


import pytest
import requests

from datasets.utils.file_utils import http_head

from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline





@pytest.mark.integration
def   _UpperCAmelCase       (     ):
      """simple docstring"""




      with offline(OfflineSimulationMode.CONNECTION_TIMES_OUT      ):
            with pytest.raises(UpperCAmelCase      ):
                  requests.request("""GET"""						,	"""https://huggingface.co"""      )
            with pytest.raises(requests.exceptions.ConnectTimeout      ):
                  requests.request("""GET"""						,	"""https://huggingface.co"""						,	timeout=1.0      )





@pytest.mark.integration
def   _UpperCAmelCase       (     ):
      """simple docstring"""




      with offline(OfflineSimulationMode.CONNECTION_FAILS      ):
            with pytest.raises(requests.exceptions.ConnectionError      ):
                  requests.request("""GET"""						,	"""https://huggingface.co"""      )





def   _UpperCAmelCase       (     ):
      """simple docstring"""




      with offline(OfflineSimulationMode.HF_DATASETS_OFFLINE_SET_TO_1      ):
            with pytest.raises(UpperCAmelCase      ):
                  http_head("""https://huggingface.co"""      )







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__UpperCamelCase    :						Optional[Any]     =							{
    'configuration_swinv2': ['SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Swinv2Config'],
}


try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __UpperCamelCase    :						List[Any]     =							[
        'SWINV2_PRETRAINED_MODEL_ARCHIVE_LIST',
        'Swinv2ForImageClassification',
        'Swinv2ForMaskedImageModeling',
        'Swinv2Model',
        'Swinv2PreTrainedModel',
    ]


if TYPE_CHECKING:
    from .configuration_swinva import SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP, SwinvaConfig

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_swinva import (
            SWINV2_PRETRAINED_MODEL_ARCHIVE_LIST,
            SwinvaForImageClassification,
            SwinvaForMaskedImageModeling,
            SwinvaModel,
            SwinvaPreTrainedModel,
        )


else:
    import sys

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



