






'''simple docstring'''




import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
		from .tokenization_big_bird import BigBirdTokenizer
else:
		__lowerCamelCase   :					Any   							=					None

__lowerCamelCase   :					Optional[Any]   							=					logging.get_logger(__name__)
__lowerCamelCase   :					Tuple   							=					{'''vocab_file''': '''spiece.model''', '''tokenizer_file''': '''tokenizer.json'''}

__lowerCamelCase   :					Optional[Any]   							=					{
    '''vocab_file''': {
        '''google/bigbird-roberta-base''': '''https://huggingface.co/google/bigbird-roberta-base/resolve/main/spiece.model''',
        '''google/bigbird-roberta-large''': (
            '''https://huggingface.co/google/bigbird-roberta-large/resolve/main/spiece.model'''
        ),
        '''google/bigbird-base-trivia-itc''': (
            '''https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/spiece.model'''
        ),
    },
    '''tokenizer_file''': {
        '''google/bigbird-roberta-base''': (
            '''https://huggingface.co/google/bigbird-roberta-base/resolve/main/tokenizer.json'''
        ),
        '''google/bigbird-roberta-large''': (
            '''https://huggingface.co/google/bigbird-roberta-large/resolve/main/tokenizer.json'''
        ),
        '''google/bigbird-base-trivia-itc''': (
            '''https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/tokenizer.json'''
        ),
    },
}

__lowerCamelCase   :					Any   							=					{
    '''google/bigbird-roberta-base''': 4096,
    '''google/bigbird-roberta-large''': 4096,
    '''google/bigbird-base-trivia-itc''': 4096,
}


__lowerCamelCase   :					Optional[Any]   							=					'''▁'''







class    A_	(a_							):
							"""simple docstring"""




							a__   		=	VOCAB_FILES_NAMES
							a__   		=	PRETRAINED_VOCAB_FILES_MAP
							a__   		=	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							a__   		=	BigBirdTokenizer
							a__   		=	['''input_ids''', '''attention_mask''']
							a__   		=	[]

							def __init__(		self			:int       ,							lowerCAmelCase__			:Dict=None       ,							lowerCAmelCase__			:int=None       ,							lowerCAmelCase__			:List[Any]="<unk>"       ,							lowerCAmelCase__			:Any="<s>"       ,							lowerCAmelCase__			:Union[str, Any]="</s>"       ,							lowerCAmelCase__			:int="<pad>"       ,							lowerCAmelCase__			:Dict="[SEP]"       ,							lowerCAmelCase__			:Dict="[MASK]"       ,							lowerCAmelCase__			:Any="[CLS]"       ,							**lowerCAmelCase__			:Optional[int]       ,							)				->  List[str]:


										'''simple docstring'''




										snake_case_				:					List[Any]   =       AddedToken(lowerCAmelCase__       ,							lstrip=lowerCAmelCase__       ,							rstrip=lowerCAmelCase__				) if isinstance(lowerCAmelCase__       ,							lowerCAmelCase__				) else bos_token
										snake_case_				:					Dict   =       AddedToken(lowerCAmelCase__       ,							lstrip=lowerCAmelCase__       ,							rstrip=lowerCAmelCase__				) if isinstance(lowerCAmelCase__       ,							lowerCAmelCase__				) else eos_token
										snake_case_				:					Any   =       AddedToken(lowerCAmelCase__       ,							lstrip=lowerCAmelCase__       ,							rstrip=lowerCAmelCase__				) if isinstance(lowerCAmelCase__       ,							lowerCAmelCase__				) else unk_token
										snake_case_				:					int   =       AddedToken(lowerCAmelCase__       ,							lstrip=lowerCAmelCase__       ,							rstrip=lowerCAmelCase__				) if isinstance(lowerCAmelCase__       ,							lowerCAmelCase__				) else pad_token
										snake_case_				:					Optional[int]   =       AddedToken(lowerCAmelCase__       ,							lstrip=lowerCAmelCase__       ,							rstrip=lowerCAmelCase__				) if isinstance(lowerCAmelCase__       ,							lowerCAmelCase__				) else cls_token
										snake_case_				:					List[str]   =       AddedToken(lowerCAmelCase__       ,							lstrip=lowerCAmelCase__       ,							rstrip=lowerCAmelCase__				) if isinstance(lowerCAmelCase__       ,							lowerCAmelCase__				) else sep_token

