




'''simple docstring'''

import json
import os
import shutil
import tempfile
from unittest import TestCase

from transformers import BartTokenizer, BartTokenizerFast, DPRQuestionEncoderTokenizer, DPRQuestionEncoderTokenizerFast
from transformers.models.bart.configuration_bart import BartConfig
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES as DPR_VOCAB_FILES_NAMES
from transformers.models.dpr.configuration_dpr import DPRConfig
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES as BART_VOCAB_FILES_NAMES
from transformers.testing_utils import require_faiss, require_tokenizers, require_torch, slow
from transformers.utils import is_datasets_available, is_faiss_available, is_torch_available


if is_torch_available() and is_datasets_available() and is_faiss_available():
							from transformers.models.rag.configuration_rag import RagConfig
							from transformers.models.rag.tokenization_rag import RagTokenizer






@require_faiss
@require_torch
class 						a				(   _lowerCamelCase     ):


				def   A_ (		self    :					Union[str, Any]					):
									snake_case_									=				tempfile.mkdtemp()
									snake_case_									=				8

									# DPR tok
									snake_case_									=				[
									    '''[UNK]''',
									    '''[CLS]''',
									    '''[SEP]''',
									    '''[PAD]''',
									    '''[MASK]''',
									    '''want''',
									    '''##want''',
									    '''##ed''',
									    '''wa''',
									    '''un''',
									    '''runn''',
									    '''##ing''',
									    ''',''',
									    '''low''',
									    '''lowest''',
									]
									snake_case_									=				os.path.join(self.tmpdirname       ,				'''dpr_tokenizer'''					)
									os.makedirs(lowercase_       ,				exist_ok=lowercase_					)
									snake_case_									=				os.path.join(lowercase_       ,				DPR_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]					)					)

									# BART tok
									snake_case_									=				[
									    '''l''',
									    '''o''',
									    '''w''',
									    '''e''',
									    '''r''',
									    '''s''',
									    '''t''',
									    '''i''',
									    '''d''',
									    '''n''',
									    '''\u0120''',
									    '''\u0120l''',
									    '''\u0120n''',
									    '''\u0120lo''',
									    '''\u0120low''',
									    '''er''',
									    '''\u0120lowest''',
									    '''\u0120newer''',
									    '''\u0120wider''',
									    '''<unk>''',
									]
									snake_case_									=				dict(zip(lowercase_       ,				range(len(lowercase_					)					)					)					)
									snake_case_									=				['''#version: 0.2''', '''\u0120 l''', '''\u0120l o''', '''\u0120lo w''', '''e r''', '''''']
									snake_case_									=				{'''unk_token''': '''<unk>'''}

									snake_case_									=				os.path.join(self.tmpdirname       ,				'''bart_tokenizer'''					)
									os.makedirs(lowercase_       ,				exist_ok=lowercase_					)
									snake_case_									=				os.path.join(lowercase_       ,				BART_VOCAB_FILES_NAMES['''vocab_file''']					)
									snake_case_									=				os.path.join(lowercase_       ,				BART_VOCAB_FILES_NAMES['''merges_file''']					)
									with open(self.vocab_file       ,				'''w'''       ,				encoding='''utf-8'''					) as fp:
														fp.write(json.dumps(lowercase_					) + '''\n'''					)
									with open(self.merges_file       ,				'''w'''       ,				encoding='''utf-8'''					) as fp:
														fp.write('''\n'''.join(lowercase_					)					)


				def   A_ (		self    :					Any					):
									return DPRQuestionEncoderTokenizer.from_pretrained(os.path.join(self.tmpdirname       ,				'''dpr_tokenizer'''					)					)


				def   A_ (		self    :					Dict					):
									return BartTokenizer.from_pretrained(os.path.join(self.tmpdirname       ,				'''bart_tokenizer'''					)					)


				def   A_ (		self    :					Optional[Any]					):
									shutil.rmtree(self.tmpdirname					)


