

'''simple docstring'''



import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch

import numpy as np
from datasets import Dataset

from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOCK_RECORDS_FILENAME, RealmRetriever
from transformers.models.realm.tokenization_realm import VOCAB_FILES_NAMES, RealmTokenizer



class lowerCamelCase			(  __lowercase						):



			'''simple docstring'''






			def lowercase__						(				self	:						Union[str, Any]			)      ->		Tuple:





									'''simple docstring'''
									A__					:       Tuple     =tempfile.mkdtemp()
									A__					:       List[str]     =5

									# Realm tok
									A__					:       Optional[int]     =[
									    '''[UNK]''',
									    '''[CLS]''',
									    '''[SEP]''',
									    '''[PAD]''',
									    '''[MASK]''',
									    '''test''',
									    '''question''',
									    '''this''',
									    '''is''',
									    '''the''',
									    '''first''',
									    '''second''',
									    '''third''',
									    '''fourth''',
									    '''fifth''',
									    '''record''',
									    '''want''',
									    '''##want''',
									    '''##ed''',
									    '''wa''',
									    '''un''',
									    '''runn''',
									    '''##ing''',
									    ''',''',
									    '''low''',
									    '''lowest''',
									]
									A__					:       Optional[int]     =os.path.join(self.tmpdirname		,      """realm_tokenizer"""			)
									os.makedirs(_a		,      exist_ok=_a			)
									A__					:       str     =os.path.join(_a		,      VOCAB_FILES_NAMES["""vocab_file"""]			)
									with open(self.vocab_file		,      """w"""		,      encoding="""utf-8"""			) as vocab_writer:
															vocab_writer.write("""""".join([x + """\n""" for x in vocab_tokens]			)			)

									A__					:       List[str]     =os.path.join(self.tmpdirname		,      """realm_block_records"""			)
									os.makedirs(_a		,      exist_ok=_a			)


			def lowercase__						(				self	:						List[Any]			)      ->		RealmTokenizer:





									'''simple docstring'''
									return RealmTokenizer.from_pretrained(os.path.join(self.tmpdirname		,      """realm_tokenizer"""			)			)


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





									'''simple docstring'''
									shutil.rmtree(self.tmpdirname			)


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





									'''simple docstring'''
									A__					:       int     =RealmConfig(num_block_records=self.num_block_records			)
									return config


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





									'''simple docstring'''
									A__					:       Optional[Any]     =Dataset.from_dict(
									    {
									        """id""": ["""0""", """1"""],
									        """question""": ["""foo""", """bar"""],
									        """answers""": [["""Foo""", """Bar"""], ["""Bar"""]],
									    }			)
									return dataset


			def lowercase__						(				self	:						Tuple			)      ->		Dict:





									'''simple docstring'''
									A__					:       Any     =np.array(
									    [
									        b"""This is the first record""",
									        b"""This is the second record""",
									        b"""This is the third record""",
									        b"""This is the fourth record""",
									        b"""This is the fifth record""",
									        b"""This is a longer longer longer record""",
									    ]		,      dtype=_a		,      )
									return block_records


			def lowercase__						(				self	:						Any			)      ->		Optional[int]:





									'''simple docstring'''
									A__					:       List[str]     =RealmRetriever(
									    block_records=self.get_dummy_block_records()		,      tokenizer=self.get_tokenizer()		,      )
									return retriever


			def lowercase__						(				self	:						List[str]			)      ->		Optional[int]:





									'''simple docstring'''
									A__					:       Dict     =self.get_config()
									A__					:       Tuple     =self.get_dummy_retriever()
									A__					:       Dict     =retriever.tokenizer

									A__					:       Union[str, Any]     =np.array([0, 3]		,      dtype="""long"""			)
									A__					:       Any     =tokenizer(["""Test question"""]			).input_ids
									A__					:       int     =tokenizer(
									    ["""the fourth"""]		,      add_special_tokens=_a		,      return_token_type_ids=_a		,      return_attention_mask=_a		,      ).input_ids
									A__					:       str     =config.reader_seq_len

