






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

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


UpperCamelCase__ =			{
    'configuration_gpt_neo': ['GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GPTNeoConfig', 'GPTNeoOnnxConfig'],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 UpperCamelCase__ =			[
     'GPT_NEO_PRETRAINED_MODEL_ARCHIVE_LIST',
     'GPTNeoForCausalLM',
     'GPTNeoForQuestionAnswering',
     'GPTNeoForSequenceClassification',
     'GPTNeoForTokenClassification',
     'GPTNeoModel',
     'GPTNeoPreTrainedModel',
     'load_tf_weights_in_gpt_neo',
 ]

try:
 if not is_flax_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 UpperCamelCase__ =			[
     'FlaxGPTNeoForCausalLM',
     'FlaxGPTNeoModel',
     'FlaxGPTNeoPreTrainedModel',
 ]


if TYPE_CHECKING:
 from .configuration_gpt_neo import GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoConfig, GPTNeoOnnxConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_gpt_neo import (
      GPT_NEO_PRETRAINED_MODEL_ARCHIVE_LIST,
      GPTNeoForCausalLM,
      GPTNeoForQuestionAnswering,
      GPTNeoForSequenceClassification,
      GPTNeoForTokenClassification,
      GPTNeoModel,
      GPTNeoPreTrainedModel,
      load_tf_weights_in_gpt_neo,
  )

 try:
  if not is_flax_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_flax_gpt_neo import FlaxGPTNeoForCausalLM, FlaxGPTNeoModel, FlaxGPTNeoPreTrainedModel


else:
 import sys

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












'''simple docstring'''
def 		__SCREAMING_SNAKE_CASE					(  _UpperCamelCase							):


   """simple docstring"""




   if number < 0:
      raise ValueError("number must not be negative"							)
   return number & (number - 1) == 0


if __name__ == "__main__":
 import doctest

 doctest.testmod()




