'''simple docstring'''





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


SCREAMING_SNAKE_CASE_:					str  =logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_:					Optional[Any]  ={
    'abeja/gpt-neox-japanese-2.7b': 'https://huggingface.co/abeja/gpt-neox-japanese-2.7b/resolve/main/config.json',
}




class 	__A				(			UpperCamelCase__     ):
    a__	:						Dict	       =  """gpt_neox_japanese"""



    def __init__(self   :   Tuple       ,      __a   :   Optional[int]=32000       ,      __a   :   List[str]=2560       ,      __a   :   Optional[int]=32       ,      __a   :   Optional[Any]=32       ,      __a   :   str=4       ,      __a   :   str="gelu"       ,      __a   :   str=1.00       ,      __a   :   Optional[int]=10000       ,      __a   :   Optional[Any]=2048       ,      __a   :   Optional[Any]=0.02       ,      __a   :   Optional[int]=1E-5       ,      __a   :   Optional[int]=True       ,      __a   :   Dict=31996       ,      __a   :   Optional[int]=31999       ,      __a   :   Union[str, Any]=0.1       ,      __a   :   Any=0.0       ,      **__a   :   Any       ,      ):
         super().__init__(bos_token_id=__a       ,      eos_token_id=__a       ,      **__a			)
         UpperCAmelCase_	   =       vocab_size
         UpperCAmelCase_	   =       max_position_embeddings
         UpperCAmelCase_	   =       hidden_size
         UpperCAmelCase_	   =       num_hidden_layers
         UpperCAmelCase_	   =       num_attention_heads
         UpperCAmelCase_	   =       intermediate_multiple_size
         UpperCAmelCase_	   =       hidden_act
         UpperCAmelCase_	   =       rotary_pct
         UpperCAmelCase_	   =       rotary_emb_base
         UpperCAmelCase_	   =       initializer_range
         UpperCAmelCase_	   =       layer_norm_eps
         UpperCAmelCase_	   =       use_cache
         UpperCAmelCase_	   =       attention_dropout
         UpperCAmelCase_	   =       hidden_dropout





'''simple docstring'''





from unittest import TestCase

from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters





def      lowerCAmelCase_    ( )   ->				str:


     '''simple docstring'''




     UpperCAmelCase_	   =       {
         "repo_name": ["test_repo1", "test_repo2", "test_repo3"],
         "path": ["test_1.py", "test_2.py", "unit_test.py"],
         "content": ["a " * 20, "a " * 30, "b " * 7],
     }
     UpperCAmelCase_	   =       Dataset.from_dict(snake_case_      )
     return dataset






class 	__A				(			UpperCamelCase__     ):



    def  _lowercase						(self   :   str			):
         UpperCAmelCase_	   =       get_dataset()
         UpperCAmelCase_	   =       make_duplicate_clusters(__a       ,      0.85			)
         self.assertEqual(len(duplicate_clusters[0]			)       ,      2			)






    def  _lowercase						(self   :   Optional[Any]			):
         UpperCAmelCase_	   =       get_dataset()
         UpperCAmelCase_   ,			UpperCAmelCase_	   =       deduplicate_dataset(__a			)
         self.assertEqual(len(__a			)       ,      2			)
         print(__a			)
         self.assertEqual(duplicate_clusters[0][0]["copies"]       ,      2			)
         self.assertEqual(duplicate_clusters[0][0]["is_extreme"]       ,      __a			)




