



'''simple docstring'''






import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch

import numpy as np
import pytest

from datasets.arrow_dataset import Dataset
from datasets.search import ElasticSearchIndex, FaissIndex, MissingIndex

from .utils import require_elasticsearch, require_faiss


UpperCamelCase__:   Dict								=			pytest.mark.integration

@require_faiss
class 				SCREAMING_SNAKE_CASE(							A__			):







	"""simple docstring"""






	def      A	(						self			:     List[str]		)			->		int:
								UpperCAmelCase :       Union[str, Any] 							=		Dataset.from_dict({'''filename''': ['''my_name-train''' + '''_''' + str(__snake_case		) for x in np.arange(30		).tolist()]}		)
								return dset







	def      A	(						self			:     List[Any]		)			->		Optional[int]:
								import faiss

								UpperCAmelCase :       Dataset 							=		self._create_dummy_dataset()
								UpperCAmelCase :       Tuple 							=		dset.map(
								    lambda __snake_case		,			__snake_case		: {"vecs": i * np.ones(5		,			dtype=np.floataa		)}		,			with_indices=__snake_case		,			keep_in_memory=__snake_case		)
								UpperCAmelCase :       Optional[int] 							=		dset.add_faiss_index('''vecs'''		,			batch_size=100		,			metric_type=faiss.METRIC_INNER_PRODUCT		)
								UpperCAmelCase							,		UpperCAmelCase :       Optional[int] 							=		dset.get_nearest_examples('''vecs'''		,			np.ones(5		,			dtype=np.floataa		)		)
								self.assertEqual(examples['''filename'''][0]		,			'''my_name-train_29'''		)
								dset.drop_index('''vecs'''		)







	def      A	(						self			:     Dict		)			->		Tuple:
								import faiss

								UpperCAmelCase :       Dataset 							=		self._create_dummy_dataset()
								dset.add_faiss_index_from_external_arrays(
								    external_arrays=np.ones((30, 5)		) * np.arange(30		).reshape(-1		,			1		)		,			index_name='''vecs'''		,			batch_size=100		,			metric_type=faiss.METRIC_INNER_PRODUCT		,			)
								UpperCAmelCase							,		UpperCAmelCase :       Optional[int] 							=		dset.get_nearest_examples('''vecs'''		,			np.ones(5		,			dtype=np.floataa		)		)
								self.assertEqual(examples['''filename'''][0]		,			'''my_name-train_29'''		)







	def      A	(						self			:     Tuple		)			->		Tuple:
								import faiss

								UpperCAmelCase :       Dataset 							=		self._create_dummy_dataset()
								dset.add_faiss_index_from_external_arrays(
								    external_arrays=np.ones((30, 5)		) * np.arange(30		).reshape(-1		,			1		)		,			index_name='''vecs'''		,			metric_type=faiss.METRIC_INNER_PRODUCT		,			)

								# Setting delete=False and unlinking manually is not pretty... but it is required on Windows to
								# ensure somewhat stable behaviour. If we don't, we get PermissionErrors. This is an age-old issue.
								# see https://bugs.python.org/issue14243 and
								# https://stackoverflow.com/questions/23212435/permission-denied-to-write-to-my-temporary-file/23212515
								with tempfile.NamedTemporaryFile(delete=__snake_case		) as tmp_file:
															dset.save_faiss_index('''vecs'''		,			tmp_file.name		)
															dset.load_faiss_index('''vecs2'''		,			tmp_file.name		)
								os.unlink(tmp_file.name		)

