
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


__A				=pytest.mark.integration




@require_faiss
class     _SCREAMING_SNAKE_CASE     (      snake_case_						):



	def     SCREAMING_SNAKE_CASE_(    self )				->       List[str]:
					lowerCamelCase_						=			Dataset.from_dict({"filename": ["my_name-train" + "_" + str(lowercase ) for x in np.arange(30 ).tolist()]} )
					return dset



	def     SCREAMING_SNAKE_CASE_(    self )				->       Union[str, Any]:
					import faiss

					lowerCamelCase_						=			self._create_dummy_dataset()
					lowerCamelCase_						=			dset.map(
					    lambda lowercase						,  lowercase : {"vecs": i * np.ones(5						,  dtype=np.floataa )}						,  with_indices=lowercase						,  keep_in_memory=lowercase )
					lowerCamelCase_						=			dset.add_faiss_index("vecs"						,  batch_size=100						,  metric_type=faiss.METRIC_INNER_PRODUCT )
					lowerCamelCase_	,    lowerCamelCase_						=			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     SCREAMING_SNAKE_CASE_(    self )				->       Dict:
					import faiss

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



	def     SCREAMING_SNAKE_CASE_(    self )				->       Optional[int]:
					import faiss

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



	def     SCREAMING_SNAKE_CASE_(    self )				->       Union[str, Any]:
					lowerCamelCase_						=			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(lowercase						,  partial(dset.get_nearest_examples						,  "vecs2"						,  np.ones(5						,  dtype=np.floataa ) ) )



	def     SCREAMING_SNAKE_CASE_(    self )				->       Optional[int]:
					from elasticsearch import Elasticsearch

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

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




@require_faiss
class     _SCREAMING_SNAKE_CASE     (      snake_case_						):



	def     SCREAMING_SNAKE_CASE_(    self )				->       Tuple:
					import faiss

					lowerCamelCase_						=			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_						=			np.zeros(5						,  dtype=np.floataa )
					lowerCamelCase_						=			1
					lowerCamelCase_	,    lowerCamelCase_						=			index.search(lowercase )
					self.assertRaises(lowercase						,  index.search						,  query.reshape(-1						,  1 ) )
					self.assertGreater(scores[0]						,  0 )
					self.assertEqual(indices[0]						,  1 )

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



	def     SCREAMING_SNAKE_CASE_(    self )				->       Any:
					import faiss

					lowerCamelCase_						=			FaissIndex(string_factory="Flat" )
					index.add_vectors(np.eye(5						,  dtype=np.floataa ) )
					self.assertIsInstance(index.faiss_index						,  faiss.IndexFlat )
					lowerCamelCase_						=			FaissIndex(string_factory="LSH" )
					index.add_vectors(np.eye(5						,  dtype=np.floataa ) )
					self.assertIsInstance(index.faiss_index						,  faiss.IndexLSH )
					with self.assertRaises(lowercase ):
									lowerCamelCase_						=			FaissIndex(string_factory="Flat"						,  custom_index=faiss.IndexFlat(5 ) )



	def     SCREAMING_SNAKE_CASE_(    self )				->       Optional[int]:
					import faiss

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



	def     SCREAMING_SNAKE_CASE_(    self )				->       List[str]:
					import faiss

					lowerCamelCase_						=			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=lowercase ) as tmp_file:
									index.save(tmp_file.name )
									lowerCamelCase_						=			FaissIndex.load(tmp_file.name )
					os.unlink(tmp_file.name )

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





@require_faiss
def 			lowerCamelCase_ (				lowerCamelCase__    ):
				import faiss

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

				lowerCamelCase_						=			"index.faiss"
				lowerCamelCase_						=			F'mock://{index_name}'
				index.save(lowerCamelCase__	, storage_options=mockfs.storage_options    )
				lowerCamelCase_						=			FaissIndex.load(lowerCamelCase__	, storage_options=mockfs.storage_options    )

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





@require_elasticsearch
class     _SCREAMING_SNAKE_CASE     (      snake_case_						):



	def     SCREAMING_SNAKE_CASE_(    self )				->       Optional[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:
									lowerCamelCase_						=			Elasticsearch()
									lowerCamelCase_						=			{"acknowledged": True}
									lowerCamelCase_						=			ElasticSearchIndex(es_client=lowercase )
									mocked_bulk.return_value([(True, None)] * 3 )
									index.add_documents(["foo", "bar", "foobar"] )

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

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

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

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








import argparse
from collections import defaultdict

import yaml


_A     =			'''docs/source/en/_toctree.yml'''





def __UpperCamelCase			(       _A  ):
						lowerCAmelCase_      			=  defaultdict(_A  )
						for doc in model_doc:
												counts[doc["local"]] += 1
						lowerCAmelCase_      			=  [key for key, value in counts.items() if value > 1]

						lowerCAmelCase_      			=  []
						for duplicate_key in duplicates:
												lowerCAmelCase_      			=  list({doc['''title'''] for doc in model_doc if doc['''local'''] == duplicate_key}  )
												if len(_A  ) > 1:
																		raise ValueError(
																		    f"{duplicate_key} is present several times in the documentation table of content at "
																		    '''`docs/source/en/_toctree.yml` with different *Title* values. Choose one of those and remove the '''
																		    '''others.'''  )
												# Only add this once
												new_doc.append({'''local''': duplicate_key, '''title''': titles[0]}  )

						# Add none duplicate-keys
						new_doc.extend([doc for doc in model_doc if counts[doc['''local''']] == 1]  )

						# Sort
						return sorted(_A ,  key=lambda _A  : s["title"].lower()  )





def __UpperCamelCase			(       _A=False  ):
						with open(_A ,  encoding='''utf-8'''  ) as f:
												lowerCAmelCase_      			=  yaml.safe_load(f.read()  )

						# Get to the API doc
						lowerCAmelCase_      			=  0
						while content[api_idx]["title"] != "API":
												api_idx += 1
						lowerCAmelCase_      			=  content[api_idx]['''sections''']

						# Then to the model doc
						lowerCAmelCase_      			=  0
						while api_doc[model_idx]["title"] != "Models":
												model_idx += 1

						lowerCAmelCase_      			=  api_doc[model_idx]['''sections''']

						lowerCAmelCase_      			=  [(idx, section) for idx, section in enumerate(_A  ) if '''sections''' in section]
						lowerCAmelCase_      			=  False
						for idx, modality_doc in modalities_docs:
												lowerCAmelCase_      			=  modality_doc['''sections''']
												lowerCAmelCase_      			=  clean_model_doc_toc(_A  )

												if old_modality_doc != new_modality_doc:
																		lowerCAmelCase_      			=  True
																		if overwrite:
																								lowerCAmelCase_      			=  new_modality_doc

						if diff:
												if overwrite:
																		lowerCAmelCase_      			=  model_doc
																		lowerCAmelCase_      			=  api_doc
																		with open(_A ,  '''w''' ,  encoding='''utf-8'''  ) as f:
																								f.write(yaml.dump(_A ,  allow_unicode=_A  )  )
												else:
																		raise ValueError(
																		    '''The model doc part of the table of content is not properly sorted, run `make style` to fix this.'''  )


if __name__ == "__main__":
						_A     =			argparse.ArgumentParser()
						parser.add_argument('''--fix_and_overwrite''', action='''store_true''', help='''Whether to fix inconsistencies.''')
						_A     =			parser.parse_args()

						check_model_doc(args.fix_and_overwrite)




