




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


_snake_case										=       pytest.mark.integration







@require_faiss
class 						lowercase							(   UpperCamelCase__		):

     def 					a__	(  self				)						->							Union[str, Any]:
           _A							:     List[str]			=						Dataset.from_dict({"""filename""": ["""my_name-train""" + """_""" + str(snake_case__				) for x in np.arange(30				).tolist()]}				)
           return dset

     def 					a__	(  self				)						->							Optional[Any]:
           import faiss

           _A							:     Dataset			=						self._create_dummy_dataset()
           _A							:     Union[str, Any]			=						dset.map(
               lambda _a		,     _a				: {"vecs": i * np.ones(5		,     dtype=np.floataa				)}		,     with_indices=snake_case__		,     keep_in_memory=snake_case__				)
           _A							:     Union[str, Any]			=						dset.add_faiss_index("""vecs"""		,     batch_size=100		,     metric_type=faiss.METRIC_INNER_PRODUCT				)
           _A							:     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 					a__	(  self				)						->							List[Any]:
           import faiss

           _A							:     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		,     )
           _A							:     Optional[Any]			=						dset.get_nearest_examples("""vecs"""		,     np.ones(5		,     dtype=np.floataa				)				)
           self.assertEqual(examples["""filename"""][0]		,     """my_name-train_29"""				)

     def 					a__	(  self				)						->							Optional[Any]:
           import faiss

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

     def 					a__	(  self				)						->							Tuple:
           _A							:     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(snake_case__		,     partial(dset.get_nearest_examples		,     """vecs2"""		,     np.ones(5		,     dtype=np.floataa				)				)				)



     def 					a__	(  self				)						->							Union[str, Any]:
           from elasticsearch import Elasticsearch

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

                 dset.add_elasticsearch_index("""filename"""		,     es_client=snake_case__				)
                 _A							:     int			=						dset.get_nearest_examples("""filename"""		,     """my_name-train_29"""				)
                 self.assertEqual(examples["""filename"""][0]		,     """my_name-train_29"""				)







@require_faiss
class 						lowercase							(   UpperCamelCase__		):

     def 					a__	(  self				)						->							Dict:
           import faiss

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

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

     def 					a__	(  self				)						->							Tuple:
           import faiss

           _A							:     Dict			=						FaissIndex(string_factory="""Flat"""				)
           index.add_vectors(np.eye(5		,     dtype=np.floataa				)				)
           self.assertIsInstance(index.faiss_index		,     faiss.IndexFlat				)
           _A							:     Union[str, Any]			=						FaissIndex(string_factory="""LSH"""				)
           index.add_vectors(np.eye(5		,     dtype=np.floataa				)				)
           self.assertIsInstance(index.faiss_index		,     faiss.IndexLSH				)
           with self.assertRaises(snake_case__				):
                 _A							:     List[Any]			=						FaissIndex(string_factory="""Flat"""		,     custom_index=faiss.IndexFlat(5				)				)

     def 					a__	(  self				)						->							Any:
           import faiss

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



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

           _A							:     str			=						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=snake_case__				) as tmp_file:
                 index.save(tmp_file.name				)
                 _A							:     int			=						FaissIndex.load(tmp_file.name				)
           os.unlink(tmp_file.name				)

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







@require_faiss
def 				lowerCAmelCase_	(     snake_case_     ):
      import faiss

      _A							:     List[Any]			=						FaissIndex(metric_type=faiss.METRIC_INNER_PRODUCT     )
      index.add_vectors(np.eye(5,dtype=np.floataa     )     )

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

      _A							:     Optional[int]			=						np.zeros(5,dtype=np.floataa     )
      _A							:     Any			=						1
      _A							:     Optional[int]			=						index.search(snake_case_     )
      assert scores[0] > 0
      assert indices[0] == 1







@require_elasticsearch
class 						lowercase							(   UpperCamelCase__		):

     def 					a__	(  self				)						->							Optional[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							:     List[str]			=						Elasticsearch()
                 _A							:     Dict			=						{"acknowledged": True}
                 _A							:     Optional[int]			=						ElasticSearchIndex(es_client=snake_case__				)
                 mocked_bulk.return_value([(True, None)] * 3				)
                 index.add_documents(["""foo""", """bar""", """foobar"""]				)

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

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

                 # batched queries
                 _A							:     Any			=						["foo", "bar", "foobar"]
                 _A							:     Optional[int]			=						{"hits": {"hits": [{"_score": 1, "_id": 1}]}}
                 _A							:     Any			=						index.search_batch(snake_case__				)
                 _A							:     Tuple			=						[scores[0] for scores in total_scores]
                 _A							:     Dict			=						[indices[0] for indices in total_indices]
                 self.assertGreater(np.min(snake_case__				)		,     0				)
                 self.assertListEqual([1, 1, 1]		,     snake_case__				)

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





"""simple docstring"""







lowerCAmelCase__      				=   [
    '''Audio''',
    '''Array2D''',
    '''Array3D''',
    '''Array4D''',
    '''Array5D''',
    '''ClassLabel''',
    '''Features''',
    '''Sequence''',
    '''Value''',
    '''Image''',
    '''Translation''',
    '''TranslationVariableLanguages''',
]
from .audio import Audio
from .features import ArrayaD, ArrayaD, ArrayaD, ArrayaD, ClassLabel, Features, Sequence, Value
from .image import Image
from .translation import Translation, TranslationVariableLanguages





