



'''simple docstring'''
from __future__ import annotations



def 		_SCREAMING_SNAKE_CASE							(				lowerCamelCase__   :      list[int | float]				):


   '''simple docstring'''







   if len(lowerCamelCase__				) == 0:
      raise ValueError("""find_min() arg is an empty sequence"""				)
   A:      List[str]														=   nums[0]
   for num in nums:
      A:      Optional[Any]														=   min(lowerCamelCase__							,							lowerCamelCase__				)
   return min_num


if __name__ == "__main__":
     import doctest

     doctest.testmod(verbose=True)










'''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__)





