
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


SCREAMING_SNAKE_CASE							:Dict							 =				pytest.mark.integration





@require_faiss
class 							UpperCAmelCase      (  __SCREAMING_SNAKE_CASE  ):




	'''simple docstring'''





	def 				UpperCamelCase_  (       self					: Tuple ):
					__A   			= Dataset.from_dict({"filename": ["my_name-train" + "_" + str(A ) for x in np.arange(30 ).tolist()]} )
					return dset






	def 				UpperCamelCase_  (       self					: Optional[Any] ):
					import faiss

					__A   			= self._create_dummy_dataset()
					__A   			= dset.map(
					    lambda A							,A : {"vecs": i * np.ones(5							,dtype=np.floataa )}							,with_indices=A							,keep_in_memory=A )
					__A   			= dset.add_faiss_index("vecs"							,batch_size=1_00							,metric_type=faiss.METRIC_INNER_PRODUCT )
					__A			,							__A   			= 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 				UpperCamelCase_  (       self					: Tuple ):
					import faiss

					__A   			= 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=1_00							,metric_type=faiss.METRIC_INNER_PRODUCT							,)
					__A			,							__A   			= dset.get_nearest_examples("vecs"							,np.ones(5							,dtype=np.floataa ) )
					self.assertEqual(examples["filename"][0]							,"my_name-train_29" )






	def 				UpperCamelCase_  (       self					: List[str] ):
					import faiss

					__A   			= 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=A ) as tmp_file:
									dset.save_faiss_index("vecs"							,tmp_file.name )
									dset.load_faiss_index("vecs2"							,tmp_file.name )
					os.unlink(tmp_file.name )

					__A			,							__A   			= dset.get_nearest_examples("vecs2"							,np.ones(5							,dtype=np.floataa ) )
					self.assertEqual(examples["filename"][0]							,"my_name-train_29" )






	def 				UpperCamelCase_  (       self					: Union[str, Any] ):
					__A   			= 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(A							,partial(dset.get_nearest_examples							,"vecs2"							,np.ones(5							,dtype=np.floataa ) ) )







	def 				UpperCamelCase_  (       self					: Dict ):
					from elasticsearch import Elasticsearch

					__A   			= 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:
									__A   			= {"acknowledged": True}
									mocked_bulk.return_value([(True, None)] * 30 )
									__A   			= {"hits": {"hits": [{"_score": 1, "_id": 29}]}}
									__A   			= Elasticsearch()

									dset.add_elasticsearch_index("filename"							,es_client=A )
									__A			,							__A   			= dset.get_nearest_examples("filename"							,"my_name-train_29" )
									self.assertEqual(examples["filename"][0]							,"my_name-train_29" )





@require_faiss
class 							UpperCAmelCase      (  __SCREAMING_SNAKE_CASE  ):




	'''simple docstring'''





	def 				UpperCamelCase_  (       self					: Optional[int] ):
					import faiss

					__A   			= 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
					__A   			= np.zeros(5							,dtype=np.floataa )
					__A   			= 1
					__A			,							__A   			= index.search(A )
					self.assertRaises(A							,index.search							,query.reshape(-1							,1 ) )
					self.assertGreater(scores[0]							,0 )
					self.assertEqual(indices[0]							,1 )

					# batched queries
					__A   			= np.eye(5							,dtype=np.floataa )[::-1]
					__A			,							__A   			= index.search_batch(A )
					self.assertRaises(A							,index.search_batch							,queries[0] )
					__A   			= [scores[0] for scores in total_scores]
					__A   			= [indices[0] for indices in total_indices]
					self.assertGreater(np.min(A )							,0 )
					self.assertListEqual([4, 3, 2, 1, 0]							,A )






