




import unittest

from transformers import RoFormerTokenizer, RoFormerTokenizerFast
from transformers.testing_utils import require_rjieba, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin







@require_rjieba
@require_tokenizers
class   A(						UpperCamelCase							,				unittest.TestCase       ):



 '''simple docstring'''


 UpperCamelCase						       =						RoFormerTokenizer
 UpperCamelCase						       =						RoFormerTokenizerFast
 UpperCamelCase						       =						True
 UpperCamelCase						       =						True

 def     a__			(    self :  Any  )       ->     Tuple:

       """simple docstring"""






       super().setUp()

 def     a__			(    self :  Any						,							**A_ :  Dict  )       ->     List[str]:

       """simple docstring"""






       return self.tokenizer_class.from_pretrained('junnyu/roformer_chinese_base'						,							**A_  )

 def     a__			(    self :  Optional[Any]						,							**A_ :  Optional[Any]  )       ->     Optional[int]:

       """simple docstring"""






       return self.rust_tokenizer_class.from_pretrained('junnyu/roformer_chinese_base'						,							**A_  )

 def     a__			(    self :  str  )       ->     Optional[int]:

       """simple docstring"""






       lowerCamelCase_							=   '永和服装饰品有限公司,今天天气非常好'
       lowerCamelCase_							=   '永和 服装 饰品 有限公司 , 今 天 天 气 非常 好'
       return input_text, output_text

 def     a__			(    self :  Any  )       ->     Optional[int]:

       """simple docstring"""






       lowerCamelCase_							=   self.get_tokenizer()
       lowerCamelCase_					,    lowerCamelCase_							=   self.get_chinese_input_output_texts()
       lowerCamelCase_							=   tokenizer.tokenize(A_  )

       self.assertListEqual(A_						,							output_text.split()  )

       lowerCamelCase_							=   tokens + [tokenizer.unk_token]
       lowerCamelCase_							=   [22943, 21332, 34431, 45904, 117, 306, 1231, 1231, 2653, 33994, 1266, 100]
       self.assertListEqual(tokenizer.convert_tokens_to_ids(A_  )						,							A_  )

 def     a__			(    self :  Optional[Any]  )       ->     Dict:

       """simple docstring"""






       lowerCamelCase_							=   self.get_rust_tokenizer()
       lowerCamelCase_					,    lowerCamelCase_							=   self.get_chinese_input_output_texts()
       lowerCamelCase_							=   tokenizer.tokenize(A_  )
       self.assertListEqual(A_						,							output_text.split()  )
       lowerCamelCase_							=   tokens + [tokenizer.unk_token]
       lowerCamelCase_							=   [22943, 21332, 34431, 45904, 117, 306, 1231, 1231, 2653, 33994, 1266, 100]
       self.assertListEqual(tokenizer.convert_tokens_to_ids(A_  )						,							A_  )

 def     a__			(    self :  Union[str, Any]  )       ->     int:

       """simple docstring"""






       pass

 def     a__			(    self :  Any  )       ->     str:

       """simple docstring"""






       pass





 def     a__			(    self :  Any  )       ->     List[str]:

       """simple docstring"""






       pass









from ..utils import is_flax_available, is_torch_available


if is_torch_available():
 from .autoencoder_kl import AutoencoderKL
 from .controlnet import ControlNetModel
 from .dual_transformer_ad import DualTransformeraDModel
 from .modeling_utils import ModelMixin
 from .prior_transformer import PriorTransformer
 from .ta_film_transformer import TaFilmDecoder
 from .transformer_ad import TransformeraDModel
 from .unet_ad import UNetaDModel
 from .unet_ad import UNetaDModel
 from .unet_ad_condition import UNetaDConditionModel
 from .unet_ad_condition import UNetaDConditionModel
 from .vq_model import VQModel

if is_flax_available():
 from .controlnet_flax import FlaxControlNetModel
 from .unet_ad_condition_flax import FlaxUNetaDConditionModel
 from .vae_flax import FlaxAutoencoderKL



