






"""simple docstring"""





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		(   SCREAMING_SNAKE_CASE_     ,unittest.TestCase			):
					UpperCAmelCase__								=				RoFormerTokenizer
					UpperCAmelCase__								=				RoFormerTokenizerFast
					UpperCAmelCase__								=				True
					UpperCAmelCase__								=				True

					def   lowerCamelCase__   (			self  :      Optional[Any]					)			->							Optional[int]:
											super().setUp()

					def   lowerCamelCase__   (			self  :      Optional[Any]     ,		**__snake_case  :      Union[str, Any]					)			->							Tuple:
											return self.tokenizer_class.from_pretrained("""junnyu/roformer_chinese_base"""     ,		**__snake_case					)

					def   lowerCamelCase__   (			self  :      Dict     ,		**__snake_case  :      Optional[int]					)			->							List[Any]:
											return self.rust_tokenizer_class.from_pretrained("""junnyu/roformer_chinese_base"""     ,		**__snake_case					)

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

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

											__magic_name__:	List[str]							=       tokens + [tokenizer.unk_token]
											__magic_name__:	Tuple							=       [2_2_9_4_3, 2_1_3_3_2, 3_4_4_3_1, 4_5_9_0_4, 1_1_7, 3_0_6, 1_2_3_1, 1_2_3_1, 2_6_5_3, 3_3_9_9_4, 1_2_6_6, 1_0_0]
											self.assertListEqual(tokenizer.convert_tokens_to_ids(__snake_case					)     ,		__snake_case					)

					def   lowerCamelCase__   (			self  :      Any					)			->							Tuple:
											__magic_name__:	str							=       self.get_rust_tokenizer()
											__magic_name__,			__magic_name__:	Optional[Any]							=       self.get_chinese_input_output_texts()
											__magic_name__:	Any							=       tokenizer.tokenize(__snake_case					)
											self.assertListEqual(__snake_case     ,		output_text.split()					)
											__magic_name__:	List[Any]							=       tokens + [tokenizer.unk_token]
											__magic_name__:	List[str]							=       [2_2_9_4_3, 2_1_3_3_2, 3_4_4_3_1, 4_5_9_0_4, 1_1_7, 3_0_6, 1_2_3_1, 1_2_3_1, 2_6_5_3, 3_3_9_9_4, 1_2_6_6, 1_0_0]
											self.assertListEqual(tokenizer.convert_tokens_to_ids(__snake_case					)     ,		__snake_case					)

					def   lowerCamelCase__   (			self  :      Dict					)			->							List[str]:
											pass

					def   lowerCamelCase__   (			self  :      Tuple					)			->							Optional[int]:
											pass






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









'''simple docstring'''







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


lowercase      :   Optional[int]      =       logging.get_logger(__name__)

lowercase      :   Optional[Any]      =       {
    """google/pegasus-large""": """https://huggingface.co/google/pegasus-large/resolve/main/config.json""",
    # See all PEGASUS models at https://huggingface.co/models?filter=pegasus
}







class 					_a (a__	):





     '''simple docstring'''



     lowerCAmelCase_  :     Any          =					"""pegasus"""
     lowerCAmelCase_  :     Dict          =					["""past_key_values"""]
     lowerCAmelCase_  :     str          =					{"""num_attention_heads""": """encoder_attention_heads""", """hidden_size""": """d_model"""}







     def __init__(				self							,__a=50_265							,__a=1_024							,__a=12							,__a=4_096							,__a=16							,__a=12							,__a=4_096							,__a=16							,__a=0.0							,__a=0.0							,__a=True							,__a=True							,__a="gelu"							,__a=1_024							,__a=0.1							,__a=0.0							,__a=0.0							,__a=0.02							,__a=0							,__a=False							,__a=0							,__a=1							,__a=1							,**__a							,)      ->				int:
          snake_case			:      List[Any]        =			vocab_size
          snake_case			:      Optional[Any]        =			max_position_embeddings
          snake_case			:      List[Any]        =			d_model
          snake_case			:      str        =			encoder_ffn_dim
          snake_case			:      List[Any]        =			encoder_layers
          snake_case			:      Optional[Any]        =			encoder_attention_heads
          snake_case			:      Union[str, Any]        =			decoder_ffn_dim
          snake_case			:      Tuple        =			decoder_layers
          snake_case			:      Union[str, Any]        =			decoder_attention_heads
          snake_case			:      Union[str, Any]        =			dropout
          snake_case			:      int        =			attention_dropout
          snake_case			:      int        =			activation_dropout
          snake_case			:      Optional[Any]        =			activation_function
          snake_case			:      Tuple        =			init_std
          snake_case			:      Union[str, Any]        =			encoder_layerdrop
          snake_case			:      int        =			decoder_layerdrop
          snake_case			:      Dict        =			use_cache
          snake_case			:      Dict        =			encoder_layers
          snake_case			:      List[Any]        =			scale_embedding  # scale factor will be sqrt(d_model) if True
          super().__init__(
              pad_token_id=__a							,eos_token_id=__a							,is_encoder_decoder=__a							,decoder_start_token_id=__a							,forced_eos_token_id=__a							,**__a							,)







     @property
     def 			snake_case_      (				self							)      ->				int:
          return self.encoder_attention_heads







     @property
     def 			snake_case_      (				self							)      ->				int:
          return self.d_model