	def 				UpperCamelCase_  (       self					: Tuple ):
					import faiss

					__A   			= FaissIndex(string_factory="Flat" )
					index.add_vectors(np.eye(5							,dtype=np.floataa ) )
					self.assertIsInstance(index.faiss_index							,faiss.IndexFlat )
					__A   			= FaissIndex(string_factory="LSH" )
					index.add_vectors(np.eye(5							,dtype=np.floataa ) )
					self.assertIsInstance(index.faiss_index							,faiss.IndexLSH )
					with self.assertRaises(A ):
									__A   			= FaissIndex(string_factory="Flat"							,custom_index=faiss.IndexFlat(5 ) )






	def 				UpperCamelCase_  (       self					: Any ):
					import faiss

					__A   			= faiss.IndexFlat(5 )
					__A   			= FaissIndex(custom_index=A )
					index.add_vectors(np.eye(5							,dtype=np.floataa ) )
					self.assertIsInstance(index.faiss_index							,faiss.IndexFlat )







	def 				UpperCamelCase_  (       self					: Union[str, Any] ):
					import faiss

					__A   			= 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=A ) as tmp_file:
									index.save(tmp_file.name )
									__A   			= FaissIndex.load(tmp_file.name )
					os.unlink(tmp_file.name )

					__A   			= np.zeros(5							,dtype=np.floataa )
					__A   			= 1
					__A			,							__A   			= index.search(A )
					self.assertGreater(scores[0]							,0 )
					self.assertEqual(indices[0]							,1 )





@require_faiss
def 						UpperCAmelCase			(	a_						)		->	Optional[int]:







				"""simple docstring"""



				import faiss

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

				__A   			= "index.faiss"
				__A   			= F'''mock://{index_name}'''
				index.save(a_		,   storage_options=mockfs.storage_options						)
				__A   			= FaissIndex.load(a_		,   storage_options=mockfs.storage_options						)

				__A   			= np.zeros(5		,   dtype=np.floataa						)
				__A   			= 1
				__A			,							__A   			= index.search(a_						)
				assert scores[0] > 0
				assert indices[0] == 1





@require_elasticsearch
class 							UpperCAmelCase      (  __SCREAMING_SNAKE_CASE  ):




	'''simple docstring'''





	def 				UpperCamelCase_  (       self					: Dict ):
					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:
									__A   			= Elasticsearch()
									__A   			= {"acknowledged": True}
									__A   			= ElasticSearchIndex(es_client=A )
									mocked_bulk.return_value([(True, None)] * 3 )
									index.add_documents(["foo", "bar", "foobar"] )

									# single query
									__A   			= "foo"
									__A   			= {"hits": {"hits": [{"_score": 1, "_id": 0}]}}
									__A			,							__A   			= index.search(A )
									self.assertEqual(scores[0]							,1 )
									self.assertEqual(indices[0]							,0 )

									# single query with timeout
									__A   			= "foo"
									__A   			= {"hits": {"hits": [{"_score": 1, "_id": 0}]}}
									__A			,							__A   			= index.search(A							,request_timeout=30 )
									self.assertEqual(scores[0]							,1 )
									self.assertEqual(indices[0]							,0 )

									# batched queries
									__A   			= ["foo", "bar", "foobar"]
									__A   			= {"hits": {"hits": [{"_score": 1, "_id": 1}]}}
									__A			,							__A   			= index.search_batch(A )
									__A   			= [scores[0] for scores in total_scores]
									__A   			= [indices[0] for indices in total_indices]
									self.assertGreater(np.min(A )							,0 )
									self.assertListEqual([1, 1, 1]							,A )

									# batched queries with timeout
									__A   			= ["foo", "bar", "foobar"]
									__A   			= {"hits": {"hits": [{"_score": 1, "_id": 1}]}}
									__A			,							__A   			= index.search_batch(A							,request_timeout=30 )
									__A   			= [scores[0] for scores in total_scores]
									__A   			= [indices[0] for indices in total_indices]
									self.assertGreater(np.min(A )							,0 )
									self.assertListEqual([1, 1, 1]							,A )




from __future__ import annotations

import math






class     UpperCAmelCase__       :



