



'''simple docstring'''





from typing import TYPE_CHECKING

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


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

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

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __a          =		[
           "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          =		_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





'''simple docstring'''





from transformers import BertTokenizerFast

from .custom_tokenization import CustomTokenizer







class     UpperCAmelCase_       (       _a	):
    """simple docstring"""







    lowercase					=		CustomTokenizer
    pass
