





'''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  _A (					__lowercase		):

		def 	lowercase__     (   self					:   int			)					->    Optional[Any]:


					"""simple docstring"""

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

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


					"""simple docstring"""

					import faiss

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


					"""simple docstring"""

					import faiss

					__snake_case					:      List[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"""  ,      batch_size=1_00  ,      metric_type=faiss.METRIC_INNER_PRODUCT  ,      )
					__snake_case      ,     __snake_case					:      Dict							      =     dset.get_nearest_examples("""vecs"""  ,      np.ones(5  ,      dtype=np.floataa			)			)
					self.assertEqual(examples["""filename"""][0]  ,      """my_name-train_29"""			)

		def 	lowercase__     (   self					:   Union[str, Any]			)					->    List[str]:


					"""simple docstring"""

					import faiss

					__snake_case					:      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=__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			)

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

		def 	lowercase__     (   self					:   List[Any]			)					->    Union[str, Any]:


					"""simple docstring"""

					__snake_case					:      List[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(__UpperCamelCase  ,      partial(dset.get_nearest_examples  ,      """vecs2"""  ,      np.ones(5  ,      dtype=np.floataa			)			)			)

		def 	lowercase__     (   self					:   List[Any]			)					->    Union[str, Any]:


					"""simple docstring"""

					from elasticsearch import Elasticsearch

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

								dset.add_elasticsearch_index("""filename"""  ,      es_client=__UpperCamelCase			)
								__snake_case      ,     __snake_case					:      List[str]							      =     dset.get_nearest_examples("""filename"""  ,      """my_name-train_29"""			)
								self.assertEqual(examples["""filename"""][0]  ,      """my_name-train_29"""			)





@require_faiss
class  _A (					__lowercase		):

		def 	lowercase__     (   self					:   Union[str, Any]			)					->    List[str]:


					"""simple docstring"""

					import faiss

					__snake_case					:      Any							      =     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
					__snake_case					:      Union[str, Any]							      =     np.zeros(5  ,      dtype=np.floataa			)
					__snake_case					:      int							      =     1
					__snake_case      ,     __snake_case					:      List[str]							      =     index.search(__UpperCamelCase			)
					self.assertRaises(__UpperCamelCase  ,      index.search  ,      query.reshape(-1  ,      1			)			)
					self.assertGreater(scores[0]  ,      0			)
					self.assertEqual(indices[0]  ,      1			)

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

		def 	lowercase__     (   self					:   Dict			)					->    str:


					"""simple docstring"""

					import faiss

					__snake_case					:      int							      =     FaissIndex(string_factory="""Flat"""			)
					index.add_vectors(np.eye(5  ,      dtype=np.floataa			)			)
					self.assertIsInstance(index.faiss_index  ,      faiss.IndexFlat			)
					__snake_case					:      str							      =     FaissIndex(string_factory="""LSH"""			)
					index.add_vectors(np.eye(5  ,      dtype=np.floataa			)			)
					self.assertIsInstance(index.faiss_index  ,      faiss.IndexLSH			)
					with self.assertRaises(__UpperCamelCase			):
								__snake_case					:      Optional[int]							      =     FaissIndex(string_factory="""Flat"""  ,      custom_index=faiss.IndexFlat(5			)			)

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


					"""simple docstring"""

					import faiss

					__snake_case					:      Optional[Any]							      =     faiss.IndexFlat(5			)
					__snake_case					:      List[str]							      =     FaissIndex(custom_index=__UpperCamelCase			)
					index.add_vectors(np.eye(5  ,      dtype=np.floataa			)			)
					self.assertIsInstance(index.faiss_index  ,      faiss.IndexFlat			)

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


					"""simple docstring"""

					import faiss

					__snake_case					:      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=__UpperCamelCase			) as tmp_file:
								index.save(tmp_file.name			)
								__snake_case					:      Optional[int]							      =     FaissIndex.load(tmp_file.name			)
					os.unlink(tmp_file.name			)

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







@require_faiss
def 					_a						(       _lowerCamelCase ) ->				List[Any]:



			"""simple docstring"""


			import faiss

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

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

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




@require_elasticsearch
class  _A (					__lowercase		):

		def 	lowercase__     (   self					:   Union[str, Any]			)					->    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:
								__snake_case					:      List[str]							      =     Elasticsearch()
								__snake_case					:      Union[str, Any]							      =     {"""acknowledged""": True}
								__snake_case					:      str							      =     ElasticSearchIndex(es_client=__UpperCamelCase			)
								mocked_bulk.return_value([(True, None)] * 3			)
								index.add_documents(["""foo""", """bar""", """foobar"""]			)

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

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

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

								# batched queries with timeout
								__snake_case					:      int							      =     ["""foo""", """bar""", """foobar"""]
								__snake_case					:      List[str]							      =     {"""hits""": {"""hits""": [{"""_score""": 1, """_id""": 1}]}}
								__snake_case      ,     __snake_case					:      Dict							      =     index.search_batch(__UpperCamelCase  ,      request_timeout=30			)
								__snake_case					:      Optional[Any]							      =     [scores[0] for scores in total_scores]
								__snake_case					:      Optional[int]							      =     [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_tokenizers_available,
    is_torch_available,
    is_vision_available,
)


lowercase   =	{
    '''configuration_layoutlmv2''': ['''LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''LayoutLMv2Config'''],
    '''processing_layoutlmv2''': ['''LayoutLMv2Processor'''],
    '''tokenization_layoutlmv2''': ['''LayoutLMv2Tokenizer'''],
}

try:
		if not is_tokenizers_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase   =	['''LayoutLMv2TokenizerFast''']

try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase   =	['''LayoutLMv2FeatureExtractor''']
		lowercase   =	['''LayoutLMv2ImageProcessor''']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase   =	[
		    '''LAYOUTLMV2_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''LayoutLMv2ForQuestionAnswering''',
		    '''LayoutLMv2ForSequenceClassification''',
		    '''LayoutLMv2ForTokenClassification''',
		    '''LayoutLMv2Layer''',
		    '''LayoutLMv2Model''',
		    '''LayoutLMv2PreTrainedModel''',
		]

if TYPE_CHECKING:
		from .configuration_layoutlmva import LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP, LayoutLMvaConfig
		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_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .feature_extraction_layoutlmva import LayoutLMvaFeatureExtractor, LayoutLMvaImageProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_layoutlmva import (
				    LAYOUTLMV2_PRETRAINED_MODEL_ARCHIVE_LIST,
				    LayoutLMvaForQuestionAnswering,
				    LayoutLMvaForSequenceClassification,
				    LayoutLMvaForTokenClassification,
				    LayoutLMvaLayer,
				    LayoutLMvaModel,
				    LayoutLMvaPreTrainedModel,
				)
else:
		import sys

		lowercase   =	_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





