




import pytest

import datasets


# Import fixture modules as plugins
snake_case_ : Tuple    		=       ["tests.fixtures.files", "tests.fixtures.hub", "tests.fixtures.fsspec"]


def    A						(__A   :    Optional[int]   ,				__A   :    Any       )   ->      Optional[int]:







     """simple docstring"""


     for item in items:
          if any(marker in item.keywords for marker in ['''integration''', '''unit''']       ):
               continue
          item.add_marker(pytest.mark.unit       )


def    A						(__A   :    Optional[Any]       )   ->      Optional[int]:







     """simple docstring"""


     config.addinivalue_line('''markers'''   ,				'''torchaudio_latest: mark test to run with torchaudio>=0.12'''       )


@pytest.fixture(autouse=__A       )
def    A						(__A   :    Optional[int]   ,				__A   :    Dict       )   ->      List[Any]:







     """simple docstring"""


     UpperCAmelCase_          =							tmp_path_factory.getbasetemp() / '''cache'''
     UpperCAmelCase_          =							test_hf_cache_home / '''datasets'''
     UpperCAmelCase_          =							test_hf_cache_home / '''metrics'''
     UpperCAmelCase_          =							test_hf_cache_home / '''modules'''
     monkeypatch.setattr('''datasets.config.HF_DATASETS_CACHE'''   ,				str(__A       )       )
     monkeypatch.setattr('''datasets.config.HF_METRICS_CACHE'''   ,				str(__A       )       )
     monkeypatch.setattr('''datasets.config.HF_MODULES_CACHE'''   ,				str(__A       )       )
     UpperCAmelCase_          =							test_hf_datasets_cache / '''downloads'''
     monkeypatch.setattr('''datasets.config.DOWNLOADED_DATASETS_PATH'''   ,				str(__A       )       )
     UpperCAmelCase_          =							test_hf_datasets_cache / '''downloads''' / '''extracted'''
     monkeypatch.setattr('''datasets.config.EXTRACTED_DATASETS_PATH'''   ,				str(__A       )       )


@pytest.fixture(autouse=__A   ,				scope='''session'''       )
def    A						()   ->      Dict:







     """simple docstring"""


     datasets.disable_progress_bar()


@pytest.fixture(autouse=__A       )
def    A						(__A   :    Tuple       )   ->      str:







     """simple docstring"""


     monkeypatch.setattr('''datasets.config.HF_UPDATE_DOWNLOAD_COUNTS'''   ,				__A       )


@pytest.fixture
def    A						(__A   :    Union[str, Any]       )   ->      int:







     """simple docstring"""


     monkeypatch.setattr('''sqlalchemy.util.deprecations.SILENCE_UBER_WARNING'''   ,				__A       )








from typing import List, Optional, TypeVar

from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableDataset, _concatenate_iterable_datasets, _interleave_iterable_datasets
from .splits import NamedSplit
from .utils import logging
from .utils.py_utils import Literal


_A   =     logging.get_logger(__name__)


_A   =     TypeVar("DatasetType", Dataset, IterableDataset)






def    lowerCamelCase__				(				__lowerCAmelCase  :  List[DatasetType]    ,							__lowerCAmelCase  :  Optional[List[float]] = None    ,							__lowerCAmelCase  :  Optional[int] = None    ,							__lowerCAmelCase  :  Optional[DatasetInfo] = None    ,							__lowerCAmelCase  :  Optional[NamedSplit] = None    ,							__lowerCAmelCase  :  Literal["first_exhausted", "all_exhausted"] = "first_exhausted"    ,							):