				@require_tokenizers
				def   A_ (		self    :					Union[str, Any]					):
									snake_case_									=				os.path.join(self.tmpdirname       ,				'''rag_tokenizer'''					)
									snake_case_									=				RagConfig(question_encoder=DPRConfig().to_dict()       ,				generator=BartConfig().to_dict()					)
									snake_case_									=				RagTokenizer(question_encoder=self.get_dpr_tokenizer()       ,				generator=self.get_bart_tokenizer()					)
									rag_config.save_pretrained(lowercase_					)
									rag_tokenizer.save_pretrained(lowercase_					)
									snake_case_									=				RagTokenizer.from_pretrained(lowercase_       ,				config=lowercase_					)
									self.assertIsInstance(new_rag_tokenizer.question_encoder       ,				lowercase_					)
									self.assertEqual(new_rag_tokenizer.question_encoder.get_vocab()       ,				rag_tokenizer.question_encoder.get_vocab()					)
									self.assertIsInstance(new_rag_tokenizer.generator       ,				lowercase_					)
									self.assertEqual(new_rag_tokenizer.generator.get_vocab()       ,				rag_tokenizer.generator.get_vocab()					)


				@slow
				def   A_ (		self    :					List[Any]					):
									snake_case_									=				RagTokenizer.from_pretrained('''facebook/rag-token-nq'''					)
									snake_case_									=				[
									    '''who got the first nobel prize in physics''',
									    '''when is the next deadpool movie being released''',
									    '''which mode is used for short wave broadcast service''',
									    '''who is the owner of reading football club''',
									    '''when is the next scandal episode coming out''',
									    '''when is the last time the philadelphia won the superbowl''',
									    '''what is the most current adobe flash player version''',
									    '''how many episodes are there in dragon ball z''',
									    '''what is the first step in the evolution of the eye''',
									    '''where is gall bladder situated in human body''',
									    '''what is the main mineral in lithium batteries''',
									    '''who is the president of usa right now''',
									    '''where do the greasers live in the outsiders''',
									    '''panda is a national animal of which country''',
									    '''what is the name of manchester united stadium''',
									]
									snake_case_									=				tokenizer(lowercase_					)
									self.assertIsNotNone(lowercase_					)


				@slow
				def   A_ (		self    :					Dict					):
									snake_case_									=				RagTokenizer.from_pretrained('''facebook/rag-sequence-nq'''					)
									snake_case_									=				[
									    '''who got the first nobel prize in physics''',
									    '''when is the next deadpool movie being released''',
									    '''which mode is used for short wave broadcast service''',
									    '''who is the owner of reading football club''',
									    '''when is the next scandal episode coming out''',
									    '''when is the last time the philadelphia won the superbowl''',
									    '''what is the most current adobe flash player version''',
									    '''how many episodes are there in dragon ball z''',
									    '''what is the first step in the evolution of the eye''',
									    '''where is gall bladder situated in human body''',
									    '''what is the main mineral in lithium batteries''',
									    '''who is the president of usa right now''',
									    '''where do the greasers live in the outsiders''',
									    '''panda is a national animal of which country''',
									    '''what is the name of manchester united stadium''',
									]
									snake_case_									=				tokenizer(lowercase_					)
									self.assertIsNotNone(lowercase_					)







'''simple docstring'''

import contextlib
import os
import sqlitea

import pytest

from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sqlalchemy


def 		__magic_name__    (	__UpperCAmelCase,      __UpperCAmelCase	)		->					str:

					'''simple docstring'''

					assert isinstance(__UpperCAmelCase,      __UpperCAmelCase	)
					assert dataset.num_rows == 4
					assert dataset.num_columns == 3
					assert dataset.column_names == ["col_1", "col_2", "col_3"]
					for feature, expected_dtype in expected_features.items():
										assert dataset.features[feature].dtype == expected_dtype


@require_sqlalchemy
@pytest.mark.parametrize('''keep_in_memory''',      [False, True]	)
def 		__magic_name__    (	__UpperCAmelCase,      __UpperCAmelCase,      __UpperCAmelCase,      __UpperCAmelCase	)		->					int:

					'''simple docstring'''

					snake_case_									=				tmp_path / '''cache'''
					snake_case_									=				{'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
					with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
										snake_case_									=				SqlDatasetReader(
										    '''dataset''',      '''sqlite:///''' + sqlite_path,      cache_dir=__UpperCAmelCase,      keep_in_memory=__UpperCAmelCase	).read()
					_check_sql_dataset(__UpperCAmelCase,      __UpperCAmelCase	)


