# 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 :	Union[str, 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[Any]							     =		concatenate_datasets
SCREAMING_SNAKE_CASE :	Union[str, Any]							     =		DownloadConfig
SCREAMING_SNAKE_CASE :	Dict							     =		DownloadManager
SCREAMING_SNAKE_CASE :	Optional[Any]							     =		DownloadMode
SCREAMING_SNAKE_CASE :	List[str]							     =		DownloadConfig
SCREAMING_SNAKE_CASE :	Optional[int]							     =		DownloadMode
SCREAMING_SNAKE_CASE :	List[Any]							     =		DownloadManager

del _arrow_dataset, _utils, _deprecated_download_manager



import pytest

import datasets.config
from datasets.utils.info_utils import is_small_dataset



@pytest.mark.parametrize("dataset_size"							,				[None, 400 * 2**20, 600 * 2**20]					)
@pytest.mark.parametrize("input_in_memory_max_size"							,				["default", 0, 100 * 2**20, 900 * 2**20]					)
def   __A		(			_A							,				_A							,				_A					):



 """simple docstring"""


 if input_in_memory_max_size != "default":
  monkeypatch.setattr(datasets.config							,				"IN_MEMORY_MAX_SIZE"							,				_A					)
 __a       =  datasets.config.IN_MEMORY_MAX_SIZE
 if input_in_memory_max_size == "default":
  assert in_memory_max_size == 0
 else:
  assert in_memory_max_size == input_in_memory_max_size
 if dataset_size and in_memory_max_size:
  __a       =  dataset_size < in_memory_max_size
 else:
  __a       =  False
 __a       =  is_small_dataset(_A					)
 assert result == expected


