

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


A__						=							pytest.mark.integration

@require_faiss
class 				__UpperCamelCase				(					SCREAMING_SNAKE_CASE			):







	def 	_SCREAMING_SNAKE_CASE							(   self: Optional[Any]      ):

						'''simple docstring'''





						__magic_name__							=    Dataset.from_dict({'filename': ['my_name-train' + '_' + str(__UpperCamelCase      ) for x in np.arange(30      ).tolist()]}      )
						return dset







	def 	_SCREAMING_SNAKE_CASE							(   self: List[str]      ):

						'''simple docstring'''





						import faiss

						__magic_name__							=    self._create_dummy_dataset()
						__magic_name__							=    dset.map(
						    lambda __UpperCamelCase  , __UpperCamelCase      : {"vecs": i * np.ones(5  , dtype=np.floataa      )}  , with_indices=__UpperCamelCase  , keep_in_memory=__UpperCamelCase      )
						__magic_name__							=    dset.add_faiss_index('vecs'  , batch_size=1_00  , metric_type=faiss.METRIC_INNER_PRODUCT      )
						__magic_name__,	__magic_name__							=    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 	_SCREAMING_SNAKE_CASE							(   self: List[Any]      ):

						'''simple docstring'''





						import faiss

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







	def 	_SCREAMING_SNAKE_CASE							(   self: Tuple      ):

						'''simple docstring'''





						import faiss

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







	def 	_SCREAMING_SNAKE_CASE							(   self: str      ):

						'''simple docstring'''





						__magic_name__							=    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(__UpperCamelCase  , partial(dset.get_nearest_examples  , 'vecs2'  , np.ones(5  , dtype=np.floataa      )      )      )







	def 	_SCREAMING_SNAKE_CASE							(   self: Union[str, Any]      ):

						'''simple docstring'''





						from elasticsearch import Elasticsearch

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

											dset.add_elasticsearch_index('filename'  , es_client=__UpperCamelCase      )
											__magic_name__,	__magic_name__							=    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			):







	def 	_SCREAMING_SNAKE_CASE							(   self: Union[str, Any]      ):

						'''simple docstring'''





						import faiss

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

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







	def 	_SCREAMING_SNAKE_CASE							(   self: Union[str, Any]      ):

						'''simple docstring'''





						import faiss

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







	def 	_SCREAMING_SNAKE_CASE							(   self: Optional[Any]      ):

						'''simple docstring'''





						import faiss

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







	def 	_SCREAMING_SNAKE_CASE							(   self: List[str]      ):

						'''simple docstring'''





						import faiss

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

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




@require_faiss
def 					_lowercase     (				a_				:					int				)				->	str:




					'''simple docstring'''







					import faiss

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

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

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


@require_elasticsearch
class 				__UpperCamelCase				(					SCREAMING_SNAKE_CASE			):







	def 	_SCREAMING_SNAKE_CASE							(   self: Union[str, Any]      ):

						'''simple docstring'''





						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__							=    Elasticsearch()
											__magic_name__							=    {'acknowledged': True}
											__magic_name__							=    ElasticSearchIndex(es_client=__UpperCamelCase      )
											mocked_bulk.return_value([(True, None)] * 3      )
											index.add_documents(['foo', 'bar', 'foobar']      )

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

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

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

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







from typing import TYPE_CHECKING

from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


A__						=							{"configuration_van": ["VAN_PRETRAINED_CONFIG_ARCHIVE_MAP", "VanConfig"]}


try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						A__						=							[
						    "VAN_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "VanForImageClassification",
						    "VanModel",
						    "VanPreTrainedModel",
						]

if TYPE_CHECKING:
						from .configuration_van import VAN_PRETRAINED_CONFIG_ARCHIVE_MAP, VanConfig

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_van import (
												    VAN_PRETRAINED_MODEL_ARCHIVE_LIST,
												    VanForImageClassification,
												    VanModel,
												    VanPreTrainedModel,
												)

else:
						import sys

						A__						=							_LazyModule(__name__, globals()["__file__"], _import_structure)




