
'''simple docstring'''






from ..utils import DummyObject, requires_backends

class 							_snake_case     (  metaclass=lowerCAmelCase_ ):
	"""simple docstring"""





	_UpperCamelCase							:  Dict								=		['''torch''', '''transformers''', '''k_diffusion''']




	def __init__(						self				: Union[str, Any]					,						*UpperCamelCase_				: Optional[int]					,						**UpperCamelCase_				: Optional[Any]      ):
			requires_backends(self					,						['''torch''', '''transformers''', '''k_diffusion''']      )




	@classmethod
	def 	__A      (						cls				: List[str]					,						*UpperCamelCase_				: str					,						**UpperCamelCase_				: List[str]      ):
			requires_backends(cls					,						['''torch''', '''transformers''', '''k_diffusion''']      )





	@classmethod
	def 	__A      (						cls				: Optional[int]					,						*UpperCamelCase_				: int					,						**UpperCamelCase_				: Any      ):
			requires_backends(cls					,						['''torch''', '''transformers''', '''k_diffusion''']      )








'''simple docstring'''






from typing import TYPE_CHECKING

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


__lowercase	=    {
    '''configuration_xlm_prophetnet''': ['''XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XLMProphetNetConfig'''],
}

try:
							if not is_sentencepiece_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowercase	=    ['''XLMProphetNetTokenizer''']

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowercase	=    [
							    '''XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''XLMProphetNetDecoder''',
							    '''XLMProphetNetEncoder''',
							    '''XLMProphetNetForCausalLM''',
							    '''XLMProphetNetForConditionalGeneration''',
							    '''XLMProphetNetModel''',
							    '''XLMProphetNetPreTrainedModel''',
							]


if TYPE_CHECKING:
							from .configuration_xlm_prophetnet import XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP, XLMProphetNetConfig

							try:
														if not is_sentencepiece_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_xlm_prophetnet import XLMProphetNetTokenizer

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_xlm_prophetnet import (
														    XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST,
														    XLMProphetNetDecoder,
														    XLMProphetNetEncoder,
														    XLMProphetNetForCausalLM,
														    XLMProphetNetForConditionalGeneration,
														    XLMProphetNetModel,
														    XLMProphetNetPreTrainedModel,
														)

else:
							import sys

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