								UpperCAmelCase							,		UpperCAmelCase :       List[str] 							=		dset.get_nearest_examples('''vecs2'''		,			np.ones(5		,			dtype=np.floataa		)		)
								self.assertEqual(examples['''filename'''][0]		,			'''my_name-train_29'''		)







	def      A	(						self			:     Optional[int]		)			->		Dict:
								UpperCAmelCase :       Dataset 							=		self._create_dummy_dataset()
								dset.add_faiss_index_from_external_arrays(
								    external_arrays=np.ones((30, 5)		) * np.arange(30		).reshape(-1		,			1		)		,			index_name='''vecs'''		)
								dset.drop_index('''vecs'''		)
								self.assertRaises(__snake_case		,			partial(dset.get_nearest_examples		,			'''vecs2'''		,			np.ones(5		,			dtype=np.floataa		)		)		)







	def      A	(						self			:     str		)			->		str:
								from elasticsearch import Elasticsearch

								UpperCAmelCase :       Dataset 							=		self._create_dummy_dataset()
								with patch('''elasticsearch.Elasticsearch.search'''		) as mocked_search, patch(
								    '''elasticsearch.client.IndicesClient.create'''		) as mocked_index_create, patch('''elasticsearch.helpers.streaming_bulk'''		) as mocked_bulk:
															UpperCAmelCase :       Dict 							=		{'''acknowledged''': True}
															mocked_bulk.return_value([(True, None)] * 30		)
															UpperCAmelCase :       Dict 							=		{'''hits''': {'''hits''': [{'''_score''': 1, '''_id''': 29}]}}
															UpperCAmelCase :       List[Any] 							=		Elasticsearch()

															dset.add_elasticsearch_index('''filename'''		,			es_client=__snake_case		)
															UpperCAmelCase							,		UpperCAmelCase :       Any 							=		dset.get_nearest_examples('''filename'''		,			'''my_name-train_29'''		)
															self.assertEqual(examples['''filename'''][0]		,			'''my_name-train_29'''		)

@require_faiss
class 				SCREAMING_SNAKE_CASE(							A__			):







	"""simple docstring"""






	def      A	(						self			:     Optional[int]		)			->		Union[str, Any]:
								import faiss

								UpperCAmelCase :       Tuple 							=		FaissIndex(metric_type=faiss.METRIC_INNER_PRODUCT		)

								# add vectors
								index.add_vectors(np.eye(5		,			dtype=np.floataa		)		)
								self.assertIsNotNone(index.faiss_index		)
								self.assertEqual(index.faiss_index.ntotal		,			5		)
								index.add_vectors(np.zeros((5, 5)		,			dtype=np.floataa		)		)
								self.assertEqual(index.faiss_index.ntotal		,			10		)

								# single query
								UpperCAmelCase :       Optional[Any] 							=		np.zeros(5		,			dtype=np.floataa		)
								UpperCAmelCase :       List[str] 							=		1
								UpperCAmelCase							,		UpperCAmelCase :       Optional[int] 							=		index.search(__snake_case		)
								self.assertRaises(__snake_case		,			index.search		,			query.reshape(-1		,			1		)		)
								self.assertGreater(scores[0]		,			0		)
								self.assertEqual(indices[0]		,			1		)

								# batched queries
								UpperCAmelCase :       Optional[int] 							=		np.eye(5		,			dtype=np.floataa		)[::-1]
								UpperCAmelCase							,		UpperCAmelCase :       List[str] 							=		index.search_batch(__snake_case		)
								self.assertRaises(__snake_case		,			index.search_batch		,			queries[0]		)
								UpperCAmelCase :       List[Any] 							=		[scores[0] for scores in total_scores]
								UpperCAmelCase :       Optional[Any] 							=		[indices[0] for indices in total_indices]
								self.assertGreater(np.min(__snake_case		)		,			0		)
								self.assertListEqual([4, 3, 2, 1, 0]		,			__snake_case		)







	def      A	(						self			:     str		)			->		Union[str, Any]:
								import faiss

