



'''simple docstring'''
import unittest
import warnings

from datasets.utils import experimental



@experimental
def 		_SCREAMING_SNAKE_CASE							(				):


			'''simple docstring'''







			return "success"


class   SCREAMING_SNAKE_CASE__				(   unittest.TestCase					):
	"""simple docstring"""


	def      a__ (		self			) ->							Optional[Any]:
				with warnings.catch_warnings(record=A			) as w:
							warnings.simplefilter("""always"""			)
							self.assertEqual(dummy_function()					,   """success"""			)
				self.assertEqual(len(A			)					,   1			)










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

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


__SCREAMING_SNAKE_CASE :      Dict             ={
    'configuration_nystromformer': ['NYSTROMFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'NystromformerConfig'],
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__SCREAMING_SNAKE_CASE :      Dict             =[
					    'NYSTROMFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'NystromformerForMaskedLM',
					    'NystromformerForMultipleChoice',
					    'NystromformerForQuestionAnswering',
					    'NystromformerForSequenceClassification',
					    'NystromformerForTokenClassification',
					    'NystromformerLayer',
					    'NystromformerModel',
					    'NystromformerPreTrainedModel',
					]


if TYPE_CHECKING:
					from .configuration_nystromformer import NYSTROMFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, NystromformerConfig

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_nystromformer import (
										    NYSTROMFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
										    NystromformerForMaskedLM,
										    NystromformerForMultipleChoice,
										    NystromformerForQuestionAnswering,
										    NystromformerForSequenceClassification,
										    NystromformerForTokenClassification,
										    NystromformerLayer,
										    NystromformerModel,
										    NystromformerPreTrainedModel,
										)


else:
					import sys

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





