
'''simple docstring'''







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowercase					:							List[str]   =      {"configuration_vit_msn": ["VIT_MSN_PRETRAINED_CONFIG_ARCHIVE_MAP", "ViTMSNConfig"]}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowercase					:							Optional[Any]   =      [
					    "VIT_MSN_PRETRAINED_MODEL_ARCHIVE_LIST",
					    "ViTMSNModel",
					    "ViTMSNForImageClassification",
					    "ViTMSNPreTrainedModel",
					]

if TYPE_CHECKING:
					from .configuration_vit_msn import VIT_MSN_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTMSNConfig

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_vit_msn import (
										    VIT_MSN_PRETRAINED_MODEL_ARCHIVE_LIST,
										    ViTMSNForImageClassification,
										    ViTMSNModel,
										    ViTMSNPreTrainedModel,
										)

else:
					import sys

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



'''simple docstring'''







from typing import TYPE_CHECKING

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


lowercase					:							str   =      {
    "configuration_nezha": ["NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP", "NezhaConfig"],
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowercase					:							Any   =      [
					    "NEZHA_PRETRAINED_MODEL_ARCHIVE_LIST",
					    "NezhaForNextSentencePrediction",
					    "NezhaForMaskedLM",
					    "NezhaForPreTraining",
					    "NezhaForMultipleChoice",
					    "NezhaForQuestionAnswering",
					    "NezhaForSequenceClassification",
					    "NezhaForTokenClassification",
					    "NezhaModel",
					    "NezhaPreTrainedModel",
					]


if TYPE_CHECKING:
					from .configuration_nezha import NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP, NezhaConfig

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_nezha import (
										    NEZHA_PRETRAINED_MODEL_ARCHIVE_LIST,
										    NezhaForMaskedLM,
										    NezhaForMultipleChoice,
										    NezhaForNextSentencePrediction,
										    NezhaForPreTraining,
										    NezhaForQuestionAnswering,
										    NezhaForSequenceClassification,
										    NezhaForTokenClassification,
										    NezhaModel,
										    NezhaPreTrainedModel,
										)


else:
					import sys

					lowercase					:							Union[str, Any]   =      _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)

