





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

SCREAMING_SNAKE_CASE__       :			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

SCREAMING_SNAKE_CASE__       :			List[str]			      =						concatenate_datasets
SCREAMING_SNAKE_CASE__       :			Optional[Any]			      =						DownloadConfig
SCREAMING_SNAKE_CASE__       :			Union[str, Any]			      =						DownloadManager
SCREAMING_SNAKE_CASE__       :			Optional[int]			      =						DownloadMode
SCREAMING_SNAKE_CASE__       :			List[str]			      =						DownloadConfig
SCREAMING_SNAKE_CASE__       :			Union[str, Any]			      =						DownloadMode
SCREAMING_SNAKE_CASE__       :			int			      =						DownloadManager

del _arrow_dataset, _utils, _deprecated_download_manager








from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


SCREAMING_SNAKE_CASE__       :			Any			      =						{"""configuration_sew""": ["""SEW_PRETRAINED_CONFIG_ARCHIVE_MAP""", """SEWConfig"""]}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  SCREAMING_SNAKE_CASE__       :			Union[str, Any]			      =						[
      """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

  SCREAMING_SNAKE_CASE__       :			Optional[int]			      =						_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

