



"""simple docstring"""






import unittest
import warnings

from datasets.utils import experimental






@experimental
def 	snake_case__  (						):
			"""simple docstring"""
			return "success"

class 			__SCREAMING_SNAKE_CASE      ( unittest.TestCase  ):


					'''simple docstring'''





					def 						snake_case			(			self				:    Tuple	)->   Tuple:
								with warnings.catch_warnings(record=lowerCamelCase	) as w:
											warnings.simplefilter('''always'''	)
											self.assertEqual(dummy_function(),    '''success'''	)
								self.assertEqual(len(lowerCamelCase	),    1	)









from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_torch_available


UpperCAmelCase__			:   Optional[int]      			=    {
    'configuration_ernie_m': ['ERNIE_M_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ErnieMConfig'],
}

try:
					if not is_sentencepiece_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCAmelCase__			:   List[Any]      			=    ['ErnieMTokenizer']

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCAmelCase__			:   Dict      			=    [
					    'ERNIE_M_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'ErnieMForMultipleChoice',
					    'ErnieMForQuestionAnswering',
					    'ErnieMForSequenceClassification',
					    'ErnieMForTokenClassification',
					    'ErnieMModel',
					    'ErnieMPreTrainedModel',
					    'ErnieMForInformationExtraction',
					]


if TYPE_CHECKING:
					from .configuration_ernie_m import ERNIE_M_PRETRAINED_CONFIG_ARCHIVE_MAP, ErnieMConfig

					try:
										if not is_sentencepiece_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_ernie_m import ErnieMTokenizer

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_ernie_m import (
										    ERNIE_M_PRETRAINED_MODEL_ARCHIVE_LIST,
										    ErnieMForInformationExtraction,
										    ErnieMForMultipleChoice,
										    ErnieMForQuestionAnswering,
										    ErnieMForSequenceClassification,
										    ErnieMForTokenClassification,
										    ErnieMModel,
										    ErnieMPreTrainedModel,
										)


else:
					import sys

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