <unk> I Re<unk> e<unk> <unk> <unk> <unk>"""
							return input_text, output_text


					def 						lowerCamelCase__  (self					:		Tuple	)		->     Optional[Any]:




							"""simple docstring"""


							lowercase__      =	BertweetTokenizer(self.vocab_file   ,      self.merges_file   ,      **self.special_tokens_map	)
							lowercase__      =	"""I am VinAI Research"""
							lowercase__      =	"""I a@@ m V@@ i@@ n@@ A@@ I R@@ e@@ s@@ e@@ a@@ r@@ c@@ h""".split()
							lowercase__      =	tokenizer.tokenize(_UpperCAmelCase	)
							self.assertListEqual(_UpperCAmelCase   ,      _UpperCAmelCase	)

							lowercase__      =	tokens + [tokenizer.unk_token]

							lowercase__      =	[4, 3, 5, 6, 3, 3, 3, 4, 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_mobilenet_va import MobileNetVaImageProcessor


A :	Optional[Any]												=     logging.get_logger(__name__)



class 							A					( UpperCAmelCase__							):
					'''simple docstring'''






					def __init__(self					:		Optional[int]   ,      *_UpperCAmelCase					:		Union[str, Any]   ,      **_UpperCAmelCase					:		Any	)		->     None:




							"""simple docstring"""


							warnings.warn(
							    """The class MobileNetV1FeatureExtractor is deprecated and will be removed in version 5 of Transformers."""
							    """ Please use MobileNetV1ImageProcessor instead."""   ,      _UpperCAmelCase   ,      )
							super().__init__(*_UpperCAmelCase   ,      **_UpperCAmelCase	)

