





from typing import TYPE_CHECKING

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


lowerCAmelCase_   =   {"configuration_gptj": ["GPTJ_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTJConfig", "GPTJOnnxConfig"]}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCAmelCase_   =   [
         "GPTJ_PRETRAINED_MODEL_ARCHIVE_LIST",
         "GPTJForCausalLM",
         "GPTJForQuestionAnswering",
         "GPTJForSequenceClassification",
         "GPTJModel",
         "GPTJPreTrainedModel",
     ]

try:
     if not is_tf_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCAmelCase_   =   [
         "TFGPTJForCausalLM",
         "TFGPTJForQuestionAnswering",
         "TFGPTJForSequenceClassification",
         "TFGPTJModel",
         "TFGPTJPreTrainedModel",
     ]

try:
     if not is_flax_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCAmelCase_   =   [
         "FlaxGPTJForCausalLM",
         "FlaxGPTJModel",
         "FlaxGPTJPreTrainedModel",
     ]


if TYPE_CHECKING:
     from .configuration_gptj import GPTJ_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTJConfig, GPTJOnnxConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_gptj import (
              GPTJ_PRETRAINED_MODEL_ARCHIVE_LIST,
              GPTJForCausalLM,
              GPTJForQuestionAnswering,
              GPTJForSequenceClassification,
              GPTJModel,
              GPTJPreTrainedModel,
          )

     try:
          if not is_tf_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_tf_gptj import (
              TFGPTJForCausalLM,
              TFGPTJForQuestionAnswering,
              TFGPTJForSequenceClassification,
              TFGPTJModel,
              TFGPTJPreTrainedModel,
          )

     try:
          if not is_flax_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_flax_gptj import FlaxGPTJForCausalLM, FlaxGPTJModel, FlaxGPTJPreTrainedModel

else:
     import sys

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













def 						A_			(  lowercase_  )			->						list:
       if len(lowercase_  ) <= 1:
              return data
       else:
              return [
                  *quick_sort([e for e in data[1:] if e <= data[0]]  ),
                  data[0],
                  *quick_sort([e for e in data[1:] if e > data[0]]  ),
              ]


if __name__ == "__main__":
   import doctest

   doctest.testmod()






