

'''simple docstring'''






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


lowerCAmelCase__											=	{
    '''configuration_roberta''': ['''ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''RobertaConfig''', '''RobertaOnnxConfig'''],
    '''tokenization_roberta''': ['''RobertaTokenizer'''],
}

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase__											=	['''RobertaTokenizerFast''']

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase__											=	[
     '''ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''RobertaForCausalLM''',
     '''RobertaForMaskedLM''',
     '''RobertaForMultipleChoice''',
     '''RobertaForQuestionAnswering''',
     '''RobertaForSequenceClassification''',
     '''RobertaForTokenClassification''',
     '''RobertaModel''',
     '''RobertaPreTrainedModel''',
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase__											=	[
     '''TF_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''TFRobertaForCausalLM''',
     '''TFRobertaForMaskedLM''',
     '''TFRobertaForMultipleChoice''',
     '''TFRobertaForQuestionAnswering''',
     '''TFRobertaForSequenceClassification''',
     '''TFRobertaForTokenClassification''',
     '''TFRobertaMainLayer''',
     '''TFRobertaModel''',
     '''TFRobertaPreTrainedModel''',
 ]

try:
 if not is_flax_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase__											=	[
     '''FlaxRobertaForCausalLM''',
     '''FlaxRobertaForMaskedLM''',
     '''FlaxRobertaForMultipleChoice''',
     '''FlaxRobertaForQuestionAnswering''',
     '''FlaxRobertaForSequenceClassification''',
     '''FlaxRobertaForTokenClassification''',
     '''FlaxRobertaModel''',
     '''FlaxRobertaPreTrainedModel''',
 ]


if TYPE_CHECKING:
 from .configuration_roberta import ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP, RobertaConfig, RobertaOnnxConfig
 from .tokenization_roberta import RobertaTokenizer

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_roberta_fast import RobertaTokenizerFast

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_roberta import (
      ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST,
      RobertaForCausalLM,
      RobertaForMaskedLM,
      RobertaForMultipleChoice,
      RobertaForQuestionAnswering,
      RobertaForSequenceClassification,
      RobertaForTokenClassification,
      RobertaModel,
      RobertaPreTrainedModel,
  )

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_roberta import (
      TF_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST,
      TFRobertaForCausalLM,
      TFRobertaForMaskedLM,
      TFRobertaForMultipleChoice,
      TFRobertaForQuestionAnswering,
      TFRobertaForSequenceClassification,
      TFRobertaForTokenClassification,
      TFRobertaMainLayer,
      TFRobertaModel,
      TFRobertaPreTrainedModel,
  )

 try:
  if not is_flax_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_flax_roberta import (
      FlaxRobertaForCausalLM,
      FlaxRobertaForMaskedLM,
      FlaxRobertaForMultipleChoice,
      FlaxRobertaForQuestionAnswering,
      FlaxRobertaForSequenceClassification,
      FlaxRobertaForTokenClassification,
      FlaxRobertaModel,
      FlaxRobertaPreTrainedModel,
  )

else:
 import sys

 lowerCAmelCase__											=	_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     (    ):






 """simple docstring"""



 with offline(OfflineSimulationMode.CONNECTION_TIMES_OUT      ):
  with pytest.raises(A__      ):
   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     (    ):






 """simple docstring"""



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






def 		_A     (    ):






 """simple docstring"""



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

