gOLIVES

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CRACKS_Models

like 0

• "torchvision.models.segmentation.deeplabv3.ASPP",
• "torch._utils._rebuild_tensor_v2",
• "torch.nn.modules.container.ModuleList",
• "torch.nn.modules.pooling.MaxPool2d",
• "torch._utils._rebuild_parameter",
• "torch.nn.modules.dropout.Dropout",
• "torchvision.models.segmentation.deeplabv3.DeepLabV3",
• "torch.FloatStorage",
• "torchvision.models.resnet.Bottleneck",
• "torch.nn.modules.pooling.AdaptiveAvgPool2d",
• "torchvision.models._utils.IntermediateLayerGetter",
• "torchvision.models.segmentation.deeplabv3.ASPPPooling",
• "torchvision.models.segmentation.deeplabv3.ASPPConv",
• "torch.nn.modules.conv.Conv2d",
• "torch.LongStorage",
• "torchvision.models.segmentation.deeplabv3.DeepLabHead",
• "collections.OrderedDict",
• "__builtin__.set",
• "torch.nn.modules.container.Sequential",
• "torch.nn.modules.batchnorm.BatchNorm2d",
• "torch.nn.modules.activation.ReLU"

How to fix it?

• "torch.LongStorage",
• "__main__.SegformerModel",
• "torch._utils._rebuild_parameter",
• "transformers.models.segformer.modeling_segformer.SegformerDWConv",
• "transformers.models.segformer.configuration_segformer.SegformerConfig",
• "__builtin__.set",
• "transformers.models.segformer.modeling_segformer.SegformerEncoder",
• "transformers.models.segformer.modeling_segformer.SegformerLayer",
• "torch.nn.modules.batchnorm.BatchNorm2d",
• "torch._C._nn.gelu",
• "transformers.models.segformer.modeling_segformer.SegformerSelfOutput",
• "transformers.models.segformer.modeling_segformer.SegformerAttention",
• "torch._utils._rebuild_tensor_v2",
• "torch.nn.modules.dropout.Dropout",
• "transformers.models.segformer.modeling_segformer.SegformerDropPath",
• "collections.OrderedDict",
• "transformers.models.segformer.modeling_segformer.SegformerDecodeHead",
• "transformers.activations.GELUActivation",
• "torch.nn.modules.container.ModuleList",
• "transformers.models.segformer.modeling_segformer.SegformerModel",
• "transformers.models.segformer.modeling_segformer.SegformerMixFFN",
• "transformers.models.segformer.modeling_segformer.SegformerMLP",
• "transformers.models.segformer.modeling_segformer.SegformerEfficientSelfAttention",
• "torch.nn.modules.conv.Conv2d",
• "torch.nn.modules.linear.Identity",
• "torch.nn.modules.activation.ReLU",
• "torch.FloatStorage",
• "torch.nn.modules.normalization.LayerNorm",
• "torch.nn.modules.linear.Linear",
• "transformers.models.segformer.modeling_segformer.SegformerOverlapPatchEmbeddings",
• "transformers.models.segformer.modeling_segformer.SegformerForSemanticSegmentation"

How to fix it?

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

How to fix it?

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

How to fix it?