


from ..utils import DummyObject, requires_backends






class    _UpperCamelCase     (       metaclass=__snake_case					):

				"""simple docstring"""







				lowerCAmelCase					=			['sentencepiece']

				def __init__(    self					, *a__					, **a__ )						->					Tuple:
					requires_backends(self					, ["""sentencepiece"""] )






class    _UpperCamelCase     (       metaclass=__snake_case					):

				"""simple docstring"""







				lowerCAmelCase					=			['sentencepiece']

				def __init__(    self					, *a__					, **a__ )						->					Tuple:
					requires_backends(self					, ["""sentencepiece"""] )






class    _UpperCamelCase     (       metaclass=__snake_case					):

				"""simple docstring"""







				lowerCAmelCase					=			['sentencepiece']

				def __init__(    self					, *a__					, **a__ )						->					str:
					requires_backends(self					, ["""sentencepiece"""] )






class    _UpperCamelCase     (       metaclass=__snake_case					):

				"""simple docstring"""







				lowerCAmelCase					=			['sentencepiece']

				def __init__(    self					, *a__					, **a__ )						->					int:
					requires_backends(self					, ["""sentencepiece"""] )






class    _UpperCamelCase     (       metaclass=__snake_case					):

				"""simple docstring"""







				lowerCAmelCase					=			['sentencepiece']

				def __init__(    self					, *a__					, **a__ )						->					Dict:
					requires_backends(self					, ["""sentencepiece"""] )






class    _UpperCamelCase     (       metaclass=__snake_case					):

				"""simple docstring"""







				lowerCAmelCase					=			['sentencepiece']

				def __init__(    self					, *a__					, **a__ )						->					List[Any]:
					requires_backends(self					, ["""sentencepiece"""] )






class    _UpperCamelCase     (       metaclass=__snake_case					):

				"""simple docstring"""







				lowerCAmelCase					=			['sentencepiece']

				def __init__(    self					, *a__					, **a__ )						->					Any:
					requires_backends(self					, ["""sentencepiece"""] )






class    _UpperCamelCase     (       metaclass=__snake_case					):

				"""simple docstring"""







				lowerCAmelCase					=			['sentencepiece']

				def __init__(    self					, *a__					, **a__ )						->					Optional[int]:
					requires_backends(self					, ["""sentencepiece"""] )






class    _UpperCamelCase     (       metaclass=__snake_case					):

				"""simple docstring"""







				lowerCAmelCase					=			['sentencepiece']

				def __init__(    self					, *a__					, **a__ )						->					str:
					requires_backends(self					, ["""sentencepiece"""] )






class    _UpperCamelCase     (       metaclass=__snake_case					):

				"""simple docstring"""







				lowerCAmelCase					=			['sentencepiece']

				def __init__(    self					, *a__					, **a__ )						->					List[Any]:
					requires_backends(self					, ["""sentencepiece"""] )






class    _UpperCamelCase     (       metaclass=__snake_case					):

				"""simple docstring"""







				lowerCAmelCase					=			['sentencepiece']

				def __init__(    self					, *a__					, **a__ )						->					Optional[int]:
					requires_backends(self					, ["""sentencepiece"""] )






class    _UpperCamelCase     (       metaclass=__snake_case					):

				"""simple docstring"""







				lowerCAmelCase					=			['sentencepiece']

				def __init__(    self					, *a__					, **a__ )						->					Tuple:
					requires_backends(self					, ["""sentencepiece"""] )






class    _UpperCamelCase     (       metaclass=__snake_case					):

				"""simple docstring"""







				lowerCAmelCase					=			['sentencepiece']

				def __init__(    self					, *a__					, **a__ )						->					str:
					requires_backends(self					, ["""sentencepiece"""] )






class    _UpperCamelCase     (       metaclass=__snake_case					):

				"""simple docstring"""







				lowerCAmelCase					=			['sentencepiece']

				def __init__(    self					, *a__					, **a__ )						->					Union[str, Any]:
					requires_backends(self					, ["""sentencepiece"""] )






class    _UpperCamelCase     (       metaclass=__snake_case					):

				"""simple docstring"""







				lowerCAmelCase					=			['sentencepiece']

				def __init__(    self					, *a__					, **a__ )						->					Dict:
					requires_backends(self					, ["""sentencepiece"""] )






class    _UpperCamelCase     (       metaclass=__snake_case					):

