




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[str]				=			pytest.mark.integration


@require_faiss
class    lowerCamelCase    (		_lowerCamelCase						):






			'''simple docstring'''





			def 							UpperCAmelCase__       ( self			:   Dict  )						->   Dict:
								__magic_name__							:	Optional[int]    							=							Dataset.from_dict({'''filename''': ['''my_name-train''' + '''_''' + str(lowerCamelCase_  ) for x in np.arange(30  ).tolist()]}  )
								return dset

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

								__magic_name__							:	Dataset    							=							self._create_dummy_dataset()
								__magic_name__							:	Union[str, Any]    							=							dset.map(
								    lambda lowerCamelCase_       ,						lowerCamelCase_  : {"vecs": i * np.ones(5       ,						dtype=np.floataa  )}       ,						with_indices=lowerCamelCase_       ,						keep_in_memory=lowerCamelCase_  )
								__magic_name__							:	Dict    							=							dset.add_faiss_index('''vecs'''       ,						batch_size=100       ,						metric_type=faiss.METRIC_INNER_PRODUCT  )
								__magic_name__							:	Optional[Any]    							=							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			:   Optional[Any]  )						->   Union[str, Any]:
								import faiss

								__magic_name__							:	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       ,						)
								__magic_name__							:	Dict    							=							dset.get_nearest_examples('''vecs'''       ,						np.ones(5       ,						dtype=np.floataa  )  )
								self.assertEqual(examples['''filename'''][0]       ,						'''my_name-train_29'''  )

			def 							UpperCAmelCase__       ( self			:   Optional[int]  )						->   Optional[int]:
								import faiss

								__magic_name__							:	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=lowerCamelCase_  ) as tmp_file:
													dset.save_faiss_index('''vecs'''       ,						tmp_file.name  )
													dset.load_faiss_index('''vecs2'''       ,						tmp_file.name  )
								os.unlink(tmp_file.name  )

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

			def 							UpperCAmelCase__       ( self			:   int  )						->   List[str]:
								__magic_name__							:	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(lowerCamelCase_       ,						partial(dset.get_nearest_examples       ,						'''vecs2'''       ,						np.ones(5       ,						dtype=np.floataa  )  )  )


			def 							UpperCAmelCase__       ( self			:   str  )						->   List[Any]:
								from elasticsearch import Elasticsearch

								__magic_name__							:	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:
													__magic_name__							:	int    							=							{'''acknowledged''': True}
													mocked_bulk.return_value([(True, None)] * 30  )
													__magic_name__							:	Optional[int]    							=							{'''hits''': {'''hits''': [{'''_score''': 1, '''_id''': 29}]}}
													__magic_name__							:	Optional[int]    							=							Elasticsearch()

													dset.add_elasticsearch_index('''filename'''       ,						es_client=lowerCamelCase_  )
													__magic_name__							:	str    							=							dset.get_nearest_examples('''filename'''       ,						'''my_name-train_29'''  )
													self.assertEqual(examples['''filename'''][0]       ,						'''my_name-train_29'''  )






@require_faiss
class    lowerCamelCase    (		_lowerCamelCase						):






			'''simple docstring'''





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

								__magic_name__							:	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
								__magic_name__							:	str    							=							np.zeros(5       ,						dtype=np.floataa  )
								__magic_name__							:	Dict    							=							1
								__magic_name__							:	Optional[Any]    							=							index.search(lowerCamelCase_  )
								self.assertRaises(lowerCamelCase_       ,						index.search       ,						query.reshape(-1       ,						1  )  )
								self.assertGreater(scores[0]       ,						0  )
								self.assertEqual(indices[0]       ,						1  )

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

			def 							UpperCAmelCase__       ( self			:   List[Any]  )						->   Any:
								import faiss

								__magic_name__							:	Dict    							=							FaissIndex(string_factory='''Flat'''  )
								index.add_vectors(np.eye(5       ,						dtype=np.floataa  )  )
								self.assertIsInstance(index.faiss_index       ,						faiss.IndexFlat  )
								__magic_name__							:	Tuple    							=							FaissIndex(string_factory='''LSH'''  )
								index.add_vectors(np.eye(5       ,						dtype=np.floataa  )  )
								self.assertIsInstance(index.faiss_index       ,						faiss.IndexLSH  )
								with self.assertRaises(lowerCamelCase_  ):
													__magic_name__							:	Optional[int]    							=							FaissIndex(string_factory='''Flat'''       ,						custom_index=faiss.IndexFlat(5  )  )

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

								__magic_name__							:	List[Any]    							=							faiss.IndexFlat(5  )
								__magic_name__							:	List[Any]    							=							FaissIndex(custom_index=lowerCamelCase_  )
								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

								__magic_name__							:	Dict    							=							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=lowerCamelCase_  ) as tmp_file:
													index.save(tmp_file.name  )
													__magic_name__							:	Dict    							=							FaissIndex.load(tmp_file.name  )
								os.unlink(tmp_file.name  )

								__magic_name__							:	int    							=							np.zeros(5       ,						dtype=np.floataa  )
								__magic_name__							:	Union[str, Any]    							=							1
								__magic_name__							:	Optional[Any]    							=							index.search(lowerCamelCase_  )
								self.assertGreater(scores[0]       ,						0  )
								self.assertEqual(indices[0]       ,						1  )







@require_faiss
def 		lowercase__   (		__A:	int				):





					'''simple docstring'''






					import faiss

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

					__magic_name__							:	Tuple    							=							'''index.faiss'''
					__magic_name__							:	Optional[Any]    							=							F'''mock://{index_name}'''
					index.save(__A							,storage_options=mockfs.storage_options				)
					__magic_name__							:	Any    							=							FaissIndex.load(__A							,storage_options=mockfs.storage_options				)

					__magic_name__							:	Any    							=							np.zeros(5							,dtype=np.floataa				)
					__magic_name__							:	Dict    							=							1
					__magic_name__							:	Tuple    							=							index.search(__A				)
					assert scores[0] > 0
					assert indices[0] == 1


@require_elasticsearch
class    lowerCamelCase    (		_lowerCamelCase						):






			'''simple docstring'''





			def 							UpperCAmelCase__       ( self			:   Tuple  )						->   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:
													__magic_name__							:	Optional[int]    							=							Elasticsearch()
													__magic_name__							:	Any    							=							{'''acknowledged''': True}
													__magic_name__							:	Any    							=							ElasticSearchIndex(es_client=lowerCamelCase_  )
													mocked_bulk.return_value([(True, None)] * 3  )
													index.add_documents(['''foo''', '''bar''', '''foobar''']  )

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

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

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

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









# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works

from ...utils import deprecate
from ..controlnet.pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline  # noqa: F401


deprecate(
    '''stable diffusion controlnet''',
    '''0.22.0''',
    '''Importing `FlaxStableDiffusionControlNetPipeline` from diffusers.pipelines.stable_diffusion.flax_pipeline_stable_diffusion_controlnet is deprecated. Please import `from diffusers import FlaxStableDiffusionControlNetPipeline` instead.''',
    standard_warn=False,
    stacklevel=3,
)



