


'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


__SCREAMING_SNAKE_CASE					:				Any									=		{
    '''configuration_tapas''': ['''TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''TapasConfig'''],
    '''tokenization_tapas''': ['''TapasTokenizer'''],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__SCREAMING_SNAKE_CASE					:				Any									=		[
							    '''TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''TapasForMaskedLM''',
							    '''TapasForQuestionAnswering''',
							    '''TapasForSequenceClassification''',
							    '''TapasModel''',
							    '''TapasPreTrainedModel''',
							    '''load_tf_weights_in_tapas''',
							]
try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__SCREAMING_SNAKE_CASE					:				str									=		[
							    '''TF_TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''TFTapasForMaskedLM''',
							    '''TFTapasForQuestionAnswering''',
							    '''TFTapasForSequenceClassification''',
							    '''TFTapasModel''',
							    '''TFTapasPreTrainedModel''',
							]


if TYPE_CHECKING:
							from .configuration_tapas import TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP, TapasConfig
							from .tokenization_tapas import TapasTokenizer

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tapas import (
														    TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST,
														    TapasForMaskedLM,
														    TapasForQuestionAnswering,
														    TapasForSequenceClassification,
														    TapasModel,
														    TapasPreTrainedModel,
														    load_tf_weights_in_tapas,
														)

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_tapas import (
														    TF_TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST,
														    TFTapasForMaskedLM,
														    TFTapasForQuestionAnswering,
														    TFTapasForSequenceClassification,
														    TFTapasModel,
														    TFTapasPreTrainedModel,
														)


else:
							import sys

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









'''simple docstring'''
import pytest
import requests

from datasets.utils.file_utils import http_head

from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline







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







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





