




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_					    = pytest.mark.integration






@require_faiss
class  _lowerCAmelCase     (  _lowercase	):

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

      def 	__magic_name__(   self		):
        import faiss

        lowerCAmelCase__				:  Dataset		       =     self._create_dummy_dataset()
        lowerCAmelCase__				:  List[str]		       =     dset.map(
            lambda __UpperCAmelCase      ,				__UpperCAmelCase		: {"vecs": i * np.ones(5      ,				dtype=np.floataa		)}      ,				with_indices=__UpperCAmelCase      ,				keep_in_memory=__UpperCAmelCase		)
        lowerCAmelCase__				:  List[Any]		       =     dset.add_faiss_index('''vecs'''      ,				batch_size=100      ,				metric_type=faiss.METRIC_INNER_PRODUCT		)
        lowerCAmelCase__       ,			lowerCAmelCase__				:  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 	__magic_name__(   self		):
        import faiss

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

      def 	__magic_name__(   self		):
        import faiss

        lowerCAmelCase__				:  Dataset		       =     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		)

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

      def 	__magic_name__(   self		):
        lowerCAmelCase__				:  Dataset		       =     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 	__magic_name__(   self		):
        from elasticsearch import Elasticsearch

        lowerCAmelCase__				:  Dataset		       =     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__				:  str		       =     {'''acknowledged''': True}
          mocked_bulk.return_value([(True, None)] * 30		)
          lowerCAmelCase__				:  List[Any]		       =     {'''hits''': {'''hits''': [{'''_score''': 1, '''_id''': 29}]}}
          lowerCAmelCase__				:  Optional[int]		       =     Elasticsearch()

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






@require_faiss
class  _lowerCAmelCase     (  _lowercase	):

      def 	__magic_name__(   self		):
        import faiss

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

      def 	__magic_name__(   self		):
        import faiss

        lowerCAmelCase__				:  int		       =     FaissIndex(string_factory='''Flat'''		)
        index.add_vectors(np.eye(5      ,				dtype=np.floataa		)		)
        self.assertIsInstance(index.faiss_index      ,				faiss.IndexFlat		)
        lowerCAmelCase__				:  Tuple		       =     FaissIndex(string_factory='''LSH'''		)
        index.add_vectors(np.eye(5      ,				dtype=np.floataa		)		)
        self.assertIsInstance(index.faiss_index      ,				faiss.IndexLSH		)
        with self.assertRaises(__UpperCAmelCase		):
          lowerCAmelCase__				:  Optional[int]		       =     FaissIndex(string_factory='''Flat'''      ,				custom_index=faiss.IndexFlat(5		)		)

      def 	__magic_name__(   self		):
        import faiss

        lowerCAmelCase__				:  Optional[int]		       =     faiss.IndexFlat(5		)
        lowerCAmelCase__				:  str		       =     FaissIndex(custom_index=__UpperCAmelCase		)
        index.add_vectors(np.eye(5      ,				dtype=np.floataa		)		)
        self.assertIsInstance(index.faiss_index      ,				faiss.IndexFlat		)







      def 	__magic_name__(   self		):
        import faiss

        lowerCAmelCase__				:  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		)
          lowerCAmelCase__				:  Any		       =     FaissIndex.load(tmp_file.name		)
        os.unlink(tmp_file.name		)

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



@require_faiss
def      __lowerCAmelCase			(					UpperCamelCase      )     ->	List[str]:
  import faiss

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

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

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






@require_elasticsearch
class  _lowerCAmelCase     (  _lowercase	):

      def 	__magic_name__(   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:
          lowerCAmelCase__				:  Optional[Any]		       =     Elasticsearch()
          lowerCAmelCase__				:  List[Any]		       =     {'''acknowledged''': True}
          lowerCAmelCase__				:  Optional[Any]		       =     ElasticSearchIndex(es_client=__UpperCAmelCase		)
          mocked_bulk.return_value([(True, None)] * 3		)
          index.add_documents(['''foo''', '''bar''', '''foobar''']		)

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

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

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

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







lowerCAmelCase_					    = [
    [0, 16, 13, 0, 0, 0],
    [0, 0, 10, 12, 0, 0],
    [0, 4, 0, 0, 14, 0],
    [0, 0, 9, 0, 0, 20],
    [0, 0, 0, 7, 0, 4],
    [0, 0, 0, 0, 0, 0],
]



def      __lowerCAmelCase			(					UpperCamelCase	,      UpperCamelCase	,      UpperCamelCase	,      UpperCamelCase      )     ->	int:
  # Return True if there is node that has not iterated.
  lowerCAmelCase__				:  List[str]		       =     [False] * len(UpperCamelCase      )
  lowerCAmelCase__				:  int		       =     [s]
  lowerCAmelCase__				:  Dict		       =     True

  while queue:
    lowerCAmelCase__				:  Union[str, Any]		       =     queue.pop(0      )
    for ind in range(len(graph[u]      )      ):
      if visited[ind] is False and graph[u][ind] > 0:
        queue.append(UpperCamelCase      )
        lowerCAmelCase__				:  List[str]		       =     True
        lowerCAmelCase__				:  int		       =     u

  return visited[t]



def      __lowerCAmelCase			(					UpperCamelCase	,      UpperCamelCase	,      UpperCamelCase      )     ->	Optional[Any]:
  lowerCAmelCase__				:  Dict		       =     [-1] * (len(UpperCamelCase      ))
  lowerCAmelCase__				:  Dict		       =     0
  lowerCAmelCase__				:  List[str]		       =     []
  lowerCAmelCase__				:  Tuple		       =     [i[:] for i in graph]  # Record original cut, copy.
  while bfs(UpperCamelCase	,      UpperCamelCase	,      UpperCamelCase	,      UpperCamelCase      ):
    lowerCAmelCase__				:  Optional[Any]		       =     float('''Inf'''      )
    lowerCAmelCase__				:  Optional[Any]		       =     sink

    while s != source:
      # Find the minimum value in select path
      lowerCAmelCase__				:  Optional[Any]		       =     min(UpperCamelCase	,      graph[parent[s]][s]      )
      lowerCAmelCase__				:  Union[str, Any]		       =     parent[s]

    max_flow += path_flow
    lowerCAmelCase__				:  List[str]		       =     sink

    while v != source:
      lowerCAmelCase__				:  Union[str, Any]		       =     parent[v]
      graph[u][v] -= path_flow
      graph[v][u] += path_flow
      lowerCAmelCase__				:  Dict		       =     parent[v]

  for i in range(len(UpperCamelCase      )      ):
    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))

