






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  SCREAMING_SNAKE_CASE			(			lowerCAmelCase      ,		unittest.TestCase					):
     '''simple docstring'''


     UpperCamelCase_							:		Optional[Any]			=	RoFormerTokenizer
     UpperCamelCase_							:		Dict			=	RoFormerTokenizerFast
     UpperCamelCase_							:		int			=	True
     UpperCamelCase_							:		str			=	True


     def 				_A       (				self       :	Tuple      ):
       super().setUp()


     def 				_A       (				self       :	Any					, **UpperCAmelCase_       :	Optional[int]      ):
       return self.tokenizer_class.from_pretrained("junnyu/roformer_chinese_base"					, **UpperCAmelCase_      )


     def 				_A       (				self       :	int					, **UpperCAmelCase_       :	str      ):
       return self.rust_tokenizer_class.from_pretrained("junnyu/roformer_chinese_base"					, **UpperCAmelCase_      )


     def 				_A       (				self       :	Dict      ):
       SCREAMING_SNAKE_CASE       :      Any							=    "永和服装饰品有限公司,今天天气非常好"
       SCREAMING_SNAKE_CASE       :      Any							=    "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       :	Tuple      ):
       SCREAMING_SNAKE_CASE       :      Union[str, Any]							=    self.get_tokenizer()
       SCREAMING_SNAKE_CASE						,  SCREAMING_SNAKE_CASE       :      Optional[int]							=    self.get_chinese_input_output_texts()
       SCREAMING_SNAKE_CASE       :      int							=    tokenizer.tokenize(UpperCAmelCase_      )

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

       SCREAMING_SNAKE_CASE       :      Optional[Any]							=    tokens + [tokenizer.unk_token]
       SCREAMING_SNAKE_CASE       :      str							=    [2_2943, 2_1332, 3_4431, 4_5904, 117, 306, 1231, 1231, 2653, 3_3994, 1266, 100]
       self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCAmelCase_      )					, UpperCAmelCase_      )


     def 				_A       (				self       :	Optional[Any]      ):
       SCREAMING_SNAKE_CASE       :      List[Any]							=    self.get_rust_tokenizer()
       SCREAMING_SNAKE_CASE						,  SCREAMING_SNAKE_CASE       :      str							=    self.get_chinese_input_output_texts()
       SCREAMING_SNAKE_CASE       :      Tuple							=    tokenizer.tokenize(UpperCAmelCase_      )
       self.assertListEqual(UpperCAmelCase_					, output_text.split()      )
       SCREAMING_SNAKE_CASE       :      str							=    tokens + [tokenizer.unk_token]
       SCREAMING_SNAKE_CASE       :      int							=    [2_2943, 2_1332, 3_4431, 4_5904, 117, 306, 1231, 1231, 2653, 3_3994, 1266, 100]
       self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCAmelCase_      )					, UpperCAmelCase_      )


     def 				_A       (				self       :	List[str]      ):
       pass


     def 				_A       (				self       :	Any      ):
       pass






     def 				_A       (				self       :	int      ):
       pass














from ...configuration_utils import PretrainedConfig
from ...utils import logging


snake_case    				=		logging.get_logger(__name__)

snake_case    				=		{
    """microsoft/markuplm-base""": """https://huggingface.co/microsoft/markuplm-base/resolve/main/config.json""",
    """microsoft/markuplm-large""": """https://huggingface.co/microsoft/markuplm-large/resolve/main/config.json""",
}


class  SCREAMING_SNAKE_CASE			(			lowerCAmelCase					):
     '''simple docstring'''


     UpperCamelCase_							:		Optional[int]			=	'''markuplm'''


     def __init__(				self       :	int					, UpperCAmelCase_       :	List[str]=3_0522					, UpperCAmelCase_       :	Optional[Any]=768					, UpperCAmelCase_       :	Any=12					, UpperCAmelCase_       :	Tuple=12					, UpperCAmelCase_       :	Union[str, Any]=3072					, UpperCAmelCase_       :	Dict="gelu"					, UpperCAmelCase_       :	Optional[int]=0.1					, UpperCAmelCase_       :	Tuple=0.1					, UpperCAmelCase_       :	Dict=512					, UpperCAmelCase_       :	Optional[int]=2					, UpperCAmelCase_       :	Any=0.02					, UpperCAmelCase_       :	Dict=1E-12					, UpperCAmelCase_       :	int=0					, UpperCAmelCase_       :	Optional[Any]=0					, UpperCAmelCase_       :	Optional[int]=2					, UpperCAmelCase_       :	str=256					, UpperCAmelCase_       :	str=1024					, UpperCAmelCase_       :	List[str]=216					, UpperCAmelCase_       :	List[Any]=1001					, UpperCAmelCase_       :	Union[str, Any]=32					, UpperCAmelCase_       :	Dict=50					, UpperCAmelCase_       :	Optional[int]="absolute"					, UpperCAmelCase_       :	Optional[int]=True					, UpperCAmelCase_       :	Any=None					, **UpperCAmelCase_       :	Any					, ):
       super().__init__(
           pad_token_id=UpperCAmelCase_					, bos_token_id=UpperCAmelCase_					, eos_token_id=UpperCAmelCase_					, **UpperCAmelCase_					, )
       SCREAMING_SNAKE_CASE       :      Any							=    vocab_size
       SCREAMING_SNAKE_CASE       :      List[Any]							=    hidden_size
       SCREAMING_SNAKE_CASE       :      List[Any]							=    num_hidden_layers
       SCREAMING_SNAKE_CASE       :      Tuple							=    num_attention_heads
       SCREAMING_SNAKE_CASE       :      List[str]							=    hidden_act
       SCREAMING_SNAKE_CASE       :      Tuple							=    intermediate_size
       SCREAMING_SNAKE_CASE       :      Any							=    hidden_dropout_prob
       SCREAMING_SNAKE_CASE       :      Union[str, Any]							=    attention_probs_dropout_prob
       SCREAMING_SNAKE_CASE       :      int							=    max_position_embeddings
       SCREAMING_SNAKE_CASE       :      Tuple							=    type_vocab_size
       SCREAMING_SNAKE_CASE       :      Any							=    initializer_range
       SCREAMING_SNAKE_CASE       :      Union[str, Any]							=    layer_norm_eps
       SCREAMING_SNAKE_CASE       :      int							=    position_embedding_type
       SCREAMING_SNAKE_CASE       :      List[str]							=    use_cache
       SCREAMING_SNAKE_CASE       :      Union[str, Any]							=    classifier_dropout
       # additional properties
       SCREAMING_SNAKE_CASE       :      Any							=    max_depth
       SCREAMING_SNAKE_CASE       :      int							=    max_xpath_tag_unit_embeddings
       SCREAMING_SNAKE_CASE       :      List[str]							=    max_xpath_subs_unit_embeddings
       SCREAMING_SNAKE_CASE       :      Optional[int]							=    tag_pad_id
       SCREAMING_SNAKE_CASE       :      Optional[Any]							=    subs_pad_id
       SCREAMING_SNAKE_CASE       :      List[Any]							=    xpath_unit_hidden_size






