





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


SCREAMING_SNAKE_CASE_						       =	pytest.mark.integration

@require_faiss
class 		UpperCamelCase__			(				lowerCAmelCase_       ):



     '''simple docstring'''

     def     SCREAMING_SNAKE_CASE__  (							self						:   Optional[int]	)					->		Tuple:




           '''simple docstring'''


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






     def     SCREAMING_SNAKE_CASE__  (							self						:   str	)					->		Tuple:




           '''simple docstring'''


           import faiss

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




           '''simple docstring'''


           import faiss

           SCREAMING_SNAKE_CASE		=						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						,)
           SCREAMING_SNAKE_CASE, SCREAMING_SNAKE_CASE		=						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						:   str	)					->		str:




           '''simple docstring'''


           import faiss

           SCREAMING_SNAKE_CASE		=						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	)

           SCREAMING_SNAKE_CASE, SCREAMING_SNAKE_CASE		=						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						:   Optional[int]	)					->		Dict:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						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     SCREAMING_SNAKE_CASE__  (							self						:   Any	)					->		List[Any]:




           '''simple docstring'''


           from elasticsearch import Elasticsearch

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

                 dset.add_elasticsearch_index("""filename"""						,es_client=lowerCamelCase__	)
                 SCREAMING_SNAKE_CASE, SCREAMING_SNAKE_CASE		=						dset.get_nearest_examples("""filename"""						,"""my_name-train_29"""	)
                 self.assertEqual(examples["""filename"""][0]						,"""my_name-train_29"""	)

@require_faiss
class 		UpperCamelCase__			(				lowerCAmelCase_       ):



     '''simple docstring'''

     def     SCREAMING_SNAKE_CASE__  (							self						:   Union[str, Any]	)					->		Tuple:




           '''simple docstring'''


           import faiss

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

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






     def     SCREAMING_SNAKE_CASE__  (							self						:   List[Any]	)					->		List[Any]:




           '''simple docstring'''


           import faiss

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






     def     SCREAMING_SNAKE_CASE__  (							self						:   List[Any]	)					->		int:




           '''simple docstring'''


           import faiss

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






     def     SCREAMING_SNAKE_CASE__  (							self						:   Dict	)					->		Optional[int]:




           '''simple docstring'''


           import faiss

           SCREAMING_SNAKE_CASE		=						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	)
                 SCREAMING_SNAKE_CASE		=						FaissIndex.load(tmp_file.name	)
           os.unlink(tmp_file.name	)

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



@require_faiss
def        __lowercase       (				_SCREAMING_SNAKE_CASE     )			->       Dict:


      '''simple docstring'''


      import faiss

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

      SCREAMING_SNAKE_CASE		=						"""index.faiss"""
      SCREAMING_SNAKE_CASE		=						F"""mock://{index_name}"""
      index.save(_SCREAMING_SNAKE_CASE			,						storage_options=mockfs.storage_options     )
      SCREAMING_SNAKE_CASE		=						FaissIndex.load(_SCREAMING_SNAKE_CASE			,						storage_options=mockfs.storage_options     )

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



@require_elasticsearch
class 		UpperCamelCase__			(				lowerCAmelCase_       ):



     '''simple docstring'''

     def     SCREAMING_SNAKE_CASE__  (							self						:   List[str]	)					->		Optional[int]:




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

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

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

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

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









from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


SCREAMING_SNAKE_CASE_						       =	{"""configuration_reformer""": ["""REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ReformerConfig"""]}

try:
      if not is_sentencepiece_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      SCREAMING_SNAKE_CASE_						       =	["""ReformerTokenizer"""]

try:
      if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      SCREAMING_SNAKE_CASE_						       =	["""ReformerTokenizerFast"""]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      SCREAMING_SNAKE_CASE_						       =	[
          """REFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """ReformerAttention""",
          """ReformerForMaskedLM""",
          """ReformerForQuestionAnswering""",
          """ReformerForSequenceClassification""",
          """ReformerLayer""",
          """ReformerModel""",
          """ReformerModelWithLMHead""",
          """ReformerPreTrainedModel""",
      ]


if TYPE_CHECKING:
      from .configuration_reformer import REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, ReformerConfig

      try:
            if not is_sentencepiece_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_reformer import ReformerTokenizer

      try:
            if not is_tokenizers_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_reformer_fast import ReformerTokenizerFast

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_reformer import (
                REFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
                ReformerAttention,
                ReformerForMaskedLM,
                ReformerForQuestionAnswering,
                ReformerForSequenceClassification,
                ReformerLayer,
                ReformerModel,
                ReformerModelWithLMHead,
                ReformerPreTrainedModel,
            )

else:
      import sys

      SCREAMING_SNAKE_CASE_						       =	_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