										# Mask token behave like a normal word, i.e. include the space before it
										snake_case_				:					Optional[int]   =       AddedToken(lowerCAmelCase__       ,							lstrip=lowerCAmelCase__       ,							rstrip=lowerCAmelCase__				) if isinstance(lowerCAmelCase__       ,							lowerCAmelCase__				) else mask_token

										super().__init__(
										    lowerCAmelCase__       ,							tokenizer_file=lowerCAmelCase__       ,							bos_token=lowerCAmelCase__       ,							eos_token=lowerCAmelCase__       ,							unk_token=lowerCAmelCase__       ,							sep_token=lowerCAmelCase__       ,							pad_token=lowerCAmelCase__       ,							cls_token=lowerCAmelCase__       ,							mask_token=lowerCAmelCase__       ,							**lowerCAmelCase__       ,							)

										snake_case_				:					Optional[int]   =       vocab_file
										snake_case_				:					int   =       False if not self.vocab_file else True

							def 							_A	(		self			:int       ,							lowerCAmelCase__			:List[int]       ,							lowerCAmelCase__			:Optional[List[int]] = None				)				->  List[int]:


										'''simple docstring'''




										snake_case_				:					Optional[int]   =       [self.sep_token_id]
										snake_case_				:					List[str]   =       [self.cls_token_id]
										if token_ids_a is None:
													return cls + token_ids_a + sep
										return cls + token_ids_a + sep + token_ids_a + sep

							def 							_A	(		self			:Optional[Any]       ,							lowerCAmelCase__			:List[int]       ,							lowerCAmelCase__			:Optional[List[int]] = None       ,							lowerCAmelCase__			:bool = False				)				->  List[int]:


										'''simple docstring'''




										if already_has_special_tokens:
													if token_ids_a is not None:
																raise ValueError(
																    "You should not supply a second sequence if the provided sequence of "
																    "ids is already formatted with special tokens for the model."				)
													return [1 if x in [self.sep_token_id, self.cls_token_id] else 0 for x in token_ids_a]

										if token_ids_a is None:
													return [1] + ([0] * len(lowerCAmelCase__				)) + [1]
										return [1] + ([0] * len(lowerCAmelCase__				)) + [1] + ([0] * len(lowerCAmelCase__				)) + [1]

							def 							_A	(		self			:Union[str, Any]       ,							lowerCAmelCase__			:List[int]       ,							lowerCAmelCase__			:Optional[List[int]] = None				)				->  List[int]:


										'''simple docstring'''




										snake_case_				:					Optional[int]   =       [self.sep_token_id]
										snake_case_				:					Tuple   =       [self.cls_token_id]

										if token_ids_a is None:
													return len(cls + token_ids_a + sep				) * [0]
										return len(cls + token_ids_a + sep				) * [0] + len(token_ids_a + sep				) * [1]






							def 							_A	(		self			:Optional[Any]       ,							lowerCAmelCase__			:str       ,							lowerCAmelCase__			:Optional[str] = None				)				->  Tuple[str]:


										'''simple docstring'''




										if not self.can_save_slow_tokenizer:
													raise ValueError(
													    "Your fast tokenizer does not have the necessary information to save the vocabulary for a slow "
													    "tokenizer."				)

										if not os.path.isdir(lowerCAmelCase__				):
													logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''				)
													return
										snake_case_				:					Any   =       os.path.join(
										    lowerCAmelCase__       ,							(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]				)

										if os.path.abspath(self.vocab_file				) != os.path.abspath(lowerCAmelCase__				):
													copyfile(self.vocab_file       ,							lowerCAmelCase__				)

										return (out_vocab_file,)












'''simple docstring'''




from unittest import TestCase

from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters

def 	__UpperCAmelCase       ( )->    int:



			"""simple docstring"""



			snake_case_				:					Any   =       {
			    "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],
			}
			snake_case_				:					int   =       Dataset.from_dict(__magic_name__						)
			return dataset







class    A_	(a_							):
							"""simple docstring"""




							def 							_A	(		self			:List[str]				)				->  str:


										'''simple docstring'''




										snake_case_				:					Union[str, Any]   =       get_dataset()
										snake_case_				:					Optional[int]   =       make_duplicate_clusters(lowerCAmelCase__       ,							0.8_5				)
										self.assertEqual(len(duplicate_clusters[0]				)       ,							2				)






							def 							_A	(		self			:Union[str, Any]				)				->  List[str]:


										'''simple docstring'''




										snake_case_				:					Optional[int]   =       get_dataset()
										snake_case_,	snake_case_				:					List[Any]   =       deduplicate_dataset(lowerCAmelCase__				)
										self.assertEqual(len(lowerCAmelCase__				)       ,							2				)
										print(lowerCAmelCase__				)
										self.assertEqual(duplicate_clusters[0][0]["copies"]       ,							2				)
										self.assertEqual(duplicate_clusters[0][0]["is_extreme"]       ,							lowerCAmelCase__				)




