



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


__snake_case    :		List[str]  =pytest.mark.integration



@require_faiss
class 	lowerCamelCase__      (							lowerCamelCase__):




		'''simple docstring'''



		def 		lowerCAmelCase__				(self			)					->      Union[str, Any]:

						"""simple docstring"""






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



		def 		lowerCAmelCase__				(self			)					->      Optional[Any]:

						"""simple docstring"""






						import faiss

						lowerCAmelCase__					:    Dataset												=					self._create_dummy_dataset()
						lowerCAmelCase__					:    Dict												=					dset.map(
						    lambda __lowerCamelCase		,__lowerCamelCase			: {"vecs": i * np.ones(5		,dtype=np.floataa			)}		,with_indices=__lowerCamelCase		,keep_in_memory=__lowerCamelCase			)
						lowerCAmelCase__					:    str												=					dset.add_faiss_index('''vecs'''		,batch_size=1_00		,metric_type=faiss.METRIC_INNER_PRODUCT			)
						lowerCAmelCase__						,		lowerCAmelCase__					:    str												=					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			)					->      Any:

						"""simple docstring"""






						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=1_00		,metric_type=faiss.METRIC_INNER_PRODUCT		,)
						lowerCAmelCase__						,		lowerCAmelCase__					:    Union[str, Any]												=					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]:

						"""simple docstring"""






						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=__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			)

						lowerCAmelCase__						,		lowerCAmelCase__					:    List[Any]												=					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]:

						"""simple docstring"""






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



		def 		lowerCAmelCase__				(self			)					->      int:

						"""simple docstring"""






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

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



@require_faiss
class 	lowerCamelCase__      (							lowerCamelCase__):




		'''simple docstring'''



		def 		lowerCAmelCase__				(self			)					->      Optional[Any]:

						"""simple docstring"""






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

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



		def 		lowerCAmelCase__				(self			)					->      List[Any]:

						"""simple docstring"""






						import faiss

						lowerCAmelCase__					:    List[str]												=					FaissIndex(string_factory='''Flat'''			)
						index.add_vectors(np.eye(5		,dtype=np.floataa			)			)
						self.assertIsInstance(index.faiss_index		,faiss.IndexFlat			)
						lowerCAmelCase__					:    Union[str, Any]												=					FaissIndex(string_factory='''LSH'''			)
						index.add_vectors(np.eye(5		,dtype=np.floataa			)			)
						self.assertIsInstance(index.faiss_index		,faiss.IndexLSH			)
						with self.assertRaises(__lowerCamelCase			):
										lowerCAmelCase__					:    int												=					FaissIndex(string_factory='''Flat'''		,custom_index=faiss.IndexFlat(5			)			)



		def 		lowerCAmelCase__				(self			)					->      Optional[int]:

						"""simple docstring"""






						import faiss

						lowerCAmelCase__					:    Any												=					faiss.IndexFlat(5			)
						lowerCAmelCase__					:    Tuple												=					FaissIndex(custom_index=__lowerCamelCase			)
						index.add_vectors(np.eye(5		,dtype=np.floataa			)			)
						self.assertIsInstance(index.faiss_index		,faiss.IndexFlat			)



		def 		lowerCAmelCase__				(self			)					->      Any:

						"""simple docstring"""






						import faiss

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

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






@require_faiss
def      lowerCAmelCase__		(   lowerCamelCase_		:		str):





				'''simple docstring'''

				import faiss

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

				lowerCAmelCase__					:    Union[str, Any]												=					'''index.faiss'''
				lowerCAmelCase__					:    List[Any]												=					f"""mock://{index_name}"""
				index.save(lowerCamelCase_	,storage_options=mockfs.storage_options)
				lowerCAmelCase__					:    Optional[Any]												=					FaissIndex.load(lowerCamelCase_	,storage_options=mockfs.storage_options)

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



@require_elasticsearch
class 	lowerCamelCase__      (							lowerCamelCase__):




		'''simple docstring'''



		def 		lowerCAmelCase__				(self			)					->      Tuple:

						"""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__					:    Any												=					Elasticsearch()
										lowerCAmelCase__					:    Tuple												=					{'''acknowledged''': True}
										lowerCAmelCase__					:    Union[str, Any]												=					ElasticSearchIndex(es_client=__lowerCamelCase			)
										mocked_bulk.return_value([(True, None)] * 3			)
										index.add_documents(['''foo''', '''bar''', '''foobar''']			)

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

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

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

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






import fire
from torch.utils.data import DataLoader
from tqdm import tqdm

from transformers import AutoTokenizer
from utils import SeqaSeqDataset, pickle_save






def      lowerCAmelCase__		(   lowerCamelCase_		:		Dict	,lowerCamelCase_		:		Optional[int]	,lowerCamelCase_		:		List[Any]=1024	,lowerCamelCase_		:		int=1024	,lowerCamelCase_		:		Dict=False	,**lowerCamelCase_		:		Tuple):





				'''simple docstring'''

				lowerCAmelCase__					:    Optional[int]												=					AutoTokenizer.from_pretrained(lowerCamelCase_)
				lowerCAmelCase__					:    Optional[Any]												=					SeqaSeqDataset(lowerCamelCase_	,lowerCamelCase_	,lowerCamelCase_	,lowerCamelCase_	,type_path='''train'''	,**lowerCamelCase_)
				lowerCAmelCase__					:    int												=					tok.pad_token_id

				def get_lens(lowerCamelCase_		:		Tuple):
								lowerCAmelCase__					:    Tuple												=					tqdm(
								    DataLoader(lowerCamelCase_	,batch_size=512	,num_workers=8	,shuffle=lowerCamelCase_	,collate_fn=ds.collate_fn)	,desc=str(ds.len_file)	,)
								lowerCAmelCase__					:    Tuple												=					[]
								for batch in dl:
												lowerCAmelCase__					:    Dict												=					batch['''input_ids'''].ne(lowerCamelCase_).sum(1).tolist()
												lowerCAmelCase__					:    Dict												=					batch['''labels'''].ne(lowerCamelCase_).sum(1).tolist()
												if consider_target:
																for src, tgt in zip(lowerCamelCase_	,lowerCamelCase_):
																				max_lens.append(max(lowerCamelCase_	,lowerCamelCase_))
												else:
																max_lens.extend(lowerCamelCase_)
								return max_lens

				lowerCAmelCase__					:    str												=					get_lens(lowerCamelCase_)
				lowerCAmelCase__					:    Tuple												=					SeqaSeqDataset(lowerCamelCase_	,lowerCamelCase_	,lowerCamelCase_	,lowerCamelCase_	,type_path='''val'''	,**lowerCamelCase_)
				lowerCAmelCase__					:    Optional[int]												=					get_lens(lowerCamelCase_)
				pickle_save(lowerCamelCase_	,train_ds.len_file)
				pickle_save(lowerCamelCase_	,val_ds.len_file)


if __name__ == "__main__":
							fire.Fire(save_len_file)

