TommyNgx

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sampleSGM

like 0

• "timm.layers.norm.LayerNorm2d",
• "timm.models.convnext.ConvNeXtStage",
• "timm.layers.mlp.GlobalResponseNormMlp",
• "__builtin__.set",
• "torch.nn.modules.flatten.Flatten",
• "torch.nn.modules.linear.Identity",
• "torch.nn.modules.linear.Linear",
• "collections.OrderedDict",
• "timm.layers.classifier.NormMlpClassifierHead",
• "timm.layers.adaptive_avgmax_pool.SelectAdaptivePool2d",
• "timm.layers.activations.GELU",
• "torch.nn.modules.dropout.Dropout",
• "torch.nn.modules.container.Sequential",
• "timm.models.convnext.ConvNeXtBlock",
• "torch.nn.modules.pooling.AdaptiveAvgPool2d",
• "torch.nn.modules.conv.Conv2d",
• "timm.layers.norm.LayerNorm",
• "torch._utils._rebuild_parameter",
• "timm.layers.grn.GlobalResponseNorm",
• "torch.FloatStorage",
• "timm.models.convnext.ConvNeXt",
• "torch._utils._rebuild_tensor_v2"

How to fix it?

• "torch.LongStorage",
• "torch.FloatStorage",
• "torch.nn.modules.activation.ReLU",
• "torch.nn.modules.pooling.MaxPool2d",
• "torch.nn.modules.conv.Conv2d",
• "collections.OrderedDict",
• "torch._utils._rebuild_tensor_v2",
• "__builtin__.set",
• "torchvision.models.resnet.Bottleneck",
• "torch._utils._rebuild_parameter",
• "torch.nn.modules.linear.Linear",
• "torchvision.models.resnet.ResNet",
• "torch.nn.modules.pooling.AdaptiveAvgPool2d",
• "torch.nn.modules.container.Sequential",
• "torch.nn.modules.batchnorm.BatchNorm2d"

How to fix it?

• "torch.nn.modules.normalization.LayerNorm",
• "timm.models.convnext.ConvNeXt",
• "torch._utils._rebuild_tensor_v2",
• "torch.nn.modules.pooling.AdaptiveAvgPool2d",
• "timm.layers.adaptive_avgmax_pool.SelectAdaptivePool2d",
• "torch.nn.modules.flatten.Flatten",
• "timm.layers.activations.GELU",
• "timm.layers.mlp.GlobalResponseNormMlp",
• "torch.nn.modules.activation.ReLU",
• "torch.nn.modules.linear.Identity",
• "torch.nn.modules.dropout.Dropout",
• "__builtin__.set",
• "torch.nn.modules.conv.Conv2d",
• "torch._utils._rebuild_parameter",
• "torch.nn.modules.linear.Linear",
• "torch.nn.modules.activation.Softmax",
• "timm.layers.grn.GlobalResponseNorm",
• "torch.nn.modules.container.Sequential",
• "timm.layers.norm.LayerNorm2d",
• "timm.models.convnext.ConvNeXtBlock",
• "src.models.mil_py.MILClassifierV4",
• "timm.models.convnext.ConvNeXtStage",
• "torch.FloatStorage",
• "timm.layers.norm.LayerNorm",
• "collections.OrderedDict",
• "src.models.mil_py._GatedAttnPool",
• "timm.layers.classifier.NormMlpClassifierHead"

How to fix it?

• "__builtin__.set",
• "src.models.mil_py.MILClassifierV4",
• "torchvision.models.resnet.Bottleneck",
• "torch.LongStorage",
• "torch.nn.modules.activation.ReLU",
• "torch._utils._rebuild_tensor_v2",
• "torch.nn.modules.linear.Linear",
• "torchvision.models.resnet.ResNet",
• "torch._utils._rebuild_parameter",
• "torch.nn.modules.linear.Identity",
• "torch.nn.modules.activation.Softmax",
• "torch.nn.modules.pooling.AdaptiveAvgPool2d",
• "collections.OrderedDict",
• "torch.nn.modules.dropout.Dropout",
• "torch.nn.modules.batchnorm.BatchNorm2d",
• "torch.nn.modules.container.Sequential",
• "torch.nn.modules.conv.Conv2d",
• "torch.nn.modules.normalization.LayerNorm",
• "torch.FloatStorage",
• "src.models.mil_py._GatedAttnPool",
• "torch.nn.modules.pooling.MaxPool2d"

How to fix it?

