



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				:		Dict										=pytest.mark.integration



@require_faiss
class        lowerCamelCase__			(							_UpperCamelCase):




		'''simple docstring'''



		def 		lowerCAmelCase__      (self )     ->			Optional[Any]:

						"""simple docstring"""






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



		def 		lowerCAmelCase__      (self )     ->			Tuple:

						"""simple docstring"""






						import faiss

						lowerCAmelCase__     :				Optional[int]												=     self._create_dummy_dataset()
						lowerCAmelCase__     :				Any												=     dset.map(
						    lambda __lowerCamelCase		,__lowerCamelCase : {"vecs": i * np.ones(5		,dtype=np.floataa )}		,with_indices=lowerCAmelCase_		,keep_in_memory=lowerCAmelCase_ )
						lowerCAmelCase__     :				Optional[int]												=     dset.add_faiss_index('''vecs'''		,batch_size=1_00		,metric_type=faiss.METRIC_INNER_PRODUCT )
						lowerCAmelCase__						,		lowerCAmelCase__     :				Optional[int]												=     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 		lowerCAmelCase__      (self )     ->			str:

						"""simple docstring"""






						import faiss

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



		def 		lowerCAmelCase__      (self )     ->			Optional[Any]:

						"""simple docstring"""






						import faiss

						lowerCAmelCase__     :				Dict												=     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 )

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



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

						"""simple docstring"""






						lowerCAmelCase__     :				Union[str, Any]												=     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 		lowerCAmelCase__      (self )     ->			Tuple:

						"""simple docstring"""






						from elasticsearch import Elasticsearch

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

										dset.add_elasticsearch_index('''filename'''		,es_client=lowerCAmelCase_ )
										lowerCAmelCase__						,		lowerCAmelCase__     :				Tuple												=     dset.get_nearest_examples('''filename'''		,'''my_name-train_29''' )
										self.assertEqual(examples['''filename'''][0]		,'''my_name-train_29''' )



@require_faiss
class        lowerCamelCase__			(							_UpperCamelCase):




		'''simple docstring'''



		def 		lowerCAmelCase__      (self )     ->			int:

						"""simple docstring"""






						import faiss

						lowerCAmelCase__     :				Dict												=     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
						lowerCAmelCase__     :				Optional[Any]												=     np.zeros(5		,dtype=np.floataa )
						lowerCAmelCase__     :				Any												=     1
						lowerCAmelCase__						,		lowerCAmelCase__     :				List[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
						lowerCAmelCase__     :				Optional[Any]												=     np.eye(5		,dtype=np.floataa )[::-1]
						lowerCAmelCase__						,		lowerCAmelCase__     :				Any												=     index.search_batch(lowerCAmelCase_ )
						self.assertRaises(lowerCAmelCase_		,index.search_batch		,queries[0] )
						lowerCAmelCase__     :				str												=     [scores[0] for scores in total_scores]
						lowerCAmelCase__     :				Tuple												=     [indices[0] for indices in total_indices]
						self.assertGreater(np.min(lowerCAmelCase_ )		,0 )
						self.assertListEqual([4, 3, 2, 1, 0]		,lowerCAmelCase_ )



		def 		lowerCAmelCase__      (self )     ->			List[str]:

						"""simple docstring"""






						import faiss

						lowerCAmelCase__     :				Tuple												=     FaissIndex(string_factory='''Flat''' )
						index.add_vectors(np.eye(5		,dtype=np.floataa ) )
						self.assertIsInstance(index.faiss_index		,faiss.IndexFlat )
						lowerCAmelCase__     :				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(lowerCAmelCase_ ):
										lowerCAmelCase__     :				List[Any]												=     FaissIndex(string_factory='''Flat'''		,custom_index=faiss.IndexFlat(5 ) )



		def 		lowerCAmelCase__      (self )     ->			Dict:

						"""simple docstring"""






						import faiss

						lowerCAmelCase__     :				str												=     faiss.IndexFlat(5 )
						lowerCAmelCase__     :				Dict												=     FaissIndex(custom_index=lowerCAmelCase_ )
						index.add_vectors(np.eye(5		,dtype=np.floataa ) )
						self.assertIsInstance(index.faiss_index		,faiss.IndexFlat )



		def 		lowerCAmelCase__      (self )     ->			Any:

						"""simple docstring"""






						import faiss

						lowerCAmelCase__     :				Tuple												=     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 )
										lowerCAmelCase__     :				List[str]												=     FaissIndex.load(tmp_file.name )
						os.unlink(tmp_file.name )

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






@require_faiss
def 	lowerCAmelCase__		(    lowerCamelCase_		:		Union[str, Any]):





