




'''simple docstring'''





from typing import TYPE_CHECKING

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


a		:  str   			=			{
    "configuration_bart": ["BART_PRETRAINED_CONFIG_ARCHIVE_MAP", "BartConfig", "BartOnnxConfig"],
    "tokenization_bart": ["BartTokenizer"],
}

try:
      if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      a		:  Union[str, Any]   			=			["BartTokenizerFast"]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      a		:  Union[str, Any]   			=			[
          "BART_PRETRAINED_MODEL_ARCHIVE_LIST",
          "BartForCausalLM",
          "BartForConditionalGeneration",
          "BartForQuestionAnswering",
          "BartForSequenceClassification",
          "BartModel",
          "BartPretrainedModel",
          "PretrainedBartModel",
      ]

try:
      if not is_tf_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      a		:  List[str]   			=			[
          "TFBartForConditionalGeneration",
          "TFBartForSequenceClassification",
          "TFBartModel",
          "TFBartPretrainedModel",
      ]

try:
      if not is_flax_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      a		:  int   			=			[
          "FlaxBartDecoderPreTrainedModel",
          "FlaxBartForCausalLM",
          "FlaxBartForConditionalGeneration",
          "FlaxBartForQuestionAnswering",
          "FlaxBartForSequenceClassification",
          "FlaxBartModel",
          "FlaxBartPreTrainedModel",
      ]

if TYPE_CHECKING:
      from .configuration_bart import BART_PRETRAINED_CONFIG_ARCHIVE_MAP, BartConfig, BartOnnxConfig
      from .tokenization_bart import BartTokenizer

      try:
            if not is_tokenizers_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_bart_fast import BartTokenizerFast

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_bart import (
                BART_PRETRAINED_MODEL_ARCHIVE_LIST,
                BartForCausalLM,
                BartForConditionalGeneration,
                BartForQuestionAnswering,
                BartForSequenceClassification,
                BartModel,
                BartPretrainedModel,
                PretrainedBartModel,
            )

      try:
            if not is_tf_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tf_bart import (
                TFBartForConditionalGeneration,
                TFBartForSequenceClassification,
                TFBartModel,
                TFBartPretrainedModel,
            )

      try:
            if not is_flax_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_flax_bart import (
                FlaxBartDecoderPreTrainedModel,
                FlaxBartForCausalLM,
                FlaxBartForConditionalGeneration,
                FlaxBartForQuestionAnswering,
                FlaxBartForSequenceClassification,
                FlaxBartModel,
                FlaxBartPreTrainedModel,
            )

else:
      import sys

      a		:  int   			=			_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)








'''simple docstring'''





from typing import TYPE_CHECKING

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


a		:  Dict   			=			{
    '''configuration_mobilevitv2''': [
        '''MOBILEVITV2_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''MobileViTV2Config''',
        '''MobileViTV2OnnxConfig''',
    ],
}


try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a		:  List[str]   			=			[
      '''MOBILEVITV2_PRETRAINED_MODEL_ARCHIVE_LIST''',
      '''MobileViTV2ForImageClassification''',
      '''MobileViTV2ForSemanticSegmentation''',
      '''MobileViTV2Model''',
      '''MobileViTV2PreTrainedModel''',
  ]

if TYPE_CHECKING:
  from .configuration_mobilevitva import (
      MOBILEVITV2_PRETRAINED_CONFIG_ARCHIVE_MAP,
      MobileViTVaConfig,
      MobileViTVaOnnxConfig,
  )

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_mobilevitva import (
        MOBILEVITV2_PRETRAINED_MODEL_ARCHIVE_LIST,
        MobileViTVaForImageClassification,
        MobileViTVaForSemanticSegmentation,
        MobileViTVaModel,
        MobileViTVaPreTrainedModel,
    )

else:
  import sys

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


