'''simple docstring'''

import json
import os
import shutil
import tempfile
import unittest

import numpy as np

from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES, BertTokenizer
from transformers.testing_utils import require_tokenizers, require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_vision_available


if is_vision_available():
  from PIL import Image

  from transformers import VisionTextDualEncoderProcessor, ViTImageProcessor



@require_tokenizers
@require_vision
class      UpperCAmelCase    (		unittest.TestCase   ):





       '''simple docstring'''



       def _lowerCAmelCase(		self					)    ->    Optional[Any]:
        lowercase__							:       Tuple										=   tempfile.mkdtemp()

        # fmt: off
        lowercase__							:       Dict										=   ['''[UNK]''', '''[CLS]''', '''[SEP]''', '''[PAD]''', '''[MASK]''', '''want''', '''##want''', '''##ed''', '''wa''', '''un''', '''runn''', '''##ing''', ''',''', '''low''', '''lowest''']
        # fmt: on
        lowercase__							:       Union[str, Any]										=   os.path.join(self.tmpdirname      ,  VOCAB_FILES_NAMES['''vocab_file''']					)
        with open(self.vocab_file      ,  '''w'''      ,  encoding='''utf-8'''					) as vocab_writer:
         vocab_writer.write(''''''.join([x + '''\n''' for x in vocab_tokens]					)					)

        lowercase__							:       Union[str, Any]										=   {
            '''do_resize''': True,
            '''size''': {'''height''': 18, '''width''': 18},
            '''do_normalize''': True,
            '''image_mean''': [0.5, 0.5, 0.5],
            '''image_std''': [0.5, 0.5, 0.5],
        }
        lowercase__							:       List[Any]										=   os.path.join(self.tmpdirname      ,  _snake_case					)
        with open(self.image_processor_file      ,  '''w'''      ,  encoding='''utf-8'''					) as fp:
         json.dump(_snake_case      ,  _snake_case					)

       def _lowerCAmelCase(		self      ,  **__lowerCAmelCase					)    ->    List[Any]:
        return BertTokenizer.from_pretrained(self.tmpdirname      ,  **_snake_case					)

       def _lowerCAmelCase(		self      ,  **__lowerCAmelCase					)    ->    Tuple:
        return ViTImageProcessor.from_pretrained(self.tmpdirname      ,  **_snake_case					)

       def _lowerCAmelCase(		self					)    ->    Union[str, Any]:
        shutil.rmtree(self.tmpdirname					)

       def _lowerCAmelCase(		self					)    ->    Union[str, Any]:
        lowercase__							:       Union[str, Any]										=   [np.random.randint(255      ,  size=(3, 30, 400)      ,  dtype=np.uinta					)]

        lowercase__							:       str										=   [Image.fromarray(np.moveaxis(_snake_case      ,  0      ,  -1					)					) for x in image_inputs]

        return image_inputs

       def _lowerCAmelCase(		self					)    ->    str:
        lowercase__							:       Any										=   self.get_tokenizer()
        lowercase__							:       Any										=   self.get_image_processor()

        lowercase__							:       List[Any]										=   VisionTextDualEncoderProcessor(tokenizer=_snake_case      ,  image_processor=_snake_case					)

        processor.save_pretrained(self.tmpdirname					)
        lowercase__							:       int										=   VisionTextDualEncoderProcessor.from_pretrained(self.tmpdirname					)

        self.assertEqual(processor.tokenizer.get_vocab()      ,  tokenizer.get_vocab()					)
        self.assertIsInstance(processor.tokenizer      ,  (BertTokenizer, BertTokenizerFast)					)

        self.assertEqual(processor.image_processor.to_json_string()      ,  image_processor.to_json_string()					)
        self.assertIsInstance(processor.image_processor      ,  _snake_case					)

       def _lowerCAmelCase(		self					)    ->    List[Any]:
        lowercase__							:       Optional[Any]										=   VisionTextDualEncoderProcessor(
            tokenizer=self.get_tokenizer()      ,  image_processor=self.get_image_processor()					)
        processor.save_pretrained(self.tmpdirname					)

