


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 					__lowerCamelCase	(unittest.TestCase		):
       _lowercase    							=      EsmTokenizer







       def 						snake_case_					(	self:				List[str]			):






            '''simple docstring'''




            super().setUp()
            __UpperCamelCase				=	tempfile.mkdtemp()
            # fmt: off
            __UpperCamelCase				=	["<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
            __UpperCamelCase				=	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 						snake_case_					(	self:				Dict,**A_:				str			):






            '''simple docstring'''




            return [self.get_tokenizer(**A_			)]







       def 						snake_case_					(	self:				Dict,**A_:				List[str]			):






            '''simple docstring'''




            return self.tokenizer_class.from_pretrained(self.tmpdirname,**A_			)







       def 						snake_case_					(	self:				str			):






            '''simple docstring'''




            __UpperCamelCase				=	self.tokenizer_class(self.vocab_file			)

            __UpperCamelCase				=	tokenizer.tokenize('LAGVS'			)
            self.assertListEqual(A_,['L', 'A', 'G', 'V', 'S']			)
            self.assertListEqual(tokenizer.convert_tokens_to_ids(A_			),[4, 5, 6, 7, 8]			)







       def 						snake_case_					(	self:				Optional[Any]			):






            '''simple docstring'''




            __UpperCamelCase				=	self.tokenizer_class(self.vocab_file			)

            __UpperCamelCase				=	'LAGVS'
            self.assertListEqual(tokenizer.encode(A_			),[0, 4, 5, 6, 7, 8, 2]			)







       def 						snake_case_					(	self:				Any			):






            '''simple docstring'''




            __UpperCamelCase				=	self.tokenizer_class(self.vocab_file			)

            __UpperCamelCase				=	['LAGVS', 'WCB']
            __UpperCamelCase				=	tokenizer(A_,padding=A_			)['input_ids']

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







       def 						snake_case_					(	self:				List[str]			):






            '''simple docstring'''




            __UpperCamelCase				=	self.tokenizer_class(self.vocab_file			)

            __UpperCamelCase				=	['LAGVS', 'WCB']
            __UpperCamelCase				=	tokenizer(A_,padding=A_			)['input_ids']

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







       def 						snake_case_					(	self:				int			):






            '''simple docstring'''




            __UpperCamelCase				=	self.get_tokenizers(fast=A_			)
            for tokenizer in tokenizers:
                 with self.subTest(F'''{tokenizer.__class__.__name__}'''			):
                      __UpperCamelCase				=	'<unk>'
                      __UpperCamelCase				=	'<mask>'

                      __UpperCamelCase				=	tokenizer.tokenize(A_			)
                      __UpperCamelCase				=	tokenizer.tokenize(A_			)

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






# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


__snake_case     =		{
    '''configuration_convnextv2''': [
        '''CONVNEXTV2_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''ConvNextV2Config''',
    ]
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __snake_case     =		[
        '''CONVNEXTV2_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''ConvNextV2ForImageClassification''',
        '''ConvNextV2Model''',
        '''ConvNextV2PreTrainedModel''',
        '''ConvNextV2Backbone''',
    ]


if TYPE_CHECKING:
    from .configuration_convnextva import (
        CONVNEXTV2_PRETRAINED_CONFIG_ARCHIVE_MAP,
        ConvNextVaConfig,
    )

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_convnextva import (
            CONVNEXTV2_PRETRAINED_MODEL_ARCHIVE_LIST,
            ConvNextVaBackbone,
            ConvNextVaForImageClassification,
            ConvNextVaModel,
            ConvNextVaPreTrainedModel,
        )

else:
    import sys

    __snake_case     =		_LazyModule(__name__, globals()['''__file__'''], _import_structure)


