



'''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							:Optional[Any]				    =					pytest.mark.integration







@require_faiss
class 	_lowerCAmelCase							(			lowerCAmelCase_ ):


	def     _a	(self							):
				A_	:						List[Any]	=     Dataset.from_dict({"""filename""": ["""my_name-train""" + """_""" + str(__lowerCAmelCase							) for x in np.arange(30							).tolist()]}							)
				return dset


	def     _a	(self							):
				import faiss

				A_	:						List[Any]	=     self._create_dummy_dataset()
				A_	:						int	=     dset.map(
				    lambda lowercase       ,      lowercase							: {"vecs": i * np.ones(5       ,      dtype=np.floataa							)}       ,      with_indices=__lowerCAmelCase       ,      keep_in_memory=__lowerCAmelCase							)
				A_	:						Union[str, Any]	=     dset.add_faiss_index("""vecs"""       ,      batch_size=100       ,      metric_type=faiss.METRIC_INNER_PRODUCT							)
				A_,    A_	:						List[Any]	=     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     _a	(self							):
				import faiss

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


	def     _a	(self							):
				import faiss

				A_	:						Optional[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"""       ,      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							)

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


	def     _a	(self							):
				A_	:						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"""							)
				dset.drop_index("""vecs"""							)
				self.assertRaises(__lowerCAmelCase       ,      partial(dset.get_nearest_examples       ,      """vecs2"""       ,      np.ones(5       ,      dtype=np.floataa							)							)							)


	def     _a	(self							):
				from elasticsearch import Elasticsearch

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

							dset.add_elasticsearch_index("""filename"""       ,      es_client=__lowerCAmelCase							)
							A_,    A_	:						Tuple	=     dset.get_nearest_examples("""filename"""       ,      """my_name-train_29"""							)
							self.assertEqual(examples["""filename"""][0]       ,      """my_name-train_29"""							)







@require_faiss
class 	_lowerCAmelCase							(			lowerCAmelCase_ ):


	def     _a	(self							):
				import faiss

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

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


	def     _a	(self							):
				import faiss

				A_	:						Tuple	=     FaissIndex(string_factory="""Flat"""							)
				index.add_vectors(np.eye(5       ,      dtype=np.floataa							)							)
				self.assertIsInstance(index.faiss_index       ,      faiss.IndexFlat							)
				A_	:						Dict	=     FaissIndex(string_factory="""LSH"""							)
				index.add_vectors(np.eye(5       ,      dtype=np.floataa							)							)
				self.assertIsInstance(index.faiss_index       ,      faiss.IndexLSH							)
				with self.assertRaises(__lowerCAmelCase							):
							A_	:						str	=     FaissIndex(string_factory="""Flat"""       ,      custom_index=faiss.IndexFlat(5							)							)


	def     _a	(self							):
				import faiss

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


	def     _a	(self							):
				import faiss

				A_	:						Any	=     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							)
							A_	:						Optional[int]	=     FaissIndex.load(tmp_file.name							)
				os.unlink(tmp_file.name							)

				A_	:						Dict	=     np.zeros(5       ,      dtype=np.floataa							)
				A_	:						Optional[Any]	=     1
				A_,    A_	:						Optional[int]	=     index.search(__lowerCAmelCase							)
				self.assertGreater(scores[0]       ,      0							)
				self.assertEqual(indices[0]       ,      1							)






@require_faiss
def 	a			( lowerCamelCase__    ):
			'''simple docstring'''





			import faiss

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

			A_	:						int	=     """index.faiss"""
			A_	:						Optional[int]	=     f'mock://{index_name}'
			index.save(lowerCamelCase__						,      storage_options=mockfs.storage_options    )
			A_	:						Tuple	=     FaissIndex.load(lowerCamelCase__						,      storage_options=mockfs.storage_options    )

			A_	:						List[Any]	=     np.zeros(5						,      dtype=np.floataa    )
			A_	:						List[str]	=     1
			A_,    A_	:						Optional[Any]	=     index.search(lowerCamelCase__    )
			assert scores[0] > 0
			assert indices[0] == 1







@require_elasticsearch
class 	_lowerCAmelCase							(			lowerCAmelCase_ ):


	def     _a	(self							):
				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:
							A_	:						List[str]	=     Elasticsearch()
							A_	:						int	=     {"""acknowledged""": True}
							A_	:						List[str]	=     ElasticSearchIndex(es_client=__lowerCAmelCase							)
							mocked_bulk.return_value([(True, None)] * 3							)
							index.add_documents(["""foo""", """bar""", """foobar"""]							)

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

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

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

							# batched queries with timeout
							A_	:						Union[str, Any]	=     ["""foo""", """bar""", """foobar"""]
							A_	:						Union[str, Any]	=     {"""hits""": {"""hits""": [{"""_score""": 1, """_id""": 1}]}}
							A_,    A_	:						Optional[Any]	=     index.search_batch(__lowerCAmelCase       ,      request_timeout=30							)
							A_	:						Optional[int]	=     [scores[0] for scores in total_scores]
							A_	:						Optional[int]	=     [indices[0] for indices in total_indices]
							self.assertGreater(np.min(__lowerCAmelCase							)       ,      0							)
							self.assertListEqual([1, 1, 1]       ,      __lowerCAmelCase							)
"""simple docstring"""


UpperCAmelCase__     						=  [
    [0, 1_6, 1_3, 0, 0, 0],
    [0, 0, 1_0, 1_2, 0, 0],
    [0, 4, 0, 0, 1_4, 0],
    [0, 0, 9, 0, 0, 2_0],
    [0, 0, 0, 7, 0, 4],
    [0, 0, 0, 0, 0, 0],
]






def 			__UpperCAmelCase    (	lowercase      ,lowercase      ,lowercase      ,lowercase						):







  """simple docstring"""
  # Return True if there is node that has not iterated.
  _UpperCAmelCase         =					[False] * len(lowercase						)
  _UpperCAmelCase         =					[s]
  _UpperCAmelCase         =					True

  while queue:
    _UpperCAmelCase         =					queue.pop(0						)
    for ind in range(len(graph[u]						)						):
      if visited[ind] is False and graph[u][ind] > 0:
        queue.append(lowercase						)
        _UpperCAmelCase         =					True
        _UpperCAmelCase         =					u

  return visited[t]






def 			__UpperCAmelCase    (	lowercase      ,lowercase      ,lowercase						):







  """simple docstring"""
  _UpperCAmelCase         =					[-1] * (len(lowercase						))
  _UpperCAmelCase         =					0
  _UpperCAmelCase         =					[]
  _UpperCAmelCase         =					[i[:] for i in graph]  # Record original cut, copy.
  while bfs(lowercase      ,lowercase      ,lowercase      ,lowercase						):
    _UpperCAmelCase         =					float("""Inf"""						)
    _UpperCAmelCase         =					sink

    while s != source:
      # Find the minimum value in select path
      _UpperCAmelCase         =					min(lowercase      ,graph[parent[s]][s]						)
      _UpperCAmelCase         =					parent[s]

    max_flow += path_flow
    _UpperCAmelCase         =					sink

    while v != source:
      _UpperCAmelCase         =					parent[v]
      graph[u][v] -= path_flow
      graph[v][u] += path_flow
      _UpperCAmelCase         =					parent[v]

  for i in range(len(lowercase						)						):
    for j in range(len(graph[0]						)						):
      if graph[i][j] == 0 and temp[i][j] > 0:
        res.append((i, j)						)

  return res


if __name__ == "__main__":
    print(mincut(test_graph, source=0, sink=5))
