'''simple docstring'''

import pytest
import requests

from datasets.utils.file_utils import http_head

from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def 			__UpperCamelCase       (   ):
 with offline(OfflineSimulationMode.CONNECTION_TIMES_OUT     ):
  with pytest.raises(snake_case__     ):
   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       (   ):
 with offline(OfflineSimulationMode.CONNECTION_FAILS     ):
  with pytest.raises(requests.exceptions.ConnectionError     ):
   requests.request('''GET'''		,     '''https://huggingface.co'''     )





def 			__UpperCamelCase       (   ):
 with offline(OfflineSimulationMode.HF_DATASETS_OFFLINE_SET_TO_1     ):
  with pytest.raises(snake_case__     ):
   http_head('''https://huggingface.co'''     )






from typing import TYPE_CHECKING

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


__UpperCAmelCase          =       {
    '''configuration_transfo_xl''': ['''TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''TransfoXLConfig'''],
    '''tokenization_transfo_xl''': ['''TransfoXLCorpus''', '''TransfoXLTokenizer'''],
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __UpperCAmelCase          =       [
        '''TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''AdaptiveEmbedding''',
        '''TransfoXLForSequenceClassification''',
        '''TransfoXLLMHeadModel''',
        '''TransfoXLModel''',
        '''TransfoXLPreTrainedModel''',
        '''load_tf_weights_in_transfo_xl''',
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __UpperCAmelCase          =       [
        '''TF_TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''TFAdaptiveEmbedding''',
        '''TFTransfoXLForSequenceClassification''',
        '''TFTransfoXLLMHeadModel''',
        '''TFTransfoXLMainLayer''',
        '''TFTransfoXLModel''',
        '''TFTransfoXLPreTrainedModel''',
    ]


if TYPE_CHECKING:
    from .configuration_transfo_xl import TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP, TransfoXLConfig
    from .tokenization_transfo_xl import TransfoXLCorpus, TransfoXLTokenizer

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_transfo_xl import (
            TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST,
            AdaptiveEmbedding,
            TransfoXLForSequenceClassification,
            TransfoXLLMHeadModel,
            TransfoXLModel,
            TransfoXLPreTrainedModel,
            load_tf_weights_in_transfo_xl,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_transfo_xl import (
            TF_TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFAdaptiveEmbedding,
            TFTransfoXLForSequenceClassification,
            TFTransfoXLLMHeadModel,
            TFTransfoXLMainLayer,
            TFTransfoXLModel,
            TFTransfoXLPreTrainedModel,
        )

else:
    import sys

    __UpperCAmelCase          =       _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