			"""simple docstring"""


			from .arrow_dataset import Dataset
			from .iterable_dataset import IterableDataset

			if not datasets:
						raise ValueError("Unable to interleave an empty list of datasets."				)
			for i, dataset in enumerate(__lowerCAmelCase				):
						if not isinstance(__lowerCAmelCase    ,							(Dataset, IterableDataset)				):
									if isinstance(__lowerCAmelCase    ,							(DatasetDict, IterableDatasetDict)				):
												if not dataset:
															raise ValueError(
															    F"""Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} """
															    "is an empty dataset dictionary."				)
												raise ValueError(
												    F"""Dataset at position {i} has at least one split: {list(__lowerCAmelCase				)}\n"""
												    F"""Please pick one to interleave with the other datasets, for example: dataset['{next(iter(__lowerCAmelCase				)				)}']"""				)
									raise ValueError(
									    F"""Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} is a {type(__lowerCAmelCase				).__name__}."""				)
						if i == 0:
									lowerCAmelCase_	,  lowerCAmelCase_						=	(
									    (Dataset, IterableDataset) if isinstance(__lowerCAmelCase    ,							__lowerCAmelCase				) else (IterableDataset, Dataset)
									)
						elif not isinstance(__lowerCAmelCase    ,							__lowerCAmelCase				):
									raise ValueError(
									    F"""Unable to interleave a {dataset_type.__name__} (at position 0) with a {other_type.__name__} (at position {i}). Expected a list of Dataset objects or a list of IterableDataset objects."""				)
			if stopping_strategy not in ["first_exhausted", "all_exhausted"]:
						raise ValueError(F"""{stopping_strategy} is not supported. Please enter a valid stopping_strategy."""				)
			if dataset_type is Dataset:
						return _interleave_map_style_datasets(
						    __lowerCAmelCase    ,							__lowerCAmelCase    ,							__lowerCAmelCase    ,							info=__lowerCAmelCase    ,							split=__lowerCAmelCase    ,							stopping_strategy=__lowerCAmelCase				)
			else:
						return _interleave_iterable_datasets(
						    __lowerCAmelCase    ,							__lowerCAmelCase    ,							__lowerCAmelCase    ,							info=__lowerCAmelCase    ,							split=__lowerCAmelCase    ,							stopping_strategy=__lowerCAmelCase				)






def    lowerCamelCase__				(				__lowerCAmelCase  :  List[DatasetType]    ,							__lowerCAmelCase  :  Optional[DatasetInfo] = None    ,							__lowerCAmelCase  :  Optional[NamedSplit] = None    ,							__lowerCAmelCase  :  int = 0    ,							):




			"""simple docstring"""


			if not dsets:
						raise ValueError("Unable to concatenate an empty list of datasets."				)
			for i, dataset in enumerate(__lowerCAmelCase				):
						if not isinstance(__lowerCAmelCase    ,							(Dataset, IterableDataset)				):
									if isinstance(__lowerCAmelCase    ,							(DatasetDict, IterableDatasetDict)				):
												if not dataset:
															raise ValueError(
															    F"""Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} """
															    "is an empty dataset dictionary."				)
												raise ValueError(
												    F"""Dataset at position {i} has at least one split: {list(__lowerCAmelCase				)}\n"""
												    F"""Please pick one to interleave with the other datasets, for example: dataset['{next(iter(__lowerCAmelCase				)				)}']"""				)
									raise ValueError(
									    F"""Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} is a {type(__lowerCAmelCase				).__name__}."""				)
						if i == 0:
									lowerCAmelCase_	,  lowerCAmelCase_						=	(
									    (Dataset, IterableDataset) if isinstance(__lowerCAmelCase    ,							__lowerCAmelCase				) else (IterableDataset, Dataset)
									)
						elif not isinstance(__lowerCAmelCase    ,							__lowerCAmelCase				):
									raise ValueError(
									    F"""Unable to interleave a {dataset_type.__name__} (at position 0) with a {other_type.__name__} (at position {i}). Expected a list of Dataset objects or a list of IterableDataset objects."""				)
			if dataset_type is Dataset:
						return _concatenate_map_style_datasets(__lowerCAmelCase    ,							info=__lowerCAmelCase    ,							split=__lowerCAmelCase    ,							axis=__lowerCAmelCase				)
			else:
						return _concatenate_iterable_datasets(__lowerCAmelCase    ,							info=__lowerCAmelCase    ,							split=__lowerCAmelCase    ,							axis=__lowerCAmelCase				)