    """simple docstring"""






    def __init__(			self					,   A_    )  ->       None:
         __UpperCamelCase    							=size
         # approximate the overall size of segment tree with given value
         __UpperCamelCase    							=[0 for i in range(0					,   4 * size    )]
         # create array to store lazy update
         __UpperCamelCase    							=[0 for i in range(0					,   4 * size    )]
         __UpperCamelCase    							=[0 for i in range(0					,   4 * size    )]  # flag for lazy update






    def _a					(			self					,   A_    )  ->       int:
         return idx * 2






    def _a					(			self					,   A_    )  ->       int:
         return idx * 2 + 1






    def _a					(			self					,   A_					,   A_					,   A_					,   A_    )  ->       None:
         if left_element == right_element:
              __UpperCamelCase    							=a[left_element - 1]
         else:
              __UpperCamelCase    							=(left_element + right_element) // 2
              self.build(self.left(A_    )					,   A_					,   A_					,   A_    )
              self.build(self.right(A_    )					,   mid + 1					,   A_					,   A_    )
              __UpperCamelCase    							=max(
                  self.segment_tree[self.left(A_    )]					,   self.segment_tree[self.right(A_    )]    )






    def _a					(			self					,   A_					,   A_					,   A_					,   A_					,   A_					,   A_    )  ->       bool:
         if self.flag[idx] is True:
              __UpperCamelCase    							=self.lazy[idx]
              __UpperCamelCase    							=False
              if left_element != right_element:
                   __UpperCamelCase    							=self.lazy[idx]
                   __UpperCamelCase    							=self.lazy[idx]
                   __UpperCamelCase    							=True
                   __UpperCamelCase    							=True

         if right_element < a or left_element > b:
              return True
         if left_element >= a and right_element <= b:
              __UpperCamelCase    							=val
              if left_element != right_element:
                   __UpperCamelCase    							=val
                   __UpperCamelCase    							=val
                   __UpperCamelCase    							=True
                   __UpperCamelCase    							=True
              return True
         __UpperCamelCase    							=(left_element + right_element) // 2
         self.update(self.left(A_    )					,   A_					,   A_					,   A_					,   A_					,   A_    )
         self.update(self.right(A_    )					,   mid + 1					,   A_					,   A_					,   A_					,   A_    )
         __UpperCamelCase    							=max(
             self.segment_tree[self.left(A_    )]					,   self.segment_tree[self.right(A_    )]    )
         return True






    def _a					(			self					,   A_					,   A_					,   A_					,   A_					,   A_    )  ->       int | float:
         if self.flag[idx] is True:
              __UpperCamelCase    							=self.lazy[idx]
              __UpperCamelCase    							=False
              if left_element != right_element:
                   __UpperCamelCase    							=self.lazy[idx]
                   __UpperCamelCase    							=self.lazy[idx]
                   __UpperCamelCase    							=True
                   __UpperCamelCase    							=True
         if right_element < a or left_element > b:
              return -math.inf
         if left_element >= a and right_element <= b:
              return self.segment_tree[idx]
         __UpperCamelCase    							=(left_element + right_element) // 2
         __UpperCamelCase    							=self.query(self.left(A_    )					,   A_					,   A_					,   A_					,   A_    )
         __UpperCamelCase    							=self.query(self.right(A_    )					,   mid + 1					,   A_					,   A_					,   A_    )
         return max(A_					,   A_    )






    def __str__(			self    )  ->       str:
         return str([self.query(1					,   1					,   self.size					,   A_					,   A_    ) for i in range(1					,   self.size + 1    )]    )


if __name__ == "__main__":
   _A		       =						[1, 2, -4, 7, 3, -5, 6, 11, -20, 9, 14, 15, 5, 2, -8]
   _A		       =						15
   _A		       =						SegmentTree(size)
   segt.build(1, 1, size, A)
   print(segt.query(1, 1, size, 4, 6))
   print(segt.query(1, 1, size, 7, 11))
   print(segt.query(1, 1, size, 7, 12))
   segt.update(1, 1, size, 1, 3, 111)
   print(segt.query(1, 1, size, 1, 15))
   segt.update(1, 1, size, 7, 8, 235)
   print(segt)