									A__					:       Any     =retriever(
									    _a		,      _a		,      answer_ids=_a		,      max_length=_a		,      return_tensors="""np"""			)

									self.assertEqual(len(_a			)		,      2			)
									self.assertEqual(len(_a			)		,      2			)
									self.assertEqual(len(_a			)		,      2			)
									self.assertEqual(concat_inputs.input_ids.shape		,      (2, 10)			)
									self.assertEqual(concat_inputs.attention_mask.shape		,      (2, 10)			)
									self.assertEqual(concat_inputs.token_type_ids.shape		,      (2, 10)			)
									self.assertEqual(concat_inputs.special_tokens_mask.shape		,      (2, 10)			)
									self.assertEqual(
									    tokenizer.convert_ids_to_tokens(concat_inputs.input_ids[0]			)		,      ["""[CLS]""", """test""", """question""", """[SEP]""", """this""", """is""", """the""", """first""", """record""", """[SEP]"""]		,      )
									self.assertEqual(
									    tokenizer.convert_ids_to_tokens(concat_inputs.input_ids[1]			)		,      ["""[CLS]""", """test""", """question""", """[SEP]""", """this""", """is""", """the""", """fourth""", """record""", """[SEP]"""]		,      )


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





									'''simple docstring'''
									A__					:       Optional[int]     =self.get_config()
									A__					:       Union[str, Any]     =self.get_dummy_retriever()
									A__					:       Tuple     =retriever.tokenizer

									A__					:       List[str]     =np.array([0, 3, 5]		,      dtype="""long"""			)
									A__					:       int     =tokenizer(["""Test question"""]			).input_ids
									A__					:       List[str]     =tokenizer(
									    ["""the fourth""", """longer longer"""]		,      add_special_tokens=_a		,      return_token_type_ids=_a		,      return_attention_mask=_a		,      ).input_ids
									A__					:       Union[str, Any]     =config.reader_seq_len

									A__					:       List[Any]     =retriever(
									    _a		,      _a		,      answer_ids=_a		,      max_length=_a		,      return_tensors="""np"""			)

									self.assertEqual([False, True, True]		,      _a			)
									self.assertEqual([[-1, -1, -1], [6, -1, -1], [6, 7, 8]]		,      _a			)
									self.assertEqual([[-1, -1, -1], [7, -1, -1], [7, 8, 9]]		,      _a			)



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





									'''simple docstring'''
									A__					:       Any     =self.get_dummy_retriever()
									retriever.save_pretrained(os.path.join(self.tmpdirname		,      """realm_block_records"""			)			)

									# Test local path
									A__					:       str     =retriever.from_pretrained(os.path.join(self.tmpdirname		,      """realm_block_records"""			)			)
									self.assertEqual(retriever.block_records[0]		,      b"""This is the first record"""			)

									# Test mocked remote path
									with patch("""transformers.models.realm.retrieval_realm.hf_hub_download"""			) as mock_hf_hub_download:
															A__					:       Tuple     =os.path.join(
															    os.path.join(self.tmpdirname		,      """realm_block_records"""			)		,      _REALM_BLOCK_RECORDS_FILENAME			)
															A__					:       str     =RealmRetriever.from_pretrained("""google/realm-cc-news-pretrained-openqa"""			)

									self.assertEqual(retriever.block_records[0]		,      b"""This is the first record"""			)


'''simple docstring'''



from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def 						__lowerCamelCase	(       __snake_case					:		int	)	->							int:






						"""simple docstring"""





						A__					:       List[Any]     =prime_factors(__snake_case	)
						if is_square_free(__snake_case	):
												return -1 if len(__snake_case	) % 2 else 1
						return 0


if __name__ == "__main__":
		import doctest

		doctest.testmod()

