





'''simple docstring'''






from ...utils import (
    OptionalDependencyNotAvailable,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)


try:
		if not (is_transformers_available() and is_torch_available() and is_transformers_version('>=', '4.27.0')):
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		from ...utils.dummy_torch_and_transformers_objects import (
		    AudioLDMPipeline,
		)
else:
		from .pipeline_audioldm import AudioLDMPipeline












'''simple docstring'''






import csv
import os

import pytest

from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.csv import CsvDatasetReader, CsvDatasetWriter

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases





def    lowercase_   (		lowercase__					,	lowercase__    ) ->List[str]:
						assert isinstance(lowercase__					,	lowercase__    )
						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





@pytest.mark.parametrize('keep_in_memory'					,	[False, True]    )
def    lowercase_   (		lowercase__					,	lowercase__					,	lowercase__    ) ->str:
						_snake_case: Optional[int]	       =		tmp_path / 'cache'
						_snake_case: int	       =		{'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
						with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
												_snake_case: Any	       =		CsvDatasetReader(lowercase__					,	cache_dir=lowercase__					,	keep_in_memory=lowercase__    ).read()
						_check_csv_dataset(lowercase__					,	lowercase__    )





@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    lowercase_   (		lowercase__					,	lowercase__					,	lowercase__    ) ->List[Any]:
						_snake_case: str	       =		tmp_path / 'cache'
						# CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
						_snake_case: Union[str, Any]	       =		{'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
						_snake_case: List[str]	       =		features.copy() if features else default_expected_features
						_snake_case: str	       =		(
						    Features({feature: Value(lowercase__    ) for feature, dtype in features.items()}    ) if features is not None else None
						)
						_snake_case: Optional[int]	       =		CsvDatasetReader(lowercase__					,	features=lowercase__					,	cache_dir=lowercase__    ).read()
						_check_csv_dataset(lowercase__					,	lowercase__    )





@pytest.mark.parametrize('split'					,	[None, NamedSplit('train'    ), 'train', 'test']    )
def    lowercase_   (		lowercase__					,	lowercase__					,	lowercase__    ) ->List[str]:
						_snake_case: Dict	       =		tmp_path / 'cache'
						_snake_case: int	       =		{'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
						_snake_case: str	       =		CsvDatasetReader(lowercase__					,	cache_dir=lowercase__					,	split=lowercase__    ).read()
						_check_csv_dataset(lowercase__					,	lowercase__    )
						assert dataset.split == split if split else "train"





@pytest.mark.parametrize('path_type'					,	[str, list]    )
def    lowercase_   (		lowercase__					,	lowercase__					,	lowercase__    ) ->List[str]:
						if issubclass(lowercase__					,	lowercase__    ):
												_snake_case: Optional[Any]	       =		csv_path
						elif issubclass(lowercase__					,	lowercase__    ):
												_snake_case: Tuple	       =		[csv_path]
						_snake_case: Tuple	       =		tmp_path / 'cache'
						_snake_case: Any	       =		{'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
						_snake_case: Union[str, Any]	       =		CsvDatasetReader(lowercase__					,	cache_dir=lowercase__    ).read()
						_check_csv_dataset(lowercase__					,	lowercase__    )





def    lowercase_   (		lowercase__					,	lowercase__					,	lowercase__=("train",)    ) ->str:
						assert isinstance(lowercase__					,	lowercase__    )
						for split in splits:
												_snake_case: Optional[int]	       =		dataset_dict[split]
												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





@pytest.mark.parametrize('keep_in_memory'					,	[False, True]    )
def    lowercase_   (		lowercase__					,	lowercase__					,	lowercase__    ) ->Optional[int]:
						_snake_case: Optional[Any]	       =		tmp_path / 'cache'
						_snake_case: Optional[Any]	       =		{'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
						with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
												_snake_case: Dict	       =		CsvDatasetReader({'train': csv_path}					,	cache_dir=lowercase__					,	keep_in_memory=lowercase__    ).read()
						_check_csv_datasetdict(lowercase__					,	lowercase__    )





@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    lowercase_   (		lowercase__					,	lowercase__					,	lowercase__    ) ->Optional[int]:
						_snake_case: List[str]	       =		tmp_path / 'cache'
						# CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
						_snake_case: str	       =		{'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
						_snake_case: str	       =		features.copy() if features else default_expected_features
						_snake_case: int	       =		(
						    Features({feature: Value(lowercase__    ) for feature, dtype in features.items()}    ) if features is not None else None
						)
						_snake_case: Tuple	       =		CsvDatasetReader({'train': csv_path}					,	features=lowercase__					,	cache_dir=lowercase__    ).read()
						_check_csv_datasetdict(lowercase__					,	lowercase__    )





@pytest.mark.parametrize('split'					,	[None, NamedSplit('train'    ), 'train', 'test']    )
def    lowercase_   (		lowercase__					,	lowercase__					,	lowercase__    ) ->List[Any]:
						if split:
												_snake_case: Optional[Any]	       =		{split: csv_path}
						else:
												_snake_case: Tuple	       =		{'train': csv_path, 'test': csv_path}
						_snake_case: Union[str, Any]	       =		tmp_path / 'cache'
						_snake_case: Dict	       =		{'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
						_snake_case: Any	       =		CsvDatasetReader(lowercase__					,	cache_dir=lowercase__    ).read()
						_check_csv_datasetdict(lowercase__					,	lowercase__					,	splits=list(path.keys()    )    )
						assert all(dataset[split].split == split for split in path.keys()    )





def    lowercase_   (		lowercase__    ) ->Union[str, Any]:
						with open(lowercase__					,	encoding='utf-8'    ) as csvfile:
												yield from csv.reader(lowercase__    )





def    lowercase_   (		lowercase__					,	lowercase__    ) ->str:
						_snake_case: List[Any]	       =		tmp_path / 'cache'
						_snake_case: Dict	       =		os.path.join(lowercase__					,	'tmp.csv'    )
						_snake_case: Optional[Any]	       =		CsvDatasetReader({'train': csv_path}					,	cache_dir=lowercase__    ).read()
						CsvDatasetWriter(dataset['train']					,	lowercase__					,	num_proc=1    ).write()

						_snake_case: Optional[int]	       =		iter_csv_file(lowercase__    )
						_snake_case: List[Any]	       =		iter_csv_file(lowercase__    )

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





def    lowercase_   (		lowercase__					,	lowercase__    ) ->str:
						_snake_case: List[str]	       =		tmp_path / 'cache'
						_snake_case: List[str]	       =		os.path.join(lowercase__					,	'tmp.csv'    )
						_snake_case: List[str]	       =		CsvDatasetReader({'train': csv_path}					,	cache_dir=lowercase__    ).read()
						CsvDatasetWriter(dataset['train']					,	lowercase__					,	num_proc=2    ).write()

						_snake_case: Optional[Any]	       =		iter_csv_file(lowercase__    )
						_snake_case: Tuple	       =		iter_csv_file(lowercase__    )

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





def    lowercase_   (		lowercase__					,	lowercase__    ) ->Any:
						_snake_case: Optional[int]	       =		tmp_path / 'cache'
						_snake_case: Any	       =		os.path.join(lowercase__					,	'tmp.csv'    )
						_snake_case: str	       =		CsvDatasetReader({'train': csv_path}					,	cache_dir=lowercase__    ).read()
						with pytest.raises(lowercase__    ):
												CsvDatasetWriter(dataset['train']					,	lowercase__					,	num_proc=0    )





