"""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


lowerCAmelCase__  :  Dict						     =	pytest.mark.integration
@require_faiss
class 				snake_case       ( __UpperCAmelCase				):




					"""simple docstring"""

					def 		__lowerCAmelCase						(				self   :	Union[str, Any]			):
									UpperCAmelCase__             =							Dataset.from_dict({'filename': ['my_name-train' + '_' + str(lowerCamelCase__			) for x in np.arange(30			).tolist()]}			)
									return dset







					def 		__lowerCAmelCase						(				self   :	List[Any]			):
									import faiss

									UpperCAmelCase__             =							self._create_dummy_dataset()
									UpperCAmelCase__             =							dset.map(
									    lambda lowerCamelCase__    ,lowerCamelCase__			: {"vecs": i * np.ones(5    ,dtype=np.floataa			)}    ,with_indices=lowerCamelCase__    ,keep_in_memory=lowerCamelCase__			)
									UpperCAmelCase__             =							dset.add_faiss_index('vecs'    ,batch_size=100    ,metric_type=faiss.METRIC_INNER_PRODUCT			)
									UpperCAmelCase__      ,	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   :	List[str]			):
									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__      ,	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]			):
									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=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			)

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







					def 		__lowerCAmelCase						(				self   :	Optional[Any]			):
									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(lowerCamelCase__    ,partial(dset.get_nearest_examples    ,'vecs2'    ,np.ones(5    ,dtype=np.floataa			)			)			)







					def 		__lowerCAmelCase						(				self   :	str			):
									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=lowerCamelCase__			)
													UpperCAmelCase__      ,	UpperCAmelCase__             =							dset.get_nearest_examples('filename'    ,'my_name-train_29'			)
													self.assertEqual(examples['filename'][0]    ,'my_name-train_29'			)






@require_faiss
class 				snake_case       ( __UpperCAmelCase				):




					"""simple docstring"""

					def 		__lowerCAmelCase						(				self   :	List[Any]			):
									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__      ,	UpperCAmelCase__             =							index.search(lowerCamelCase__			)
									self.assertRaises(lowerCamelCase__    ,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__      ,	UpperCAmelCase__             =							index.search_batch(lowerCamelCase__			)
									self.assertRaises(lowerCamelCase__    ,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(lowerCamelCase__			)    ,0			)
									self.assertListEqual([4, 3, 2, 1, 0]    ,lowerCamelCase__			)







					def 		__lowerCAmelCase						(				self   :	Dict			):
									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(lowerCamelCase__			):
													UpperCAmelCase__             =							FaissIndex(string_factory='Flat'    ,custom_index=faiss.IndexFlat(5			)			)







					def 		__lowerCAmelCase						(				self   :	str			):
									import faiss

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







					def 		__lowerCAmelCase						(				self   :	List[Any]			):
									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=lowerCamelCase__			) 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__      ,	UpperCAmelCase__             =							index.search(lowerCamelCase__			)
									self.assertGreater(scores[0]    ,0			)
									self.assertEqual(indices[0]    ,1			)






@require_faiss
def   a_						(					lowerCamelCase       ):
				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(lowerCamelCase					,			storage_options=mockfs.storage_options       )
				UpperCAmelCase__             =							FaissIndex.load(lowerCamelCase					,			storage_options=mockfs.storage_options       )

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







@require_elasticsearch
class 				snake_case       ( __UpperCAmelCase				):




					"""simple docstring"""

					def 		__lowerCAmelCase						(				self   :	Any			):
									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=lowerCamelCase__			)
													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__      ,	UpperCAmelCase__             =							index.search(lowerCamelCase__			)
													self.assertEqual(scores[0]    ,1			)
													self.assertEqual(indices[0]    ,0			)

													# single query with timeout
													UpperCAmelCase__             =							'foo'
													UpperCAmelCase__             =							{'hits': {'hits': [{'_score': 1, '_id': 0}]}}
													UpperCAmelCase__      ,	UpperCAmelCase__             =							index.search(lowerCamelCase__    ,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__      ,	UpperCAmelCase__             =							index.search_batch(lowerCamelCase__			)
													UpperCAmelCase__             =							[scores[0] for scores in total_scores]
													UpperCAmelCase__             =							[indices[0] for indices in total_indices]
													self.assertGreater(np.min(lowerCamelCase__			)    ,0			)
													self.assertListEqual([1, 1, 1]    ,lowerCamelCase__			)