								UpperCAmelCase :       Optional[Any] 							=		FaissIndex(string_factory='''Flat'''		)
								index.add_vectors(np.eye(5		,			dtype=np.floataa		)		)
								self.assertIsInstance(index.faiss_index		,			faiss.IndexFlat		)
								UpperCAmelCase :       int 							=		FaissIndex(string_factory='''LSH'''		)
								index.add_vectors(np.eye(5		,			dtype=np.floataa		)		)
								self.assertIsInstance(index.faiss_index		,			faiss.IndexLSH		)
								with self.assertRaises(__snake_case		):
															UpperCAmelCase :       List[str] 							=		FaissIndex(string_factory='''Flat'''		,			custom_index=faiss.IndexFlat(5		)		)







	def      A	(						self			:     int		)			->		List[str]:
								import faiss

								UpperCAmelCase :       Any 							=		faiss.IndexFlat(5		)
								UpperCAmelCase :       Optional[int] 							=		FaissIndex(custom_index=__snake_case		)
								index.add_vectors(np.eye(5		,			dtype=np.floataa		)		)
								self.assertIsInstance(index.faiss_index		,			faiss.IndexFlat		)







	def      A	(						self			:     str		)			->		List[str]:
								import faiss

								UpperCAmelCase :       int 							=		FaissIndex(metric_type=faiss.METRIC_INNER_PRODUCT		)
								index.add_vectors(np.eye(5		,			dtype=np.floataa		)		)

								# Setting delete=False and unlinking manually is not pretty... but it is required on Windows to
								# ensure somewhat stable behaviour. If we don't, we get PermissionErrors. This is an age-old issue.
								# see https://bugs.python.org/issue14243 and
								# https://stackoverflow.com/questions/23212435/permission-denied-to-write-to-my-temporary-file/23212515
								with tempfile.NamedTemporaryFile(delete=__snake_case		) as tmp_file:
															index.save(tmp_file.name		)
															UpperCAmelCase :       int 							=		FaissIndex.load(tmp_file.name		)
								os.unlink(tmp_file.name		)

								UpperCAmelCase :       str 							=		np.zeros(5		,			dtype=np.floataa		)
								UpperCAmelCase :       List[str] 							=		1
								UpperCAmelCase							,		UpperCAmelCase :       List[Any] 							=		index.search(__snake_case		)
								self.assertGreater(scores[0]		,			0		)
								self.assertEqual(indices[0]		,			1		)


@require_faiss
def  snake_case_     (					_lowerCAmelCase  :						Optional[int]  )      ->   Union[str, Any]:
							import faiss

							UpperCAmelCase :       List[str] 							=		FaissIndex(metric_type=faiss.METRIC_INNER_PRODUCT  )
							index.add_vectors(np.eye(5   ,      dtype=np.floataa  )  )

							UpperCAmelCase :       Dict 							=		'''index.faiss'''
							UpperCAmelCase :       Dict 							=		f"""mock://{index_name}"""
							index.save(_lowerCAmelCase   ,      storage_options=mockfs.storage_options  )
							UpperCAmelCase :       Tuple 							=		FaissIndex.load(_lowerCAmelCase   ,      storage_options=mockfs.storage_options  )

							UpperCAmelCase :       Union[str, Any] 							=		np.zeros(5   ,      dtype=np.floataa  )
							UpperCAmelCase :       Any 							=		1
							UpperCAmelCase							,		UpperCAmelCase :       Tuple 							=		index.search(_lowerCAmelCase  )
							assert scores[0] > 0
							assert indices[0] == 1




@require_elasticsearch
class 				SCREAMING_SNAKE_CASE(							A__			):







	"""simple docstring"""






	def      A	(						self			:     str		)			->		Union[str, Any]:
								from elasticsearch import Elasticsearch

								with patch('''elasticsearch.Elasticsearch.search'''		) as mocked_search, patch(
								    '''elasticsearch.client.IndicesClient.create'''		) as mocked_index_create, patch('''elasticsearch.helpers.streaming_bulk'''		) as mocked_bulk:
															UpperCAmelCase :       Any 							=		Elasticsearch()
															UpperCAmelCase :       List[Any] 							=		{'''acknowledged''': True}
															UpperCAmelCase :       Optional[Any] 							=		ElasticSearchIndex(es_client=__snake_case		)
															mocked_bulk.return_value([(True, None)] * 3		)
															index.add_documents(['''foo''', '''bar''', '''foobar''']		)