@require_sqlalchemy
@pytest.mark.parametrize(
    '''features''',      [
        None,
        {'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''},
        {'''col_1''': '''string''', '''col_2''': '''string''', '''col_3''': '''string'''},
        {'''col_1''': '''int32''', '''col_2''': '''int32''', '''col_3''': '''int32'''},
        {'''col_1''': '''float32''', '''col_2''': '''float32''', '''col_3''': '''float32'''},
    ],      )
def 		__magic_name__    (	__UpperCAmelCase,      __UpperCAmelCase,      __UpperCAmelCase,      __UpperCAmelCase	)		->					List[str]:

					'''simple docstring'''

					snake_case_									=				tmp_path / '''cache'''
					snake_case_									=				{'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
					snake_case_									=				features.copy() if features else default_expected_features
					snake_case_									=				(
					    Features({feature: Value(__UpperCAmelCase	) for feature, dtype in features.items()}	) if features is not None else None
					)
					snake_case_									=				SqlDatasetReader('''dataset''',      '''sqlite:///''' + sqlite_path,      features=__UpperCAmelCase,      cache_dir=__UpperCAmelCase	).read()
					_check_sql_dataset(__UpperCAmelCase,      __UpperCAmelCase	)


def 		__magic_name__    (	__UpperCAmelCase	)		->					List[str]:

					'''simple docstring'''

					with contextlib.closing(sqlitea.connect(__UpperCAmelCase	)	) as con:
										snake_case_									=				con.cursor()
										cur.execute('''SELECT * FROM dataset'''	)
										for row in cur:
															yield row


@require_sqlalchemy
def 		__magic_name__    (	__UpperCAmelCase,      __UpperCAmelCase,      __UpperCAmelCase	)		->					List[Any]:

					'''simple docstring'''

					snake_case_									=				tmp_path / '''cache'''
					snake_case_									=				os.path.join(__UpperCAmelCase,      '''tmp.sql'''	)
					snake_case_									=				SqlDatasetReader('''dataset''',      '''sqlite:///''' + sqlite_path,      cache_dir=__UpperCAmelCase	).read()
					SqlDatasetWriter(__UpperCAmelCase,      '''dataset''',      '''sqlite:///''' + output_sqlite_path,      num_proc=1	).write()

					snake_case_									=				iter_sql_file(__UpperCAmelCase	)
					snake_case_									=				iter_sql_file(__UpperCAmelCase	)

					for rowa, rowa in zip(__UpperCAmelCase,      __UpperCAmelCase	):
										assert rowa == rowa


@require_sqlalchemy
def 		__magic_name__    (	__UpperCAmelCase,      __UpperCAmelCase,      __UpperCAmelCase	)		->					Any:

					'''simple docstring'''

					snake_case_									=				tmp_path / '''cache'''
					snake_case_									=				os.path.join(__UpperCAmelCase,      '''tmp.sql'''	)
					snake_case_									=				SqlDatasetReader('''dataset''',      '''sqlite:///''' + sqlite_path,      cache_dir=__UpperCAmelCase	).read()
					SqlDatasetWriter(__UpperCAmelCase,      '''dataset''',      '''sqlite:///''' + output_sqlite_path,      num_proc=2	).write()

					snake_case_									=				iter_sql_file(__UpperCAmelCase	)
					snake_case_									=				iter_sql_file(__UpperCAmelCase	)

					for rowa, rowa in zip(__UpperCAmelCase,      __UpperCAmelCase	):
										assert rowa == rowa


@require_sqlalchemy
def 		__magic_name__    (	__UpperCAmelCase,      __UpperCAmelCase,      __UpperCAmelCase	)		->					List[str]:

					'''simple docstring'''

					snake_case_									=				tmp_path / '''cache'''
					snake_case_									=				os.path.join(__UpperCAmelCase,      '''tmp.sql'''	)
					snake_case_									=				SqlDatasetReader('''dataset''',      '''sqlite:///''' + sqlite_path,      cache_dir=__UpperCAmelCase	).read()
					with pytest.raises(__UpperCAmelCase	):
										SqlDatasetWriter(__UpperCAmelCase,      '''dataset''',      '''sqlite:///''' + output_sqlite_path,      num_proc=0	).write()

