


'''simple docstring'''
import os
import tempfile
import unittest
from typing import List

from transformers.models.esm.tokenization_esm import VOCAB_FILES_NAMES, EsmTokenizer
from transformers.testing_utils import require_tokenizers
from transformers.tokenization_utils import PreTrainedTokenizer
from transformers.tokenization_utils_base import PreTrainedTokenizerBase






@require_tokenizers
class 		UpperCamelCase_		(					unittest.TestCase   ):





						"""simple docstring"""




						UpperCAmelCase__	:       Tuple         =     EsmTokenizer
						def 					__A					( self				:					Union[str, Any]  )							->					Any:
										super().setUp()
										__magic_name__	  = tempfile.mkdtemp()
										# fmt: off
										__magic_name__	  = ["<cls>", "<pad>", "<eos>", "<unk>", "L", "A", "G", "V", "S", "E", "R", "T", "I", "D", "P", "K", "Q", "N", "F", "Y", "M", "H", "W", "C", "X", "B", "U", "Z", "O", ".", "-", "<null_1>", "<mask>"]  # noqa: E501
										# fmt: on
										__magic_name__	  = os.path.join(self.tmpdirname	,				VOCAB_FILES_NAMES["vocab_file"]  )
										with open(self.vocab_file	,				"w"	,				encoding="utf-8"  ) as vocab_writer:
														vocab_writer.write("".join([x + "\n" for x in vocab_tokens]  )  )
						def 					__A					( self				:					str	,				**_lowerCamelCase				:					Any  )							->					List[PreTrainedTokenizerBase]:
										return [self.get_tokenizer(**__lowerCamelCase  )]
						def 					__A					( self				:					Dict	,				**_lowerCamelCase				:					Optional[int]  )							->					PreTrainedTokenizer:
										return self.tokenizer_class.from_pretrained(self.tmpdirname	,				**__lowerCamelCase  )
						def 					__A					( self				:					List[Any]  )							->					Union[str, Any]:
										__magic_name__	  = self.tokenizer_class(self.vocab_file  )

										__magic_name__	  = tokenizer.tokenize("LAGVS"  )
										self.assertListEqual(__lowerCamelCase	,				["L", "A", "G", "V", "S"]  )
										self.assertListEqual(tokenizer.convert_tokens_to_ids(__lowerCamelCase  )	,				[4, 5, 6, 7, 8]  )
						def 					__A					( self				:					Any  )							->					Any:
										__magic_name__	  = self.tokenizer_class(self.vocab_file  )

										__magic_name__	  = "LAGVS"
										self.assertListEqual(tokenizer.encode(__lowerCamelCase  )	,				[0, 4, 5, 6, 7, 8, 2]  )
						def 					__A					( self				:					Union[str, Any]  )							->					Tuple:
										__magic_name__	  = self.tokenizer_class(self.vocab_file  )

										__magic_name__	  = ["LAGVS", "WCB"]
										__magic_name__	  = tokenizer(__lowerCamelCase	,				padding=__lowerCamelCase  )["input_ids"]

										self.assertListEqual(__lowerCamelCase	,				[[0, 4, 5, 6, 7, 8, 2], [0, 22, 23, 25, 2]]  )
						def 					__A					( self				:					List[Any]  )							->					Optional[Any]:
										__magic_name__	  = self.tokenizer_class(self.vocab_file  )

										__magic_name__	  = ["LAGVS", "WCB"]
										__magic_name__	  = tokenizer(__lowerCamelCase	,				padding=__lowerCamelCase  )["input_ids"]

										self.assertListEqual(__lowerCamelCase	,				[[0, 4, 5, 6, 7, 8, 2], [0, 22, 23, 25, 2, 1, 1]]  )

						def 					__A					( self				:					List[Any]  )							->					List[str]:
										__magic_name__	  = self.get_tokenizers(fast=__lowerCamelCase  )
										for tokenizer in tokenizers:
														with self.subTest(f'{tokenizer.__class__.__name__}'  ):
																		__magic_name__	  = "<unk>"
																		__magic_name__	  = "<mask>"

																		__magic_name__	  = tokenizer.tokenize(__lowerCamelCase  )
																		__magic_name__	  = tokenizer.tokenize(__lowerCamelCase  )

																		self.assertEqual(len(__lowerCamelCase  )	,				1  )
																		self.assertEqual(len(__lowerCamelCase  )	,				1  )
																		self.assertEqual(token_a[0]	,				__lowerCamelCase  )
																		self.assertEqual(token_a[0]	,				__lowerCamelCase  )







'''simple docstring'''
import warnings

from ...utils import logging
from .image_processing_convnext import ConvNextImageProcessor


__magic_name__   :   int  							=logging.get_logger(__name__)






class 		UpperCamelCase_		(					A   ):





						"""simple docstring"""




						def __init__( self				:					List[str]	,				*_lowerCamelCase				:					List[str]	,				**_lowerCamelCase				:					Optional[Any]  )							->					None:
										warnings.warn(
										    "The class ConvNextFeatureExtractor is deprecated and will be removed in version 5 of Transformers."
										    " Please use ConvNextImageProcessor instead."	,				_lowerCamelCase	,				)
										super().__init__(*_lowerCamelCase	,				**_lowerCamelCase  )