• "torch._utils._rebuild_tensor_v2",
• "torch.nn.modules.container.Sequential",
• "timm.layers.mlp.GlobalResponseNormMlp",
• "timm.layers.norm.LayerNorm2d",
• "timm.models.convnext.ConvNeXt",
• "torch.nn.modules.dropout.Dropout",
• "timm.models.convnext.ConvNeXtStage",
• "torch.nn.modules.linear.Identity",
• "collections.OrderedDict",
• "timm.layers.grn.GlobalResponseNorm",
• "timm.layers.classifier.NormMlpClassifierHead",
• "torch.FloatStorage",
• "timm.layers.activations.GELU",
• "timm.layers.adaptive_avgmax_pool.SelectAdaptivePool2d",
• "torch.nn.modules.pooling.AdaptiveAvgPool2d",
• "torch.nn.modules.flatten.Flatten",
• "timm.layers.norm.LayerNorm",
• "__builtin__.set",
• "torch.nn.modules.conv.Conv2d",
• "torch._utils._rebuild_parameter",
• "timm.models.convnext.ConvNeXtBlock",
• "torch.nn.modules.linear.Linear"

How to fix it?

• "torch._utils._rebuild_tensor_v2",
• "torch.LongStorage",
• "torchvision.models.resnet.ResNet",
• "torch.FloatStorage",
• "torchvision.models.resnet.Bottleneck",
• "torch.nn.modules.container.Sequential",
• "torch.nn.modules.pooling.AdaptiveAvgPool2d",
• "collections.OrderedDict",
• "__builtin__.set",
• "torch.nn.modules.pooling.MaxPool2d",
• "torch.nn.modules.batchnorm.BatchNorm2d",
• "torch.nn.modules.conv.Conv2d",
• "torch._utils._rebuild_parameter",
• "torch.nn.modules.activation.ReLU",
• "torch.nn.modules.linear.Linear"

How to fix it?

• "torch.nn.modules.flatten.Flatten",
• "src.models.detr_model_attn.EfficientDeformableAttention",
• "torch.FloatStorage",
• "torch.nn.modules.normalization.LayerNorm",
• "timm.layers.grn.GlobalResponseNorm",
• "timm.models.convnext.ConvNeXt",
• "torch.nn.modules.pooling.AdaptiveAvgPool2d",
• "timm.layers.adaptive_avgmax_pool.SelectAdaptivePool2d",
• "torch.nn.modules.linear.Identity",
• "timm.layers.norm.LayerNorm2d",
• "torch._utils._rebuild_tensor_v2",
• "torch.nn.modules.linear.Linear",
• "torch.nn.modules.activation.Sigmoid",
• "__builtin__.set",
• "src.models.detr_model_attn.PositionEmbeddingSine",
• "_codecs.encode",
• "torch.nn.modules.container.ModuleDict",
• "timm.layers.norm.LayerNorm",
• "torch.nn.modules.activation.ReLU",
• "timm.models.convnext.ConvNeXtStage",
• "torch.nn.modules.linear.NonDynamicallyQuantizableLinear",
• "src.models.detr_model.M2DETRModel",
• "timm.layers.activations.GELU",
• "torch.nn.modules.activation.MultiheadAttention",
• "collections.OrderedDict",
• "src.models.m2_model.TimmFeatureWrapper",
• "torch.nn.modules.sparse.Embedding",
• "torch.nn.modules.dropout.Dropout",
• "torch._utils._rebuild_parameter",
• "src.models.detr_model.EfficientDETRDecoder",
• "torch.nn.modules.container.ModuleList",
• "src.models.detr_model_attn.MultiScaleSpatialAttention",
• "torch.nn.modules.container.Sequential",
• "numpy.dtype",
• "timm.models.convnext.ConvNeXtBlock",
• "timm.layers.mlp.GlobalResponseNormMlp",
• "numpy._core.multiarray.scalar",
• "timm.layers.classifier.NormMlpClassifierHead",
• "torch.nn.modules.conv.Conv2d"

How to fix it?