        lowercase__							:       List[Any]										=   self.get_tokenizer(bos_token='''(BOS)'''      ,  eos_token='''(EOS)'''					)
        lowercase__							:       Optional[Any]										=   self.get_image_processor(do_normalize=_snake_case      ,  padding_value=1.0					)

        lowercase__							:       Dict										=   VisionTextDualEncoderProcessor.from_pretrained(
            self.tmpdirname      ,  bos_token='''(BOS)'''      ,  eos_token='''(EOS)'''      ,  do_normalize=_snake_case      ,  padding_value=1.0					)

        self.assertEqual(processor.tokenizer.get_vocab()      ,  tokenizer_add_kwargs.get_vocab()					)
        self.assertIsInstance(processor.tokenizer      ,  (BertTokenizer, BertTokenizerFast)					)

        self.assertEqual(processor.image_processor.to_json_string()      ,  image_processor_add_kwargs.to_json_string()					)
        self.assertIsInstance(processor.image_processor      ,  _snake_case					)

       def _lowerCAmelCase(		self					)    ->    Dict:
        lowercase__							:       List[str]										=   self.get_image_processor()
        lowercase__							:       List[Any]										=   self.get_tokenizer()

        lowercase__							:       Dict										=   VisionTextDualEncoderProcessor(tokenizer=_snake_case      ,  image_processor=_snake_case					)

        lowercase__							:       Optional[Any]										=   self.prepare_image_inputs()

        lowercase__							:       Any										=   image_processor(_snake_case      ,  return_tensors='''np'''					)
        lowercase__							:       List[Any]										=   processor(images=_snake_case      ,  return_tensors='''np'''					)

        for key in input_feat_extract.keys():
         self.assertAlmostEqual(input_feat_extract[key].sum()      ,  input_processor[key].sum()      ,  delta=1E-2					)

       def _lowerCAmelCase(		self					)    ->    int:
        lowercase__							:       str										=   self.get_image_processor()
        lowercase__							:       Dict										=   self.get_tokenizer()

        lowercase__							:       Tuple										=   VisionTextDualEncoderProcessor(tokenizer=_snake_case      ,  image_processor=_snake_case					)

        lowercase__							:       Union[str, Any]										=   '''lower newer'''

        lowercase__							:       Dict										=   processor(text=_snake_case					)

        lowercase__							:       Dict										=   tokenizer(_snake_case					)

        for key in encoded_tok.keys():
         self.assertListEqual(encoded_tok[key]      ,  encoded_processor[key]					)

       def _lowerCAmelCase(		self					)    ->    Optional[Any]:
        lowercase__							:       Optional[int]										=   self.get_image_processor()
        lowercase__							:       List[str]										=   self.get_tokenizer()

        lowercase__							:       List[str]										=   VisionTextDualEncoderProcessor(tokenizer=_snake_case      ,  image_processor=_snake_case					)

        lowercase__							:       Tuple										=   '''lower newer'''
        lowercase__							:       Optional[Any]										=   self.prepare_image_inputs()

        lowercase__							:       Optional[Any]										=   processor(text=_snake_case      ,  images=_snake_case					)

        self.assertListEqual(list(inputs.keys()					)      ,  ['''input_ids''', '''token_type_ids''', '''attention_mask''', '''pixel_values''']					)

        # test if it raises when no input is passed
        with self.assertRaises(_snake_case					):
         processor()

       def _lowerCAmelCase(		self					)    ->    Union[str, Any]:
        lowercase__							:       Optional[Any]										=   self.get_image_processor()
        lowercase__							:       Tuple										=   self.get_tokenizer()

        lowercase__							:       Any										=   VisionTextDualEncoderProcessor(tokenizer=_snake_case      ,  image_processor=_snake_case					)

        lowercase__							:       Optional[int]										=   [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

        lowercase__							:       int										=   processor.batch_decode(_snake_case					)
        lowercase__							:       Any										=   tokenizer.batch_decode(_snake_case					)

        self.assertListEqual(_snake_case      ,  _snake_case					)


