


from typing import TYPE_CHECKING

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


__UpperCamelCase       :       Tuple						       =				{
    "configuration_nezha": ["NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP", "NezhaConfig"],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __UpperCamelCase       :       Union[str, 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

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






from typing import TYPE_CHECKING

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


__UpperCamelCase       :       Dict						       =				{
    "configuration_trocr": ["TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP", "TrOCRConfig"],
    "processing_trocr": ["TrOCRProcessor"],
}


try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __UpperCamelCase       :       Optional[int]						       =				[
           "TROCR_PRETRAINED_MODEL_ARCHIVE_LIST",
           "TrOCRForCausalLM",
           "TrOCRPreTrainedModel",
       ]


if TYPE_CHECKING:
       from .configuration_trocr import TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP, TrOCRConfig
       from .processing_trocr import TrOCRProcessor

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_trocr import TROCR_PRETRAINED_MODEL_ARCHIVE_LIST, TrOCRForCausalLM, TrOCRPreTrainedModel

else:
       import sys

       __UpperCamelCase       :       Tuple						       =				_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)


