
"""simple docstring"""





# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position

UpperCamelCase_       :    Optional[Any]						      =			'''2.13.1'''

import platform

import pyarrow
from packaging import version


if version.parse(platform.python_version()) < version.parse('''3.7'''):
		raise ImportWarning(
		    '''To use `datasets`, Python>=3.7 is required, and the current version of Python doesn\'t match this condition.'''
		)

if version.parse(pyarrow.__version__).major < 8:
		raise ImportWarning(
		    '''To use `datasets`, the module `pyarrow>=8.0.0` is required, and the current version of `pyarrow` doesn\'t match this condition.\n'''
		    '''If you are running this in a Google Colab, you should probably just restart the runtime to use the right version of `pyarrow`.'''
		)

del platform
del pyarrow
del version

from .arrow_dataset import Dataset
from .arrow_reader import ReadInstruction
from .builder import ArrowBasedBuilder, BeamBasedBuilder, BuilderConfig, DatasetBuilder, GeneratorBasedBuilder
from .combine import concatenate_datasets, interleave_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .download import *
from .features import *
from .fingerprint import disable_caching, enable_caching, is_caching_enabled, set_caching_enabled
from .info import DatasetInfo, MetricInfo
from .inspect import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
    list_datasets,
    list_metrics,
)
from .iterable_dataset import IterableDataset
from .load import load_dataset, load_dataset_builder, load_from_disk, load_metric
from .metric import Metric
from .splits import (
    NamedSplit,
    NamedSplitAll,
    Split,
    SplitBase,
    SplitDict,
    SplitGenerator,
    SplitInfo,
    SubSplitInfo,
    percent,
)
from .tasks import *
from .utils import *
from .utils import logging


# deprecated modules
from datasets import arrow_dataset as _arrow_dataset  # isort:skip
from datasets import utils as _utils  # isort:skip
from datasets.utils import download_manager as _deprecated_download_manager  # isort:skip

UpperCamelCase_       :    Tuple						      =			concatenate_datasets
UpperCamelCase_       :    Optional[int]						      =			DownloadConfig
UpperCamelCase_       :    str						      =			DownloadManager
UpperCamelCase_       :    int						      =			DownloadMode
UpperCamelCase_       :    List[str]						      =			DownloadConfig
UpperCamelCase_       :    Optional[Any]						      =			DownloadMode
UpperCamelCase_       :    Optional[Any]						      =			DownloadManager

del _arrow_dataset, _utils, _deprecated_download_manager






"""simple docstring"""





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCamelCase_       :    List[str]						      =			{'''configuration_sew''': ['''SEW_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''SEWConfig''']}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		UpperCamelCase_       :    Tuple						      =			[
		    '''SEW_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''SEWForCTC''',
		    '''SEWForSequenceClassification''',
		    '''SEWModel''',
		    '''SEWPreTrainedModel''',
		]

if TYPE_CHECKING:
		from .configuration_sew import SEW_PRETRAINED_CONFIG_ARCHIVE_MAP, SEWConfig

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_sew import (
				    SEW_PRETRAINED_MODEL_ARCHIVE_LIST,
				    SEWForCTC,
				    SEWForSequenceClassification,
				    SEWModel,
				    SEWPreTrainedModel,
				)


else:
		import sys

		UpperCamelCase_       :    List[str]						      =			_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




