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






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






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






@require_sqlalchemy
def 				__lowerCamelCase		(						lowerCAmelCase__     ,  lowerCAmelCase__     ,  lowerCAmelCase__     ):
       lowerCAmelCase__					     = tmp_path / 'cache'
       lowerCAmelCase__					     = os.path.join(lowerCAmelCase__     ,  'tmp.sql'     )
       lowerCAmelCase__					     = SqlDatasetReader('dataset'     ,  'sqlite:///' + sqlite_path     ,  cache_dir=lowerCAmelCase__     ).read()
       SqlDatasetWriter(lowerCAmelCase__     ,  'dataset'     ,  'sqlite:///' + output_sqlite_path     ,  num_proc=1     ).write()

       lowerCAmelCase__					     = iter_sql_file(lowerCAmelCase__     )
       lowerCAmelCase__					     = iter_sql_file(lowerCAmelCase__     )

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






@require_sqlalchemy
def 				__lowerCamelCase		(						lowerCAmelCase__     ,  lowerCAmelCase__     ,  lowerCAmelCase__     ):
       lowerCAmelCase__					     = tmp_path / 'cache'
       lowerCAmelCase__					     = os.path.join(lowerCAmelCase__     ,  'tmp.sql'     )
       lowerCAmelCase__					     = SqlDatasetReader('dataset'     ,  'sqlite:///' + sqlite_path     ,  cache_dir=lowerCAmelCase__     ).read()
       SqlDatasetWriter(lowerCAmelCase__     ,  'dataset'     ,  'sqlite:///' + output_sqlite_path     ,  num_proc=2     ).write()

       lowerCAmelCase__					     = iter_sql_file(lowerCAmelCase__     )
       lowerCAmelCase__					     = iter_sql_file(lowerCAmelCase__     )

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






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

from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


if is_sentencepiece_available():
    from ..ta.tokenization_ta import TaTokenizer
else:
    from ...utils.dummy_sentencepiece_objects import TaTokenizer

lowerCAmelCase__     						=			TaTokenizer

if is_tokenizers_available():
    from ..ta.tokenization_ta_fast import TaTokenizerFast
else:
    from ...utils.dummy_tokenizers_objects import TaTokenizerFast

lowerCAmelCase__     						=			TaTokenizerFast

lowerCAmelCase__     						=			{'configuration_mt5': ['MT5Config', 'MT5OnnxConfig']}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase__     						=			[
        'MT5EncoderModel',
        'MT5ForConditionalGeneration',
        'MT5ForQuestionAnswering',
        'MT5Model',
        'MT5PreTrainedModel',
        'MT5Stack',
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase__     						=			['TFMT5EncoderModel', 'TFMT5ForConditionalGeneration', 'TFMT5Model']

try:
    if not is_flax_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase__     						=			['FlaxMT5EncoderModel', 'FlaxMT5ForConditionalGeneration', 'FlaxMT5Model']


if TYPE_CHECKING:
    from .configuration_mta import MTaConfig, MTaOnnxConfig

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_mta import (
            MTaEncoderModel,
            MTaForConditionalGeneration,
            MTaForQuestionAnswering,
            MTaModel,
            MTaPreTrainedModel,
            MTaStack,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_mta import TFMTaEncoderModel, TFMTaForConditionalGeneration, TFMTaModel

    try:
        if not is_flax_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_flax_mta import FlaxMTaEncoderModel, FlaxMTaForConditionalGeneration, FlaxMTaModel

else:
    import sys

    lowerCAmelCase__     						=			_LazyModule(
        __name__,
        globals()['__file__'],
        _import_structure,
        extra_objects={'MT5Tokenizer': MTaTokenizer, 'MT5TokenizerFast': MTaTokenizerFast},
        module_spec=__spec__,
    )