       def _lowerCAmelCase(		self					)    ->    str:
        lowercase__							:       Any										=   self.get_image_processor()
        lowercase__							:       Optional[int]										=   self.get_tokenizer()

        lowercase__							:       Any										=   VisionTextDualEncoderProcessor(tokenizer=_snake_case      ,  image_processor=_snake_case					)

        lowercase__							:       Tuple										=   '''lower newer'''
        lowercase__							:       List[str]										=   self.prepare_image_inputs()

        lowercase__							:       List[str]										=   processor(text=_snake_case      ,  images=_snake_case					)

        self.assertListEqual(list(inputs.keys()					)      ,  processor.model_input_names					)








"""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


__UpperCamelCase     :						Optional[int]						       =  pytest.mark.integration







@require_faiss
class       a							(   a__  ):



 def    UpperCamelCase__  (     self     ):







  """simple docstring"""






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



 def    UpperCamelCase__  (     self     ):







  """simple docstring"""






  import faiss

  lowerCAmelCase    				= self._create_dummy_dataset()
  lowerCAmelCase    				= dset.map(
      lambda _snake_case				,       _snake_case     : {"vecs": i * np.ones(5				,       dtype=np.floataa     )}				,       with_indices=_snake_case				,       keep_in_memory=_snake_case     )
  lowerCAmelCase    				= dset.add_faiss_index('vecs'				,       batch_size=1_00				,       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    UpperCamelCase__  (     self     ):







  """simple docstring"""






  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=1_00				,       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    UpperCamelCase__  (     self     ):







  """simple docstring"""






  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=_snake_case     ) 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    UpperCamelCase__  (     self     ):







  """simple docstring"""






  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(_snake_case				,       partial(dset.get_nearest_examples				,       'vecs2'				,       np.ones(5				,       dtype=np.floataa     )     )     )



 def    UpperCamelCase__  (     self     ):







  """simple docstring"""






  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=_snake_case     )
   lowerCAmelCase				,lowerCAmelCase    				= dset.get_nearest_examples('filename'				,       'my_name-train_29'     )
   self.assertEqual(examples['filename'][0]				,       'my_name-train_29'     )







@require_faiss
class       a							(   a__  ):



 def    UpperCamelCase__  (     self     ):







  """simple docstring"""






  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(_snake_case     )
  self.assertRaises(_snake_case				,       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(_snake_case     )
  self.assertRaises(_snake_case				,       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(_snake_case     )				,       0     )
  self.assertListEqual([4, 3, 2, 1, 0]				,       _snake_case     )



 def    UpperCamelCase__  (     self     ):







  """simple docstring"""






  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(_snake_case     ):
   lowerCAmelCase    				= FaissIndex(string_factory='Flat'				,       custom_index=faiss.IndexFlat(5     )     )



 def    UpperCamelCase__  (     self     ):







  """simple docstring"""






  import faiss

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



 def    UpperCamelCase__  (     self     ):







  """simple docstring"""






  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=_snake_case     ) 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(_snake_case     )
  self.assertGreater(scores[0]				,       0     )
  self.assertEqual(indices[0]				,       1     )


@require_faiss
def 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    Dict			):
 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(_UpperCAmelCase  ,     storage_options=mockfs.storage_options			)
 lowerCAmelCase    				= FaissIndex.load(_UpperCAmelCase  ,     storage_options=mockfs.storage_options			)

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







@require_elasticsearch
class       a							(   a__  ):



 def    UpperCamelCase__  (     self     ):







  """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:
   lowerCAmelCase    				= Elasticsearch()
   lowerCAmelCase    				= {'acknowledged': True}
   lowerCAmelCase    				= ElasticSearchIndex(es_client=_snake_case     )
   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(_snake_case     )
   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(_snake_case				,       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(_snake_case     )
   lowerCAmelCase    				= [scores[0] for scores in total_scores]
   lowerCAmelCase    				= [indices[0] for indices in total_indices]
   self.assertGreater(np.min(_snake_case     )				,       0     )
   self.assertListEqual([1, 1, 1]				,       _snake_case     )

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





