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 SCREAMING_SNAKE_CASE_						(	__lowerCAmelCase						):







   def 		lowerCamelCase_     (			self		:		List[str]							):





    """simple docstring"""


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







   def 		lowerCamelCase_     (			self		:		Dict							):





    """simple docstring"""


    import faiss

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





    """simple docstring"""


    import faiss

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







   def 		lowerCamelCase_     (			self		:		List[Any]							):





    """simple docstring"""


    import faiss

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







   def 		lowerCamelCase_     (			self		:		str							):





    """simple docstring"""


    UpperCamelCase          =	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 		lowerCamelCase_     (			self		:		List[str]							):





    """simple docstring"""


    from elasticsearch import Elasticsearch

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

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





@require_faiss
class SCREAMING_SNAKE_CASE_						(	__lowerCAmelCase						):







   def 		lowerCamelCase_     (			self		:		Optional[int]							):





    """simple docstring"""


    import faiss

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







   def 		lowerCamelCase_     (			self		:		Optional[Any]							):





    """simple docstring"""


    import faiss

    UpperCamelCase          =	FaissIndex(string_factory="""Flat"""							)
    index.add_vectors(np.eye(5					,					dtype=np.floataa							)							)
    self.assertIsInstance(index.faiss_index					,					faiss.IndexFlat							)
    UpperCamelCase          =	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          =	FaissIndex(string_factory="""Flat"""					,					custom_index=faiss.IndexFlat(5							)							)







   def 		lowerCamelCase_     (			self		:		Dict							):





    """simple docstring"""


    import faiss

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







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





    """simple docstring"""


    import faiss

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

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





@require_faiss
def        lowercase(     UpperCamelCase_    )						->     Optional[Any]:







 '''simple docstring'''
 import faiss

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

 UpperCamelCase          =	"""index.faiss"""
 UpperCamelCase          =	f"""mock://{index_name}"""
 index.save(lowercase_				, storage_options=mockfs.storage_options    )
 UpperCamelCase          =	FaissIndex.load(lowercase_				, storage_options=mockfs.storage_options    )

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


@require_elasticsearch
class SCREAMING_SNAKE_CASE_						(	__lowerCAmelCase						):







   def 		lowerCamelCase_     (			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          =	Elasticsearch()
     UpperCamelCase          =	{"""acknowledged""": True}
     UpperCamelCase          =	ElasticSearchIndex(es_client=A__							)
     mocked_bulk.return_value([(True, None)] * 3							)
     index.add_documents(["""foo""", """bar""", """foobar"""]							)

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

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

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

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



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


A_       : Optional[int]         =			{'configuration_ibert': ['IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'IBertConfig', 'IBertOnnxConfig']}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A_       : str         =			[
	    'IBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'IBertForMaskedLM',
	    'IBertForMultipleChoice',
	    'IBertForQuestionAnswering',
	    'IBertForSequenceClassification',
	    'IBertForTokenClassification',
	    'IBertModel',
	    'IBertPreTrainedModel',
	]

if TYPE_CHECKING:
	from .configuration_ibert import IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, IBertConfig, IBertOnnxConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_ibert import (
		    IBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    IBertForMaskedLM,
		    IBertForMultipleChoice,
		    IBertForQuestionAnswering,
		    IBertForSequenceClassification,
		    IBertForTokenClassification,
		    IBertModel,
		    IBertPreTrainedModel,
		)

else:
	import sys

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



