






'''simple docstring'''




from ..utils import DummyObject, requires_backends







class    A_	(metaclass=a_							):
							"""simple docstring"""




							a__   		=	['''transformers''', '''torch''', '''note_seq''']

							def __init__(		self			:Any       ,							*lowerCAmelCase__			:Dict       ,							**lowerCAmelCase__			:List[Any]				)				->  Dict:


										'''simple docstring'''




										requires_backends(self       ,							["transformers", "torch", "note_seq"]				)

							@classmethod
							def 							_A	(		cls			:Union[str, Any]       ,							*lowerCAmelCase__			:List[str]       ,							**lowerCAmelCase__			:int				)				->  int:


										'''simple docstring'''




										requires_backends(cls       ,							["transformers", "torch", "note_seq"]				)






							@classmethod
							def 							_A	(		cls			:List[Any]       ,							*lowerCAmelCase__			:Optional[int]       ,							**lowerCAmelCase__			:List[Any]				)				->  Dict:


										'''simple docstring'''




										requires_backends(cls       ,							["transformers", "torch", "note_seq"]				)












'''simple docstring'''




from typing import TYPE_CHECKING

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


__lowerCamelCase   :					Dict   							=					{
    '''configuration_gpt_neox_japanese''': ['''GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTNeoXJapaneseConfig'''],
    '''tokenization_gpt_neox_japanese''': ['''GPTNeoXJapaneseTokenizer'''],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__lowerCamelCase   :					int   							=					[
		    '''GPT_NEOX_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''GPTNeoXJapaneseForCausalLM''',
		    '''GPTNeoXJapaneseLayer''',
		    '''GPTNeoXJapaneseModel''',
		    '''GPTNeoXJapanesePreTrainedModel''',
		]


if TYPE_CHECKING:
		from .configuration_gpt_neox_japanese import GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoXJapaneseConfig
		from .tokenization_gpt_neox_japanese import GPTNeoXJapaneseTokenizer

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_gpt_neox_japanese import (
				    GPT_NEOX_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST,
				    GPTNeoXJapaneseForCausalLM,
				    GPTNeoXJapaneseLayer,
				    GPTNeoXJapaneseModel,
				    GPTNeoXJapanesePreTrainedModel,
				)


else:
		import sys

		__lowerCamelCase   :					Optional[int]   							=					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




