


'''simple docstring'''

from typing import TYPE_CHECKING

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


lowercase__				     =		{
    "configuration_gpt_neo": ["GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTNeoConfig", "GPTNeoOnnxConfig"],
}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowercase__				     =		[
       "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:
   lowercase__				     =		[
       "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

   lowercase__				     =		_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





'''simple docstring'''

def __UpperCamelCase   (			__lowerCamelCase		: int = 400_0000				)      ->     int:







     '''simple docstring'''






     _a						=		[]
     _a			,			_a						=		0, 1
     while b <= n:
          if b % 2 == 0:
               even_fibs.append(__lowerCamelCase				)
          _a			,			_a						=		b, a + b
     return sum(__lowerCamelCase				)


if __name__ == "__main__":
   print(f'''{solution() = }''')

