




from typing import TYPE_CHECKING

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


_lowerCAmelCase						:   Optional[int]		=   {
    "configuration_gpt_neo": ["GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTNeoConfig", "GPTNeoOnnxConfig"],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _lowerCAmelCase						:   List[str]		=   [
      "GPT_NEO_PRETRAINED_MODEL_ARCHIVE_LIST",
      "GPTNeoForCausalLM",
      "GPTNeoForQuestionAnswering",
      "GPTNeoForSequenceClassification",
      "GPTNeoForTokenClassification",
      "GPTNeoModel",
      "GPTNeoPreTrainedModel",
      "load_tf_weights_in_gpt_neo",
  ]

try:
  if not is_flax_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _lowerCAmelCase						:   Tuple		=   [
      "FlaxGPTNeoForCausalLM",
      "FlaxGPTNeoModel",
      "FlaxGPTNeoPreTrainedModel",
  ]


if TYPE_CHECKING:
  from .configuration_gpt_neo import GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoConfig, GPTNeoOnnxConfig

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_gpt_neo import (
        GPT_NEO_PRETRAINED_MODEL_ARCHIVE_LIST,
        GPTNeoForCausalLM,
        GPTNeoForQuestionAnswering,
        GPTNeoForSequenceClassification,
        GPTNeoForTokenClassification,
        GPTNeoModel,
        GPTNeoPreTrainedModel,
        load_tf_weights_in_gpt_neo,
    )

  try:
    if not is_flax_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_flax_gpt_neo import FlaxGPTNeoForCausalLM, FlaxGPTNeoModel, FlaxGPTNeoPreTrainedModel


else:
  import sys

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











from typing import TYPE_CHECKING

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


_lowerCAmelCase						:   Optional[int]		=   {
    "configuration_maskformer": ["MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "MaskFormerConfig"],
    "configuration_maskformer_swin": ["MaskFormerSwinConfig"],
}

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _lowerCAmelCase						:   Optional[int]		=   ["MaskFormerFeatureExtractor"]
  _lowerCAmelCase						:   Dict		=   ["MaskFormerImageProcessor"]


try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _lowerCAmelCase						:   int		=   [
      "MASKFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
      "MaskFormerForInstanceSegmentation",
      "MaskFormerModel",
      "MaskFormerPreTrainedModel",
  ]
  _lowerCAmelCase						:   List[str]		=   [
      "MaskFormerSwinBackbone",
      "MaskFormerSwinModel",
      "MaskFormerSwinPreTrainedModel",
  ]

if TYPE_CHECKING:
  from .configuration_maskformer import MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, MaskFormerConfig
  from .configuration_maskformer_swin import MaskFormerSwinConfig

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .feature_extraction_maskformer import MaskFormerFeatureExtractor
    from .image_processing_maskformer import MaskFormerImageProcessor
  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_maskformer import (
        MASKFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
        MaskFormerForInstanceSegmentation,
        MaskFormerModel,
        MaskFormerPreTrainedModel,
    )
    from .modeling_maskformer_swin import (
        MaskFormerSwinBackbone,
        MaskFormerSwinModel,
        MaskFormerSwinPreTrainedModel,
    )


else:
  import sys

  _lowerCAmelCase						:   str		=   _LazyModule(__name__, globals()["__file__"], _import_structure)





