


'''simple docstring'''






import os
import unittest

from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow

from ...test_tokenization_common import TokenizerTesterMixin




@require_jieba
class 						a__							(				a__							,							unittest.TestCase    ):





							'''simple docstring'''






							lowercase__     :  List[Any]      		= CpmAntTokenizer
							lowercase__     :  Any      		= False







							def     __SCREAMING_SNAKE_CASE				(						self  )			->				List[Any]:
														super().setUp()

														lowerCAmelCase__			  =      [
														    '''<d>''',
														    '''</d>''',
														    '''<s>''',
														    '''</s>''',
														    '''</_>''',
														    '''<unk>''',
														    '''<pad>''',
														    '''</n>''',
														    '''我''',
														    '''是''',
														    '''C''',
														    '''P''',
														    '''M''',
														    '''A''',
														    '''n''',
														    '''t''',
														]
														lowerCAmelCase__			  =      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]  )  )







							@tooslow
							def     __SCREAMING_SNAKE_CASE				(						self  )			->				Dict:
														lowerCAmelCase__			  =      CpmAntTokenizer.from_pretrained('''openbmb/cpm-ant-10b'''  )
														lowerCAmelCase__			  =      '''今天天气真好！'''
														lowerCAmelCase__			  =      ['''今天''', '''天气''', '''真''', '''好''', '''！''']
														lowerCAmelCase__			  =      tokenizer.tokenize(lowerCamelCase_  )
														self.assertListEqual(lowerCamelCase_   ,       lowerCamelCase_  )
														lowerCAmelCase__			  =      '''今天天气真好！'''
														lowerCAmelCase__			  =      [tokenizer.bos_token] + tokens

														lowerCAmelCase__			  =      [6, 98_02, 1_49_62, 20_82, 8_31, 2_44]
														self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCamelCase_  )   ,       lowerCamelCase_  )

														lowerCAmelCase__			  =      tokenizer.decode(lowerCamelCase_  )
														self.assertEqual(lowerCamelCase_   ,       lowerCamelCase_  )



'''simple docstring'''






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__UpperCAmelCase       							=				{
    '''configuration_clipseg''': [
        '''CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''CLIPSegConfig''',
        '''CLIPSegTextConfig''',
        '''CLIPSegVisionConfig''',
    ],
    '''processing_clipseg''': ['''CLIPSegProcessor'''],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__UpperCAmelCase       							=				[
		    '''CLIPSEG_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''CLIPSegModel''',
		    '''CLIPSegPreTrainedModel''',
		    '''CLIPSegTextModel''',
		    '''CLIPSegVisionModel''',
		    '''CLIPSegForImageSegmentation''',
		]

if TYPE_CHECKING:
		from .configuration_clipseg import (
		    CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    CLIPSegConfig,
		    CLIPSegTextConfig,
		    CLIPSegVisionConfig,
		)
		from .processing_clipseg import CLIPSegProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_clipseg import (
				    CLIPSEG_PRETRAINED_MODEL_ARCHIVE_LIST,
				    CLIPSegForImageSegmentation,
				    CLIPSegModel,
				    CLIPSegPreTrainedModel,
				    CLIPSegTextModel,
				    CLIPSegVisionModel,
				)

else:
		import sys

		__UpperCAmelCase       							=				_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)