

from typing import TYPE_CHECKING

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


lowerCAmelCase_			      =      {
    '''configuration_gpt_bigcode''': ['''GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTBigCodeConfig'''],
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase_			      =      [
					    '''GPT_BIGCODE_PRETRAINED_MODEL_ARCHIVE_LIST''',
					    '''GPTBigCodeForSequenceClassification''',
					    '''GPTBigCodeForTokenClassification''',
					    '''GPTBigCodeForCausalLM''',
					    '''GPTBigCodeModel''',
					    '''GPTBigCodePreTrainedModel''',
					]

if TYPE_CHECKING:
					from .configuration_gpt_bigcode import GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTBigCodeConfig

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_gpt_bigcode import (
										    GPT_BIGCODE_PRETRAINED_MODEL_ARCHIVE_LIST,
										    GPTBigCodeForCausalLM,
										    GPTBigCodeForSequenceClassification,
										    GPTBigCodeForTokenClassification,
										    GPTBigCodeModel,
										    GPTBigCodePreTrainedModel,
										)


else:
					import sys

					lowerCAmelCase_			      =      _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




def 	SCREAMING_SNAKE_CASE_							(	_snake_case	:int				)  ->     int:
   if not isinstance(_snake_case	,   _snake_case				):
      raise ValueError('''Input must be an integer'''				)
   if input_num <= 0:
      raise ValueError('''Input must be positive'''				)
   return sum(
       divisor for divisor in range(1	,   input_num // 2 + 1				) if input_num % divisor == 0				)


if __name__ == "__main__":
   import doctest

   doctest.testmod()