															# single query
															UpperCAmelCase :       Optional[Any] 							=		'''foo'''
															UpperCAmelCase :       List[str] 							=		{'''hits''': {'''hits''': [{'''_score''': 1, '''_id''': 0}]}}
															UpperCAmelCase							,		UpperCAmelCase :       int 							=		index.search(__snake_case		)
															self.assertEqual(scores[0]		,			1		)
															self.assertEqual(indices[0]		,			0		)

															# single query with timeout
															UpperCAmelCase :       str 							=		'''foo'''
															UpperCAmelCase :       Optional[int] 							=		{'''hits''': {'''hits''': [{'''_score''': 1, '''_id''': 0}]}}
															UpperCAmelCase							,		UpperCAmelCase :       Tuple 							=		index.search(__snake_case		,			request_timeout=30		)
															self.assertEqual(scores[0]		,			1		)
															self.assertEqual(indices[0]		,			0		)

															# batched queries
															UpperCAmelCase :       Any 							=		['''foo''', '''bar''', '''foobar''']
															UpperCAmelCase :       Optional[Any] 							=		{'''hits''': {'''hits''': [{'''_score''': 1, '''_id''': 1}]}}
															UpperCAmelCase							,		UpperCAmelCase :       Optional[int] 							=		index.search_batch(__snake_case		)
															UpperCAmelCase :       int 							=		[scores[0] for scores in total_scores]
															UpperCAmelCase :       List[str] 							=		[indices[0] for indices in total_indices]
															self.assertGreater(np.min(__snake_case		)		,			0		)
															self.assertListEqual([1, 1, 1]		,			__snake_case		)

															# batched queries with timeout
															UpperCAmelCase :       Optional[int] 							=		['''foo''', '''bar''', '''foobar''']
															UpperCAmelCase :       int 							=		{'''hits''': {'''hits''': [{'''_score''': 1, '''_id''': 1}]}}
															UpperCAmelCase							,		UpperCAmelCase :       str 							=		index.search_batch(__snake_case		,			request_timeout=30		)
															UpperCAmelCase :       Optional[Any] 							=		[scores[0] for scores in total_scores]
															UpperCAmelCase :       Tuple 							=		[indices[0] for indices in total_indices]
															self.assertGreater(np.min(__snake_case		)		,			0		)
															self.assertListEqual([1, 1, 1]		,			__snake_case		)










'''simple docstring'''






import random

from .binary_exp_mod import bin_exp_mod


def  snake_case_     (					_lowerCAmelCase  :						Tuple   ,      _lowerCAmelCase  :						Optional[Any]=1000  )      ->   int:
							if n < 2:
														return False

							if n % 2 == 0:
														return n == 2

							# this means n is odd
							UpperCAmelCase :       str 							=		n - 1
							UpperCAmelCase :       List[Any] 							=		0
							while d % 2 == 0:
														d /= 2
														exp += 1

							# n - 1=d*(2**exp)
							UpperCAmelCase :       List[str] 							=		0
							while count < prec:
														UpperCAmelCase :       int 							=		random.randint(2   ,      n - 1  )
														UpperCAmelCase :       List[str] 							=		bin_exp_mod(_lowerCAmelCase   ,      _lowerCAmelCase   ,      _lowerCAmelCase  )
														if b != 1:
																					UpperCAmelCase :       int 							=		True
																					for _ in range(_lowerCAmelCase  ):
																												if b == n - 1:
																																			UpperCAmelCase :       Dict 							=		False
																																			break
																												UpperCAmelCase :       str 							=		b * b
																												b %= n
																					if flag:
																												return False
																					count += 1
							return True


if __name__ == "__main__":
						UpperCamelCase__:   Optional[int]								=			abs(int(input("Enter bound : ").strip()))
						print("Here's the list of primes:")
						print(", ".join(str(i) for i in range(n + 1) if is_prime_big(i)))





