Spaces:

tgieruc

/

agnostic-segmentation

like 0

Runtime error

• "torch.nn.modules.conv.Conv2d",
• "__builtin__.set",
• "torch._utils._rebuild_tensor_v2",
• "segmentation_models_pytorch.decoders.unet.model.Unet",
• "torch.nn.modules.batchnorm.BatchNorm2d",
• "segmentation_models_pytorch.encoders.resnet.ResNetEncoder",
• "segmentation_models_pytorch.base.heads.SegmentationHead",
• "torch.nn.modules.linear.Identity",
• "torchvision.models.resnet.BasicBlock",
• "segmentation_models_pytorch.base.modules.Attention",
• "torch._utils._rebuild_parameter",
• "segmentation_models_pytorch.base.modules.Conv2dReLU",
• "torch.nn.modules.container.ModuleList",
• "segmentation_models_pytorch.decoders.unet.decoder.UnetDecoder",
• "collections.OrderedDict",
• "torch.LongStorage",
• "torch.nn.modules.activation.ReLU",
• "torch.nn.modules.pooling.MaxPool2d",
• "segmentation_models_pytorch.base.modules.Activation",
• "torch.nn.modules.container.Sequential",
• "torch.nn.modules.activation.Sigmoid",
• "torch.FloatStorage",
• "segmentation_models_pytorch.decoders.unet.decoder.DecoderBlock"

How to fix it?