• "src.models.detr_model_attn.EfficientDeformableAttention",
• "torch.FloatStorage",
• "torch.nn.modules.normalization.LayerNorm",
• "timm.models.eva.Eva",
• "torch.nn.modules.pooling.AdaptiveAvgPool2d",
• "torch.nn.modules.linear.Identity",
• "torch._utils._rebuild_tensor_v2",
• "torch.nn.modules.linear.Linear",
• "src.models.m2_model.DinoFeatureWrapper",
• "torch.nn.modules.activation.Sigmoid",
• "__builtin__.set",
• "src.models.detr_model_attn.PositionEmbeddingSine",
• "_codecs.encode",
• "torch.nn.modules.container.ModuleDict",
• "timm.layers.norm.LayerNorm",
• "torch.nn.modules.activation.ReLU",
• "torch.nn.modules.linear.NonDynamicallyQuantizableLinear",
• "timm.models.eva.EvaAttention",
• "timm.layers.format.Format",
• "src.models.detr_model.M2DETRModel",
• "torch.nn.modules.activation.MultiheadAttention",
• "collections.OrderedDict",
• "torch.nn.modules.sparse.Embedding",
• "torch.nn.modules.dropout.Dropout",
• "torch._utils._rebuild_parameter",
• "torch.nn.modules.activation.GELU",
• "timm.models.eva.EvaBlock",
• "src.models.detr_model.EfficientDETRDecoder",
• "timm.layers.mlp.Mlp",
• "torch.nn.modules.container.ModuleList",
• "src.models.detr_model_attn.MultiScaleSpatialAttention",
• "torch.nn.modules.container.Sequential",
• "numpy.dtype",
• "timm.layers.patch_embed.PatchEmbed",
• "numpy._core.multiarray.scalar",
• "timm.layers.pos_embed_sincos.RotaryEmbeddingDinoV3",
• "torch.nn.modules.conv.Conv2d"

How to fix it?

• "torch.nn.modules.flatten.Flatten",
• "torch.FloatStorage",
• "timm.layers.grn.GlobalResponseNorm",
• "timm.models.convnext.ConvNeXt",
• "torch.nn.modules.pooling.AdaptiveAvgPool2d",
• "timm.layers.adaptive_avgmax_pool.SelectAdaptivePool2d",
• "torch.nn.modules.linear.Identity",
• "timm.layers.norm.LayerNorm2d",
• "torch._utils._rebuild_tensor_v2",
• "torch.nn.modules.linear.Linear",
• "__builtin__.set",
• "_codecs.encode",
• "timm.layers.norm.LayerNorm",
• "timm.models.convnext.ConvNeXtStage",
• "timm.layers.activations.GELU",
• "collections.OrderedDict",
• "torch.nn.modules.dropout.Dropout",
• "torch._utils._rebuild_parameter",
• "torch.nn.modules.container.Sequential",
• "numpy.dtype",
• "timm.models.convnext.ConvNeXtBlock",
• "timm.layers.mlp.GlobalResponseNormMlp",
• "numpy._core.multiarray.scalar",
• "timm.layers.classifier.NormMlpClassifierHead",
• "torch.nn.modules.conv.Conv2d"

How to fix it?

• "numpy.dtype",
• "__builtin__.set",
• "collections.OrderedDict",
• "torch.FloatStorage",
• "torch.nn.modules.pooling.MaxPool2d",
• "_codecs.encode",
• "torch.LongStorage",
• "torchvision.models.resnet.ResNet",
• "torch.nn.modules.batchnorm.BatchNorm2d",
• "torch.nn.modules.activation.ReLU",
• "torch._utils._rebuild_parameter",
• "torch.nn.modules.pooling.AdaptiveAvgPool2d",
• "torchvision.models.resnet.Bottleneck",
• "torch.nn.modules.conv.Conv2d",
• "numpy._core.multiarray.scalar",
• "torch._utils._rebuild_tensor_v2",
• "torch.nn.modules.container.Sequential",
• "torch.nn.modules.linear.Linear"

How to fix it?

• "ultralytics.nn.modules.block.C2f",
• "torch.nn.modules.batchnorm.BatchNorm2d",
• "ultralytics.nn.modules.head.Detect",
• "torch.FloatStorage",
• "ultralytics.nn.modules.block.SPPF",
• "ultralytics.utils.loss.BboxLoss",
• "torch.nn.modules.activation.SiLU",
• "torch.nn.modules.loss.BCEWithLogitsLoss",
• "ultralytics.nn.tasks.DetectionModel",
• "collections.OrderedDict",
• "ultralytics.nn.modules.block.DFL",
• "torch.HalfStorage",
• "ultralytics.nn.modules.block.Bottleneck",
• "torch.nn.modules.container.ModuleList",
• "ultralytics.nn.modules.conv.Concat",
• "torch._utils._rebuild_tensor_v2",
• "torch._utils._rebuild_parameter",
• "torch.nn.modules.pooling.MaxPool2d",
• "torch.Size",
• "torch.device",
• "torch.LongStorage",
• "ultralytics.utils.tal.TaskAlignedAssigner",
• "ultralytics.nn.modules.conv.Conv",
• "torch.nn.modules.container.Sequential",
• "__builtin__.set",
• "torch.nn.modules.conv.Conv2d",
• "ultralytics.utils.loss.v8DetectionLoss",
• "torch.nn.modules.upsampling.Upsample",
• "ultralytics.utils.IterableSimpleNamespace"

How to fix it?