				"""simple docstring"""







				lowerCAmelCase					=			['sentencepiece']

				def __init__(    self					, *a__					, **a__ )						->					List[str]:
					requires_backends(self					, ["""sentencepiece"""] )






class    _UpperCamelCase     (       metaclass=__snake_case					):

				"""simple docstring"""







				lowerCAmelCase					=			['sentencepiece']

				def __init__(    self					, *a__					, **a__ )						->					Tuple:
					requires_backends(self					, ["""sentencepiece"""] )






class    _UpperCamelCase     (       metaclass=__snake_case					):

				"""simple docstring"""







				lowerCAmelCase					=			['sentencepiece']

				def __init__(    self					, *a__					, **a__ )						->					Optional[int]:
					requires_backends(self					, ["""sentencepiece"""] )






class    _UpperCamelCase     (       metaclass=__snake_case					):

				"""simple docstring"""







				lowerCAmelCase					=			['sentencepiece']

				def __init__(    self					, *a__					, **a__ )						->					List[Any]:
					requires_backends(self					, ["""sentencepiece"""] )






class    _UpperCamelCase     (       metaclass=__snake_case					):

				"""simple docstring"""







				lowerCAmelCase					=			['sentencepiece']

				def __init__(    self					, *a__					, **a__ )						->					Any:
					requires_backends(self					, ["""sentencepiece"""] )






class    _UpperCamelCase     (       metaclass=__snake_case					):

				"""simple docstring"""







				lowerCAmelCase					=			['sentencepiece']

				def __init__(    self					, *a__					, **a__ )						->					List[Any]:
					requires_backends(self					, ["""sentencepiece"""] )






class    _UpperCamelCase     (       metaclass=__snake_case					):

				"""simple docstring"""







				lowerCAmelCase					=			['sentencepiece']

				def __init__(    self					, *a__					, **a__ )						->					List[Any]:
					requires_backends(self					, ["""sentencepiece"""] )






class    _UpperCamelCase     (       metaclass=__snake_case					):

				"""simple docstring"""







				lowerCAmelCase					=			['sentencepiece']

				def __init__(    self					, *a__					, **a__ )						->					Optional[Any]:
					requires_backends(self					, ["""sentencepiece"""] )






class    _UpperCamelCase     (       metaclass=__snake_case					):

				"""simple docstring"""







				lowerCAmelCase					=			['sentencepiece']

				def __init__(    self					, *a__					, **a__ )						->					Any:
					requires_backends(self					, ["""sentencepiece"""] )






class    _UpperCamelCase     (       metaclass=__snake_case					):

				"""simple docstring"""







				lowerCAmelCase					=			['sentencepiece']

				def __init__(    self					, *a__					, **a__ )						->					Optional[Any]:
					requires_backends(self					, ["""sentencepiece"""] )






class    _UpperCamelCase     (       metaclass=__snake_case					):

				"""simple docstring"""







				lowerCAmelCase					=			['sentencepiece']

				def __init__(    self					, *a__					, **a__ )						->					Union[str, Any]:
					requires_backends(self					, ["""sentencepiece"""] )






class    _UpperCamelCase     (       metaclass=__snake_case					):

				"""simple docstring"""







				lowerCAmelCase					=			['sentencepiece']

				def __init__(    self					, *a__					, **a__ )						->					int:
					requires_backends(self					, ["""sentencepiece"""] )






class    _UpperCamelCase     (       metaclass=__snake_case					):

				"""simple docstring"""







				lowerCAmelCase					=			['sentencepiece']

				def __init__(    self					, *a__					, **a__ )						->					List[str]:
					requires_backends(self					, ["""sentencepiece"""] )






class    _UpperCamelCase     (       metaclass=__snake_case					):

				"""simple docstring"""







				lowerCAmelCase					=			['sentencepiece']

				def __init__(    self					, *a__					, **a__ )						->					Tuple:
					requires_backends(self					, ["""sentencepiece"""] )






class    _UpperCamelCase     (       metaclass=__snake_case					):

				"""simple docstring"""







				lowerCAmelCase					=			['sentencepiece']

				def __init__(    self					, *a__					, **a__ )						->					int:
					requires_backends(self					, ["""sentencepiece"""] )






class    _UpperCamelCase     (       metaclass=__snake_case					):