				'''simple docstring'''

				import faiss

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

				lowerCAmelCase__     :				Any												=     '''index.faiss'''
				lowerCAmelCase__     :				Tuple												=     f"""mock://{index_name}"""
				index.save(lowerCAmelCase_       ,storage_options=mockfs.storage_options)
				lowerCAmelCase__     :				List[Any]												=     FaissIndex.load(lowerCAmelCase_       ,storage_options=mockfs.storage_options)

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



@require_elasticsearch
class        lowerCamelCase__			(							_UpperCamelCase):




		'''simple docstring'''



		def 		lowerCAmelCase__      (self )     ->			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:
										lowerCAmelCase__     :				Any												=     Elasticsearch()
										lowerCAmelCase__     :				Union[str, Any]												=     {'''acknowledged''': True}
										lowerCAmelCase__     :				Optional[Any]												=     ElasticSearchIndex(es_client=lowerCAmelCase_ )
										mocked_bulk.return_value([(True, None)] * 3 )
										index.add_documents(['''foo''', '''bar''', '''foobar'''] )

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

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

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

										# batched queries with timeout
										lowerCAmelCase__     :				Any												=     ['''foo''', '''bar''', '''foobar''']
										lowerCAmelCase__     :				Tuple												=     {'''hits''': {'''hits''': [{'''_score''': 1, '''_id''': 1}]}}
										lowerCAmelCase__						,		lowerCAmelCase__     :				Any												=     index.search_batch(lowerCAmelCase_		,request_timeout=30 )
										lowerCAmelCase__     :				Dict												=     [scores[0] for scores in total_scores]
										lowerCAmelCase__     :				Any												=     [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_tf_available,
    is_tokenizers_available,
    is_torch_available,
    is_vision_available,
)


_snake_case  :    Union[str, Any]						    =  {
    'configuration_layoutlmv3': [
        'LAYOUTLMV3_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'LayoutLMv3Config',
        'LayoutLMv3OnnxConfig',
    ],
    'processing_layoutlmv3': ['LayoutLMv3Processor'],
    'tokenization_layoutlmv3': ['LayoutLMv3Tokenizer'],
}

try:
     if not is_tokenizers_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _snake_case  :    Union[str, Any]						    =  ['LayoutLMv3TokenizerFast']

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _snake_case  :    List[str]						    =  [
         'LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST',
         'LayoutLMv3ForQuestionAnswering',
         'LayoutLMv3ForSequenceClassification',
         'LayoutLMv3ForTokenClassification',
         'LayoutLMv3Model',
         'LayoutLMv3PreTrainedModel',
     ]

try:
     if not is_tf_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _snake_case  :    Optional[Any]						    =  [
         'TF_LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST',
         'TFLayoutLMv3ForQuestionAnswering',
         'TFLayoutLMv3ForSequenceClassification',
         'TFLayoutLMv3ForTokenClassification',
         'TFLayoutLMv3Model',
         'TFLayoutLMv3PreTrainedModel',
     ]

try:
     if not is_vision_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _snake_case  :    Tuple						    =  ['LayoutLMv3FeatureExtractor']
     _snake_case  :    str						    =  ['LayoutLMv3ImageProcessor']


if TYPE_CHECKING:
     from .configuration_layoutlmva import (
         LAYOUTLMV3_PRETRAINED_CONFIG_ARCHIVE_MAP,
         LayoutLMvaConfig,
         LayoutLMvaOnnxConfig,
     )
     from .processing_layoutlmva import LayoutLMvaProcessor
     from .tokenization_layoutlmva import LayoutLMvaTokenizer

     try:
          if not is_tokenizers_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_layoutlmva_fast import LayoutLMvaTokenizerFast

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_layoutlmva import (
              LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST,
              LayoutLMvaForQuestionAnswering,
              LayoutLMvaForSequenceClassification,
              LayoutLMvaForTokenClassification,
              LayoutLMvaModel,
              LayoutLMvaPreTrainedModel,
          )

     try:
          if not is_tf_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_tf_layoutlmva import (
              TF_LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST,
              TFLayoutLMvaForQuestionAnswering,
              TFLayoutLMvaForSequenceClassification,
              TFLayoutLMvaForTokenClassification,
              TFLayoutLMvaModel,
              TFLayoutLMvaPreTrainedModel,
          )

     try:
          if not is_vision_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .feature_extraction_layoutlmva import LayoutLMvaFeatureExtractor
          from .image_processing_layoutlmva import LayoutLMvaImageProcessor

else:
     import sys

     _snake_case  :    Any						    =  _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)

