





from typing import TYPE_CHECKING

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


a__			:    Tuple			      =		{
    'configuration_xlm_prophetnet': ['XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP', 'XLMProphetNetConfig'],
}

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

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      a__			:    List[str]			      =		[
          '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

      a__			:    Dict			      =		_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)






from typing import TYPE_CHECKING

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


a__			:    Tuple			      =		{'configuration_yoso': ['YOSO_PRETRAINED_CONFIG_ARCHIVE_MAP', 'YosoConfig']}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      a__			:    Optional[int]			      =		[
          'YOSO_PRETRAINED_MODEL_ARCHIVE_LIST',
          'YosoForMaskedLM',
          'YosoForMultipleChoice',
          'YosoForQuestionAnswering',
          'YosoForSequenceClassification',
          'YosoForTokenClassification',
          'YosoLayer',
          'YosoModel',
          'YosoPreTrainedModel',
      ]


if TYPE_CHECKING:
      from .configuration_yoso import YOSO_PRETRAINED_CONFIG_ARCHIVE_MAP, YosoConfig

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_yoso import (
                YOSO_PRETRAINED_MODEL_ARCHIVE_LIST,
                YosoForMaskedLM,
                YosoForMultipleChoice,
                YosoForQuestionAnswering,
                YosoForSequenceClassification,
                YosoForTokenClassification,
                YosoLayer,
                YosoModel,
                YosoPreTrainedModel,
            )


else:
      import sys

      a__			:    Union[str, Any]			      =		_LazyModule(__name__, globals()['__file__'], _import_structure)



