


from typing import TYPE_CHECKING

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


lowercase_	   =     {"configuration_glpn": ["GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP", "GLPNConfig"]}

try:
       if not is_vision_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowercase_	   =     ["GLPNFeatureExtractor"]
       lowercase_	   =     ["GLPNImageProcessor"]

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowercase_	   =     [
           "GLPN_PRETRAINED_MODEL_ARCHIVE_LIST",
           "GLPNForDepthEstimation",
           "GLPNLayer",
           "GLPNModel",
           "GLPNPreTrainedModel",
       ]


if TYPE_CHECKING:
       from .configuration_glpn import GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP, GLPNConfig

       try:
              if not is_vision_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .feature_extraction_glpn import GLPNFeatureExtractor
              from .image_processing_glpn import GLPNImageProcessor

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_glpn import (
                  GLPN_PRETRAINED_MODEL_ARCHIVE_LIST,
                  GLPNForDepthEstimation,
                  GLPNLayer,
                  GLPNModel,
                  GLPNPreTrainedModel,
              )


else:
       import sys

       lowercase_	   =     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)





from typing import TYPE_CHECKING

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


lowercase_	   =     {
    'configuration_convnext': ['CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ConvNextConfig', 'ConvNextOnnxConfig']
}

try:
       if not is_vision_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowercase_	   =     ['ConvNextFeatureExtractor']
       lowercase_	   =     ['ConvNextImageProcessor']

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowercase_	   =     [
           'CONVNEXT_PRETRAINED_MODEL_ARCHIVE_LIST',
           'ConvNextForImageClassification',
           'ConvNextModel',
           'ConvNextPreTrainedModel',
           'ConvNextBackbone',
       ]

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowercase_	   =     [
           'TFConvNextForImageClassification',
           'TFConvNextModel',
           'TFConvNextPreTrainedModel',
       ]

if TYPE_CHECKING:
       from .configuration_convnext import CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP, ConvNextConfig, ConvNextOnnxConfig

       try:
              if not is_vision_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .feature_extraction_convnext import ConvNextFeatureExtractor
              from .image_processing_convnext import ConvNextImageProcessor

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_convnext import (
                  CONVNEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  ConvNextBackbone,
                  ConvNextForImageClassification,
                  ConvNextModel,
                  ConvNextPreTrainedModel,
              )

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_convnext import TFConvNextForImageClassification, TFConvNextModel, TFConvNextPreTrainedModel


else:
       import sys

       lowercase_	   =     _LazyModule(__name__, globals()['__file__'], _import_structure)

