


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   lowerCAmelCase__(    snake_case__    ,    unittest.TestCase						):






    '''simple docstring'''





    A_  :     Optional[Any]			= RoFormerTokenizer
    A_  :     int			= RoFormerTokenizerFast
    A_  :     Dict			= True
    A_  :     Optional[Any]			= True





    def 					_lowerCamelCase (	self				:   Union[str, Any]	):





       '''simple docstring'''
       super().setUp()





    def 					_lowerCamelCase (	self				:   int       ,   **__snake_case				:   Any	):





       '''simple docstring'''
       return self.tokenizer_class.from_pretrained('''junnyu/roformer_chinese_base'''       ,   **__snake_case	)





    def 					_lowerCamelCase (	self				:   List[str]       ,   **__snake_case				:   str	):





       '''simple docstring'''
       return self.rust_tokenizer_class.from_pretrained('''junnyu/roformer_chinese_base'''       ,   **__snake_case	)





    def 					_lowerCamelCase (	self				:   Any	):





       '''simple docstring'''
       UpperCAmelCase_							:      List[str]						=   '''永和服装饰品有限公司,今天天气非常好'''
       UpperCAmelCase_							:      List[str]						=   '''永和 服装 饰品 有限公司 , 今 天 天 气 非常 好'''
       return input_text, output_text





    def 					_lowerCamelCase (	self				:   List[Any]	):





       '''simple docstring'''
       UpperCAmelCase_							:      List[str]						=   self.get_tokenizer()
       UpperCAmelCase_							:      List[Any]						=   self.get_chinese_input_output_texts()
       UpperCAmelCase_							:      int						=   tokenizer.tokenize(__snake_case	)

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

       UpperCAmelCase_							:      Any						=   tokens + [tokenizer.unk_token]
       UpperCAmelCase_							:      Union[str, Any]						=   [22_943, 21_332, 34_431, 45_904, 117, 306, 1_231, 1_231, 2_653, 33_994, 1_266, 100]
       self.assertListEqual(tokenizer.convert_tokens_to_ids(__snake_case	)       ,   __snake_case	)





    def 					_lowerCamelCase (	self				:   Optional[int]	):





       '''simple docstring'''
       UpperCAmelCase_							:      List[str]						=   self.get_rust_tokenizer()
       UpperCAmelCase_							:      Union[str, Any]						=   self.get_chinese_input_output_texts()
       UpperCAmelCase_							:      List[str]						=   tokenizer.tokenize(__snake_case	)
       self.assertListEqual(__snake_case       ,   output_text.split()	)
       UpperCAmelCase_							:      str						=   tokens + [tokenizer.unk_token]
       UpperCAmelCase_							:      List[str]						=   [22_943, 21_332, 34_431, 45_904, 117, 306, 1_231, 1_231, 2_653, 33_994, 1_266, 100]
       self.assertListEqual(tokenizer.convert_tokens_to_ids(__snake_case	)       ,   __snake_case	)





    def 					_lowerCamelCase (	self				:   List[str]	):





       '''simple docstring'''
       pass





    def 					_lowerCamelCase (	self				:   Optional[Any]	):





       '''simple docstring'''
       pass





    def 					_lowerCamelCase (	self				:   Dict	):





       '''simple docstring'''
       pass



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__UpperCamelCase				:  str      					=							{
    'configuration_x_clip': [
        'XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'XCLIPConfig',
        'XCLIPTextConfig',
        'XCLIPVisionConfig',
    ],
    'processing_x_clip': ['XCLIPProcessor'],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __UpperCamelCase				:  Any      					=							[
           'XCLIP_PRETRAINED_MODEL_ARCHIVE_LIST',
           'XCLIPModel',
           'XCLIPPreTrainedModel',
           'XCLIPTextModel',
           'XCLIPVisionModel',
       ]

if TYPE_CHECKING:
       from .configuration_x_clip import (
           XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
           XCLIPConfig,
           XCLIPTextConfig,
           XCLIPVisionConfig,
       )
       from .processing_x_clip import XCLIPProcessor

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_x_clip import (
                  XCLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
                  XCLIPModel,
                  XCLIPPreTrainedModel,
                  XCLIPTextModel,
                  XCLIPVisionModel,
              )

else:
       import sys

       __UpperCamelCase				:  List[str]      					=							_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)