


'''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__    					=      pytest.mark.integration




@require_faiss
class 			lowerCamelCase_   (	__a      ):






      def lowercase_							(					self				:    List[str] ):


          '''simple docstring'''


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






      def lowercase_							(					self				:    List[str] ):


          '''simple docstring'''


          import faiss

          UpperCAmelCase__			:		Dataset													=				self._create_dummy_dataset()
          UpperCAmelCase__			:		Any													=				dset.map(
              lambda _A						,						_A : {"vecs": i * np.ones(5						,						dtype=np.floataa )}						,						with_indices=_A						,						keep_in_memory=_A )
          UpperCAmelCase__			:		int													=				dset.add_faiss_index('''vecs'''						,						batch_size=100						,						metric_type=faiss.METRIC_INNER_PRODUCT )
          UpperCAmelCase__						,						UpperCAmelCase__			:		Tuple													=				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 lowercase_							(					self				:    Tuple ):


          '''simple docstring'''


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






      def lowercase_							(					self				:    Any ):


          '''simple docstring'''


          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=_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 )

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






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


          '''simple docstring'''


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






      def lowercase_							(					self				:    Tuple ):


          '''simple docstring'''


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

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




@require_faiss
class 			lowerCamelCase_   (	__a      ):






      def lowercase_							(					self				:    List[str] ):


          '''simple docstring'''


          import faiss

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

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






      def lowercase_							(					self				:    int ):


          '''simple docstring'''


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






      def lowercase_							(					self				:    List[Any] ):


          '''simple docstring'''


          import faiss

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






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


          '''simple docstring'''


          import faiss

          UpperCAmelCase__			:		Optional[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=_A ) as tmp_file:
              index.save(tmp_file.name )
              UpperCAmelCase__			:		Tuple													=				FaissIndex.load(tmp_file.name )
          os.unlink(tmp_file.name )

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





@require_faiss
def 					a__       (					lowerCAmelCase__						)    ->	Optional[Any]:
    import faiss

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

    UpperCAmelCase__			:		Union[str, Any]													=				'''index.faiss'''
    UpperCAmelCase__			:		Optional[Any]													=				F"""mock://{index_name}"""
    index.save(lowerCAmelCase__  ,					storage_options=mockfs.storage_options						)
    UpperCAmelCase__			:		List[Any]													=				FaissIndex.load(lowerCAmelCase__  ,					storage_options=mockfs.storage_options						)

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







@require_elasticsearch
class 			lowerCamelCase_   (	__a      ):






      def lowercase_							(					self				:    str ):


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

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

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

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

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




'''simple docstring'''
import os
from collections import namedtuple

import pytest

from datasets import ClassLabel, Features, Sequence, Value
from datasets.commands.test import TestCommand
from datasets.info import DatasetInfo, DatasetInfosDict


UpperCamelCase__    					=      namedtuple(
    '''_TestCommandArgs''',
    [
        '''dataset''',
        '''name''',
        '''cache_dir''',
        '''data_dir''',
        '''all_configs''',
        '''save_infos''',
        '''ignore_verifications''',
        '''force_redownload''',
        '''clear_cache''',
    ],
    defaults=[None, None, None, False, False, False, False, False],
)





def 					a__       (					lowerCAmelCase__  ,					lowerCAmelCase__						)    ->	Optional[int]:
    return (abs(source - target						) / target) < 0.0_1







@pytest.mark.integration
def 					a__       (					lowerCAmelCase__						)    ->	Optional[int]:
    UpperCAmelCase__			:		str													=				_TestCommandArgs(dataset=lowerCAmelCase__  ,					all_configs=lowerCAmelCase__  ,					save_infos=lowerCAmelCase__						)
    UpperCAmelCase__			:		Tuple													=				TestCommand(*lowerCAmelCase__						)
    test_command.run()
    UpperCAmelCase__			:		List[Any]													=				os.path.join(lowerCAmelCase__  ,					'''README.md'''						)
    assert os.path.exists(lowerCAmelCase__						)
    UpperCAmelCase__			:		List[str]													=				DatasetInfosDict.from_directory(lowerCAmelCase__						)
    UpperCAmelCase__			:		Any													=				DatasetInfosDict(
        {
            '''default''': DatasetInfo(
                features=Features(
                    {
                        '''tokens''': Sequence(Value('''string'''						)						),
                        '''ner_tags''': Sequence(
                            ClassLabel(names=['''O''', '''B-PER''', '''I-PER''', '''B-ORG''', '''I-ORG''', '''B-LOC''', '''I-LOC''']						)						),
                        '''langs''': Sequence(Value('''string'''						)						),
                        '''spans''': Sequence(Value('''string'''						)						),
                    }						)  ,					splits=[
                    {
                        '''name''': '''train''',
                        '''num_bytes''': 2_35_15_63,
                        '''num_examples''': 1_00_00,
                    },
                    {
                        '''name''': '''validation''',
                        '''num_bytes''': 23_84_18,
                        '''num_examples''': 10_00,
                    },
                ]  ,					download_size=3_94_06_80  ,					dataset_size=2_58_99_81  ,					)
        }						)
    assert dataset_infos.keys() == expected_dataset_infos.keys()
    for key in DatasetInfo._INCLUDED_INFO_IN_YAML:
        UpperCAmelCase__						,						UpperCAmelCase__			:		str													=				getattr(dataset_infos['''default''']  ,					lowerCAmelCase__						), getattr(expected_dataset_infos['''default''']  ,					lowerCAmelCase__						)
        if key == "num_bytes":
            assert is_apercent_close(lowerCAmelCase__  ,					lowerCAmelCase__						)
        elif key == "splits":
            assert list(lowerCAmelCase__						) == list(lowerCAmelCase__						)
            for split in result:
                assert result[split].name == expected[split].name
                assert result[split].num_examples == expected[split].num_examples
                assert is_apercent_close(result[split].num_bytes  ,					expected[split].num_bytes						)
        else:
            result == expected