				"""simple docstring"""







				lowerCAmelCase					=			['sentencepiece']

				def __init__(    self					, *a__					, **a__ )						->					str:
					requires_backends(self					, ["""sentencepiece"""] )







from typing import TYPE_CHECKING

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


_lowercase							:   int						=						{
    "configuration_roberta_prelayernorm": [
        "ROBERTA_PRELAYERNORM_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "RobertaPreLayerNormConfig",
        "RobertaPreLayerNormOnnxConfig",
    ],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_lowercase							:   List[Any]						=						[
				    "ROBERTA_PRELAYERNORM_PRETRAINED_MODEL_ARCHIVE_LIST",
				    "RobertaPreLayerNormForCausalLM",
				    "RobertaPreLayerNormForMaskedLM",
				    "RobertaPreLayerNormForMultipleChoice",
				    "RobertaPreLayerNormForQuestionAnswering",
				    "RobertaPreLayerNormForSequenceClassification",
				    "RobertaPreLayerNormForTokenClassification",
				    "RobertaPreLayerNormModel",
				    "RobertaPreLayerNormPreTrainedModel",
				]

try:
				if not is_tf_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_lowercase							:   Optional[int]						=						[
				    "TF_ROBERTA_PRELAYERNORM_PRETRAINED_MODEL_ARCHIVE_LIST",
				    "TFRobertaPreLayerNormForCausalLM",
				    "TFRobertaPreLayerNormForMaskedLM",
				    "TFRobertaPreLayerNormForMultipleChoice",
				    "TFRobertaPreLayerNormForQuestionAnswering",
				    "TFRobertaPreLayerNormForSequenceClassification",
				    "TFRobertaPreLayerNormForTokenClassification",
				    "TFRobertaPreLayerNormMainLayer",
				    "TFRobertaPreLayerNormModel",
				    "TFRobertaPreLayerNormPreTrainedModel",
				]

try:
				if not is_flax_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_lowercase							:   str						=						[
				    "FlaxRobertaPreLayerNormForCausalLM",
				    "FlaxRobertaPreLayerNormForMaskedLM",
				    "FlaxRobertaPreLayerNormForMultipleChoice",
				    "FlaxRobertaPreLayerNormForQuestionAnswering",
				    "FlaxRobertaPreLayerNormForSequenceClassification",
				    "FlaxRobertaPreLayerNormForTokenClassification",
				    "FlaxRobertaPreLayerNormModel",
				    "FlaxRobertaPreLayerNormPreTrainedModel",
				]


if TYPE_CHECKING:
				from .configuration_roberta_prelayernorm import (
				    ROBERTA_PRELAYERNORM_PRETRAINED_CONFIG_ARCHIVE_MAP,
				    RobertaPreLayerNormConfig,
				    RobertaPreLayerNormOnnxConfig,
				)

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_roberta_prelayernorm import (
								    ROBERTA_PRELAYERNORM_PRETRAINED_MODEL_ARCHIVE_LIST,
								    RobertaPreLayerNormForCausalLM,
								    RobertaPreLayerNormForMaskedLM,
								    RobertaPreLayerNormForMultipleChoice,
								    RobertaPreLayerNormForQuestionAnswering,
								    RobertaPreLayerNormForSequenceClassification,
								    RobertaPreLayerNormForTokenClassification,
								    RobertaPreLayerNormModel,
								    RobertaPreLayerNormPreTrainedModel,
								)

				try:
								if not is_tf_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_tf_roberta_prelayernorm import (
								    TF_ROBERTA_PRELAYERNORM_PRETRAINED_MODEL_ARCHIVE_LIST,
								    TFRobertaPreLayerNormForCausalLM,
								    TFRobertaPreLayerNormForMaskedLM,
								    TFRobertaPreLayerNormForMultipleChoice,
								    TFRobertaPreLayerNormForQuestionAnswering,
								    TFRobertaPreLayerNormForSequenceClassification,
								    TFRobertaPreLayerNormForTokenClassification,
								    TFRobertaPreLayerNormMainLayer,
								    TFRobertaPreLayerNormModel,
								    TFRobertaPreLayerNormPreTrainedModel,
								)

				try:
								if not is_flax_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_flax_roberta_prelayernorm import (
								    FlaxRobertaPreLayerNormForCausalLM,
								    FlaxRobertaPreLayerNormForMaskedLM,
								    FlaxRobertaPreLayerNormForMultipleChoice,
								    FlaxRobertaPreLayerNormForQuestionAnswering,
								    FlaxRobertaPreLayerNormForSequenceClassification,
								    FlaxRobertaPreLayerNormForTokenClassification,
								    FlaxRobertaPreLayerNormModel,
								    FlaxRobertaPreLayerNormPreTrainedModel,
								)

else:
				import sys

				_lowercase							:   List[Any]						=						_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



