





'''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


__lowerCAmelCase				:      List[Any]						      =pytest.mark.integration






@require_faiss
class   UpperCAmelCase      (			UpperCamelCase__							):
 def 	UpperCAmelCase_				(							self :int				)->				int:
     A__							=     Dataset.from_dict({"filename": ["my_name-train" + "_" + str(lowercase_				) for x in np.arange(30				).tolist()]}				)
     return dset
 def 	UpperCAmelCase_				(							self :Dict				)->				Tuple:
     import faiss

     A__							=     self._create_dummy_dataset()
     A__							=     dset.map(
         lambda lowercase_		,			lowercase_				: {"vecs": i * np.ones(5		,			dtype=np.floataa				)}		,			with_indices=lowercase_		,			keep_in_memory=lowercase_				)
     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 :Dict				)->				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"		,			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 :Any				)->				Any:
     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=lowercase_				) 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]				)->				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(lowercase_		,			partial(dset.get_nearest_examples		,			"vecs2"		,			np.ones(5		,			dtype=np.floataa				)				)				)



 def 	UpperCAmelCase_				(							self :str				)->				int:
     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=lowercase_				)
         A__,      A__							=     dset.get_nearest_examples("filename"		,			"my_name-train_29"				)
         self.assertEqual(examples["filename"][0]		,			"my_name-train_29"				)






@require_faiss
class   UpperCAmelCase      (			UpperCamelCase__							):
 def 	UpperCAmelCase_				(							self :Dict				)->				Union[str, Any]:
     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(lowercase_				)
     self.assertRaises(lowercase_		,			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(lowercase_				)
     self.assertRaises(lowercase_		,			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(lowercase_				)		,			0				)
     self.assertListEqual([4, 3, 2, 1, 0]		,			lowercase_				)
 def 	UpperCAmelCase_				(							self :Tuple				)->				Any:
     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(lowercase_				):
         A__							=     FaissIndex(string_factory="Flat"		,			custom_index=faiss.IndexFlat(5				)				)
 def 	UpperCAmelCase_				(							self :str				)->				Tuple:
     import faiss

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



 def 	UpperCAmelCase_				(							self :Optional[int]				)->				List[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=lowercase_				) 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(lowercase_				)
     self.assertGreater(scores[0]		,			0				)
     self.assertEqual(indices[0]		,			1				)





@require_faiss
def 		UpperCamelCase							(				_lowerCamelCase   :   Union[str, Any]			):
    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(_lowerCamelCase		,			storage_options=mockfs.storage_options			)
    A__							=     FaissIndex.load(_lowerCamelCase		,			storage_options=mockfs.storage_options			)

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






@require_elasticsearch
class   UpperCAmelCase      (			UpperCamelCase__							):
 def 	UpperCAmelCase_				(							self :Optional[int]				)->				int:
     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=lowercase_				)
         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(lowercase_				)
         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(lowercase_		,			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(lowercase_				)
         A__							=     [scores[0] for scores in total_scores]
         A__							=     [indices[0] for indices in total_indices]
         self.assertGreater(np.min(lowercase_				)		,			0				)
         self.assertListEqual([1, 1, 1]		,			lowercase_				)

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










'''simple docstring'''

from __future__ import annotations





def 		UpperCamelCase							(				_lowerCamelCase   :   list[int]			):  # This function is recursive
    A__							=     len(_lowerCamelCase			)
    # If the array contains only one element, we return it (it's the stop condition of
    # recursion)
    if array_length <= 1:
        return array
        # Else
    A__							=     array[0]
    A__							=     False
    A__							=     1
    A__							=     []
    while not is_found and i < array_length:
        if array[i] < pivot:
            A__							=     True
            A__							=     [element for element in array[i:] if element >= array[i]]
            A__							=     longest_subsequence(_lowerCamelCase			)
            if len(_lowerCamelCase			) > len(_lowerCamelCase			):
                A__							=     temp_array
        else:
            i += 1

    A__							=     [element for element in array[1:] if element >= pivot]
    A__							=     [pivot, *longest_subsequence(_lowerCamelCase			)]
    if len(_lowerCamelCase			) > len(_lowerCamelCase			):
        return temp_array
    else:
        return longest_subseq


if __name__ == "__main__":
  import doctest

  doctest.testmod()



