



"""simple docstring"""






from typing import TYPE_CHECKING

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


__snake_case				:  Any =       {
    'configuration_convbert': ['CONVBERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ConvBertConfig', 'ConvBertOnnxConfig'],
    'tokenization_convbert': ['ConvBertTokenizer'],
}

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__snake_case				:  Any =       ['ConvBertTokenizerFast']

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__snake_case				:  Optional[Any] =       [
	    'CONVBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'ConvBertForMaskedLM',
	    'ConvBertForMultipleChoice',
	    'ConvBertForQuestionAnswering',
	    'ConvBertForSequenceClassification',
	    'ConvBertForTokenClassification',
	    'ConvBertLayer',
	    'ConvBertModel',
	    'ConvBertPreTrainedModel',
	    'load_tf_weights_in_convbert',
	]


try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__snake_case				:  List[str] =       [
	    'TF_CONVBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'TFConvBertForMaskedLM',
	    'TFConvBertForMultipleChoice',
	    'TFConvBertForQuestionAnswering',
	    'TFConvBertForSequenceClassification',
	    'TFConvBertForTokenClassification',
	    'TFConvBertLayer',
	    'TFConvBertModel',
	    'TFConvBertPreTrainedModel',
	]


if TYPE_CHECKING:
	from .configuration_convbert import CONVBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, ConvBertConfig, ConvBertOnnxConfig
	from .tokenization_convbert import ConvBertTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_convbert_fast import ConvBertTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_convbert import (
		    CONVBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    ConvBertForMaskedLM,
		    ConvBertForMultipleChoice,
		    ConvBertForQuestionAnswering,
		    ConvBertForSequenceClassification,
		    ConvBertForTokenClassification,
		    ConvBertLayer,
		    ConvBertModel,
		    ConvBertPreTrainedModel,
		    load_tf_weights_in_convbert,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_convbert import (
		    TF_CONVBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFConvBertForMaskedLM,
		    TFConvBertForMultipleChoice,
		    TFConvBertForQuestionAnswering,
		    TFConvBertForSequenceClassification,
		    TFConvBertForTokenClassification,
		    TFConvBertLayer,
		    TFConvBertModel,
		    TFConvBertPreTrainedModel,
		)


else:
	import sys

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



import pytest

import datasets


# Import fixture modules as plugins
__snake_case   							=						['''tests.fixtures.files''', '''tests.fixtures.hub''', '''tests.fixtures.fsspec''']






def 		_A		(		_lowercase					,  _lowercase )					-> Tuple:


     """simple docstring"""


     for item in items:
          if any(marker in item.keywords for marker in ['integration', 'unit'] ):
               continue
          item.add_marker(pytest.mark.unit )






def 		_A		(		_lowercase )					-> str:


     """simple docstring"""


     config.addinivalue_line('markers'					,  'torchaudio_latest: mark test to run with torchaudio>=0.12' )






@pytest.fixture(autouse=_lowercase )
def 		_A		(		_lowercase					,  _lowercase )					-> Any:


     """simple docstring"""


     __UpperCamelCase =			tmp_path_factory.getbasetemp() / 'cache'
     __UpperCamelCase =			test_hf_cache_home / 'datasets'
     __UpperCamelCase =			test_hf_cache_home / 'metrics'
     __UpperCamelCase =			test_hf_cache_home / 'modules'
     monkeypatch.setattr('datasets.config.HF_DATASETS_CACHE'					,  str(_lowercase ) )
     monkeypatch.setattr('datasets.config.HF_METRICS_CACHE'					,  str(_lowercase ) )
     monkeypatch.setattr('datasets.config.HF_MODULES_CACHE'					,  str(_lowercase ) )
     __UpperCamelCase =			test_hf_datasets_cache / 'downloads'
     monkeypatch.setattr('datasets.config.DOWNLOADED_DATASETS_PATH'					,  str(_lowercase ) )
     __UpperCamelCase =			test_hf_datasets_cache / 'downloads' / 'extracted'
     monkeypatch.setattr('datasets.config.EXTRACTED_DATASETS_PATH'					,  str(_lowercase ) )






@pytest.fixture(autouse=_lowercase					,  scope='session' )
def 		_A		(		)					-> Dict:


     """simple docstring"""


     datasets.disable_progress_bar()






@pytest.fixture(autouse=_lowercase )
def 		_A		(		_lowercase )					-> Tuple:


     """simple docstring"""


     monkeypatch.setattr('datasets.config.HF_UPDATE_DOWNLOAD_COUNTS'					,  _lowercase )






@pytest.fixture
def 		_A		(		_lowercase )					-> Any:


     """simple docstring"""


     monkeypatch.setattr('sqlalchemy.util.deprecations.SILENCE_UBER_WARNING'					,  _lowercase )


