



from typing import TYPE_CHECKING

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


_lowerCamelCase         =	{"""configuration_vilt""": ["""VILT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ViltConfig"""]}

try:
      if not is_vision_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      _lowerCamelCase         =	["""ViltFeatureExtractor"""]
      _lowerCamelCase         =	["""ViltImageProcessor"""]
      _lowerCamelCase         =	["""ViltProcessor"""]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      _lowerCamelCase         =	[
          """VILT_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """ViltForImageAndTextRetrieval""",
          """ViltForImagesAndTextClassification""",
          """ViltForTokenClassification""",
          """ViltForMaskedLM""",
          """ViltForQuestionAnswering""",
          """ViltLayer""",
          """ViltModel""",
          """ViltPreTrainedModel""",
      ]


if TYPE_CHECKING:
      from .configuration_vilt import VILT_PRETRAINED_CONFIG_ARCHIVE_MAP, ViltConfig

      try:
            if not is_vision_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .feature_extraction_vilt import ViltFeatureExtractor
            from .image_processing_vilt import ViltImageProcessor
            from .processing_vilt import ViltProcessor

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_vilt import (
                VILT_PRETRAINED_MODEL_ARCHIVE_LIST,
                ViltForImageAndTextRetrieval,
                ViltForImagesAndTextClassification,
                ViltForMaskedLM,
                ViltForQuestionAnswering,
                ViltForTokenClassification,
                ViltLayer,
                ViltModel,
                ViltPreTrainedModel,
            )


else:
      import sys

      _lowerCamelCase         =	_LazyModule(__name__, globals()["""__file__"""], _import_structure)







from typing import TYPE_CHECKING

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


UpperCAmelCase				 =   {
    """configuration_gptsan_japanese""": ["""GPTSAN_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTSanJapaneseConfig"""],
    """tokenization_gptsan_japanese""": ["""GPTSanJapaneseTokenizer"""],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase				 =   [
      """GPTSAN_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """GPTSanJapaneseForConditionalGeneration""",
      """GPTSanJapaneseModel""",
      """GPTSanJapanesePreTrainedModel""",
  ]
  UpperCAmelCase				 =   [
      """GPTSanJapaneseTokenizer""",
  ]


if TYPE_CHECKING:
  from .configuration_gptsan_japanese import GPTSAN_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTSanJapaneseConfig
  from .tokenization_gptsan_japanese import GPTSanJapaneseTokenizer

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_gptsan_japanese import (
        GPTSAN_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST,
        GPTSanJapaneseForConditionalGeneration,
        GPTSanJapaneseModel,
        GPTSanJapanesePreTrainedModel,
    )
    from .tokenization_gptsan_japanese import GPTSanJapaneseTokenizer


else:
  import sys

  UpperCAmelCase				 =   _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)