






from typing import TYPE_CHECKING

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


snake_case    				=		{
    """configuration_gpt_bigcode""": ["""GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTBigCodeConfig"""],
}

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

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














from ..utils import DummyObject, requires_backends


class  SCREAMING_SNAKE_CASE			(			metaclass=lowerCAmelCase					):
     '''simple docstring'''


     UpperCamelCase_							:		Union[str, Any]			=	['''keras_nlp''']


     def __init__(				self       :	Dict					, *UpperCAmelCase_       :	Optional[Any]					, **UpperCAmelCase_       :	Dict      ):
       requires_backends(self					, ["keras_nlp"]      )






