

'''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      					=     pytest.mark.integration
@require_faiss
class 					_snake_case		(A__):






			def 		UpperCamelCase__							(  self     ):
				UpperCAmelCase_     :      Union[str, Any]						=  Dataset.from_dict({"filename": ["my_name-train" + "_" + str(__UpperCAmelCase     ) for x in np.arange(30     ).tolist()]}     )
				return dset






			def 		UpperCamelCase__							(  self     ):
				import faiss

				UpperCAmelCase_     :      Union[str, Any]						=  self._create_dummy_dataset()
				UpperCAmelCase_     :      Dict						=  dset.map(
				    lambda _snake_case			,_snake_case     : {"vecs": i * np.ones(5			,dtype=np.floataa     )}			,with_indices=__UpperCAmelCase			,keep_in_memory=__UpperCAmelCase     )
				UpperCAmelCase_     :      List[str]						=  dset.add_faiss_index("vecs"			,batch_size=1_00			,metric_type=faiss.METRIC_INNER_PRODUCT     )
				UpperCAmelCase_					,					UpperCAmelCase_     :      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 		UpperCamelCase__							(  self     ):
				import faiss

				UpperCAmelCase_     :      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=1_00			,metric_type=faiss.METRIC_INNER_PRODUCT			,)
				UpperCAmelCase_					,					UpperCAmelCase_     :      Tuple						=  dset.get_nearest_examples("vecs"			,np.ones(5			,dtype=np.floataa     )     )
				self.assertEqual(examples["filename"][0]			,"my_name-train_29"     )






			def 		UpperCamelCase__							(  self     ):
				import faiss

				UpperCAmelCase_     :      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"			,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     )

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






			def 		UpperCamelCase__							(  self     ):
				UpperCAmelCase_     :      List[str]						=  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 		UpperCamelCase__							(  self     ):
				from elasticsearch import Elasticsearch

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

					dset.add_elasticsearch_index("filename"			,es_client=__UpperCAmelCase     )
					UpperCAmelCase_					,					UpperCAmelCase_     :      Union[str, Any]						=  dset.get_nearest_examples("filename"			,"my_name-train_29"     )
					self.assertEqual(examples["filename"][0]			,"my_name-train_29"     )




@require_faiss
class 					_snake_case		(A__):






			def 		UpperCamelCase__							(  self     ):
				import faiss

				UpperCAmelCase_     :      int						=  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
				UpperCAmelCase_     :      Any						=  np.zeros(5			,dtype=np.floataa     )
				UpperCAmelCase_     :      Optional[int]						=  1
				UpperCAmelCase_					,					UpperCAmelCase_     :      Optional[Any]						=  index.search(__UpperCAmelCase     )
				self.assertRaises(__UpperCAmelCase			,index.search			,query.reshape(-1			,1     )     )
				self.assertGreater(scores[0]			,0     )
				self.assertEqual(indices[0]			,1     )

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






			def 		UpperCamelCase__							(  self     ):
				import faiss

				UpperCAmelCase_     :      str						=  FaissIndex(string_factory="Flat"     )
				index.add_vectors(np.eye(5			,dtype=np.floataa     )     )
				self.assertIsInstance(index.faiss_index			,faiss.IndexFlat     )
				UpperCAmelCase_     :      Optional[Any]						=  FaissIndex(string_factory="LSH"     )
				index.add_vectors(np.eye(5			,dtype=np.floataa     )     )
				self.assertIsInstance(index.faiss_index			,faiss.IndexLSH     )
				with self.assertRaises(__UpperCAmelCase     ):
					UpperCAmelCase_     :      str						=  FaissIndex(string_factory="Flat"			,custom_index=faiss.IndexFlat(5     )     )






			def 		UpperCamelCase__							(  self     ):
				import faiss

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






			def 		UpperCamelCase__							(  self     ):
				import faiss

				UpperCAmelCase_     :      Tuple						=  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     )
					UpperCAmelCase_     :      Optional[Any]						=  FaissIndex.load(tmp_file.name     )
				os.unlink(tmp_file.name     )

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




@require_faiss
def  a__       (    _SCREAMING_SNAKE_CASE   :       Tuple				)     ->					Tuple:


	"""simple docstring"""





	import faiss

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

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

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





@require_elasticsearch
class 					_snake_case		(A__):






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

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

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

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

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







"""simple docstring"""




import logging
from dataclasses import dataclass, field
from typing import Optional

from seqaseq_trainer import arg_to_scheduler

from transformers import TrainingArguments


A_				:      Optional[Any]           =			logging.getLogger(__name__)





@dataclass
class  lowerCamelCase    (A__      ):
			lowerCamelCase__ :		Optional[float]       		=				field(
			    default=0.0      ,metadata={'help': 'The label smoothing epsilon to apply (if not zero).'}      )
			lowerCamelCase__ :		bool       		=				field(default=A__      ,metadata={'help': 'Whether to SortishSamler or not.'}      )
			lowerCamelCase__ :		bool       		=				field(
			    default=A__      ,metadata={'help': 'Whether to use generate to calculate generative metrics (ROUGE, BLEU).'}      )
			lowerCamelCase__ :		bool       		=				field(default=A__      ,metadata={'help': 'whether to use adafactor'}      )
			lowerCamelCase__ :		Optional[float]       		=				field(
			    default=A__      ,metadata={'help': 'Encoder layer dropout probability. Goes into model.config.'}      )
			lowerCamelCase__ :		Optional[float]       		=				field(
			    default=A__      ,metadata={'help': 'Decoder layer dropout probability. Goes into model.config.'}      )
			lowerCamelCase__ :		Optional[float]       		=				field(default=A__      ,metadata={'help': 'Dropout probability. Goes into model.config.'}      )
			lowerCamelCase__ :		Optional[float]       		=				field(
			    default=A__      ,metadata={'help': 'Attention dropout probability. Goes into model.config.'}      )
			lowerCamelCase__ :		Optional[str]       		=				field(
			    default='linear'      ,metadata={'help': f"Which lr scheduler to use. Selected in {sorted(arg_to_scheduler.keys()      )}"}      ,)