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




"""simple docstring"""






import os

import numpy
import onnx



def   a_						(					lowerCamelCase					,			lowerCamelCase       ):
				UpperCAmelCase__             =							a.name
				UpperCAmelCase__             =							b.name

				UpperCAmelCase__             =							''
				UpperCAmelCase__             =							''

				UpperCAmelCase__             =							a == b

				UpperCAmelCase__             =							name_a
				UpperCAmelCase__             =							name_b

				return res



def   a_						(					lowerCamelCase					,			lowerCamelCase					,			lowerCamelCase       ):
				for i, input_name in enumerate(node_proto.input       ):
								if input_name == name:
												node_proto.input.insert(lowerCamelCase					,			lowerCamelCase       )
												node_proto.input.pop(i + 1       )

				if node_proto.op_type == "If":
								_graph_replace_input_with(node_proto.attribute[0].g					,			lowerCamelCase					,			lowerCamelCase       )
								_graph_replace_input_with(node_proto.attribute[1].g					,			lowerCamelCase					,			lowerCamelCase       )
				if node_proto.op_type == "Loop":
								_graph_replace_input_with(node_proto.attribute[0].g					,			lowerCamelCase					,			lowerCamelCase       )



def   a_						(					lowerCamelCase					,			lowerCamelCase					,			lowerCamelCase       ):
				for n in graph_proto.node:
								_node_replace_input_with(lowerCamelCase					,			lowerCamelCase					,			lowerCamelCase       )



def   a_						(					lowerCamelCase					,			lowerCamelCase					,			lowerCamelCase       ):
				UpperCAmelCase__             =							list(model.graph.initializer       )
				UpperCAmelCase__             =							list(model_without_ext.graph.initializer       )
				for i, ref_i in ind_to_replace:
								assert inits_with_data[i].name == inits[i].name
								assert inits_with_data[ref_i].name == inits[ref_i].name
								assert i > ref_i

								UpperCAmelCase__             =							inits[i].name
								UpperCAmelCase__             =							inits[ref_i].name

								model_without_ext.graph.initializer.remove(inits[i]       )

								# for n in model.graph.node:
								_graph_replace_input_with(model_without_ext.graph					,			lowerCamelCase					,			lowerCamelCase       )







def   a_						(					lowerCamelCase       ):
				UpperCAmelCase__             =							os.path.dirname(lowerCamelCase       )
				UpperCAmelCase__             =							os.path.basename(lowerCamelCase       )

				UpperCAmelCase__             =							onnx.load(os.path.join(lowerCamelCase					,			lowerCamelCase       )       )

				UpperCAmelCase__             =							list(model.graph.initializer       )

				UpperCAmelCase__             =							set()
				UpperCAmelCase__             =							{}
				UpperCAmelCase__             =							[]

				UpperCAmelCase__             =							0

				for i in range(len(lowerCamelCase       )       ):
								if i in dup_set:
												continue

								for j in range(i + 1					,			len(lowerCamelCase       )       ):
												if j in dup_set:
																continue
												if _is_equal_tensor_proto(inits[i]					,			inits[j]       ):
																dup_set.add(lowerCamelCase       )
																dup_set.add(lowerCamelCase       )

																UpperCAmelCase__             =							inits[j].data_type
																UpperCAmelCase__             =							numpy.prod(inits[j].dims       )
																if dtype == 1:
																				mem_size *= 4
																elif dtype == 6:
																				mem_size *= 4
																elif dtype == 7 or dtype == 1_1:
																				mem_size *= 8
																else:
																				print('unexpected data type: '					,			lowerCamelCase       )
																total_reduced_size += mem_size

																UpperCAmelCase__             =							inits[i].name
																UpperCAmelCase__             =							inits[j].name

																if name_i in dup_map:
																				dup_map[name_i].append(lowerCamelCase       )
																else:
																				UpperCAmelCase__             =							[name_j]
																ind_to_replace.append((j, i)       )

				print('total reduced size: '					,			total_reduced_size / 1_0_2_4 / 1_0_2_4 / 1_0_2_4					,			'GB'       )

				UpperCAmelCase__             =							sorted(lowerCamelCase       )
				_remove_dup_initializers_from_model(lowerCamelCase					,			lowerCamelCase					,			lowerCamelCase       )

				UpperCAmelCase__             =							'optimized_' + model_file_name
				UpperCAmelCase__             =							os.path.join(lowerCamelCase					,			lowerCamelCase       )
				onnx.save(lowerCamelCase					,			lowerCamelCase       )

				return new_model



