



from typing import TYPE_CHECKING

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


A:     int										=	{
    "configuration_conditional_detr": [
        "CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "ConditionalDetrConfig",
        "ConditionalDetrOnnxConfig",
    ]
}

try:
      if not is_vision_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      A:     Dict										=	["ConditionalDetrFeatureExtractor"]
      A:     str										=	["ConditionalDetrImageProcessor"]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      A:     List[Any]										=	[
          "CONDITIONAL_DETR_PRETRAINED_MODEL_ARCHIVE_LIST",
          "ConditionalDetrForObjectDetection",
          "ConditionalDetrForSegmentation",
          "ConditionalDetrModel",
          "ConditionalDetrPreTrainedModel",
      ]


if TYPE_CHECKING:
      from .configuration_conditional_detr import (
          CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP,
          ConditionalDetrConfig,
          ConditionalDetrOnnxConfig,
      )

      try:
            if not is_vision_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .feature_extraction_conditional_detr import ConditionalDetrFeatureExtractor
            from .image_processing_conditional_detr import ConditionalDetrImageProcessor

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_conditional_detr import (
                CONDITIONAL_DETR_PRETRAINED_MODEL_ARCHIVE_LIST,
                ConditionalDetrForObjectDetection,
                ConditionalDetrForSegmentation,
                ConditionalDetrModel,
                ConditionalDetrPreTrainedModel,
            )

else:
      import sys

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





"""simple docstring"""
from typing import TYPE_CHECKING

from ...utils import _LazyModule


A:     Dict										=	{"tokenization_bertweet": ["BertweetTokenizer"]}


if TYPE_CHECKING:
      from .tokenization_bertweet import BertweetTokenizer

else:
      import sys

      A:     int										=	_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
