novak2

/

testing

like 0

• "__torch__.model.mobilenet_v3.___torch_mangle_9.InvertedResidual",
• "__torch__.model.mobilenet_v3.ECABlock",
• "__torch__.torch.nn.modules.batchnorm.___torch_mangle_38.BatchNorm2d",
• "torch.LongStorage",
• "__torch__.model.mobilenet_v3.___torch_mangle_19.InvertedResidual",
• "__torch__.torch.nn.modules.container.___torch_mangle_33.Sequential",
• "__torch__.torch.nn.modules.container.___torch_mangle_35.Sequential",
• "__torch__.torch.nn.modules.conv.Conv2d",
• "__torch__.torch.nn.modules.batchnorm.___torch_mangle_2.BatchNorm2d",
• "__torch__.torch.nn.modules.batchnorm.BatchNorm2d",
• "__torch__.torch.nn.modules.conv.___torch_mangle_5.Conv2d",
• "__torch__.torch.nn.modules.container.___torch_mangle_24.Sequential",
• "__torch__.torch.nn.modules.batchnorm.___torch_mangle_21.BatchNorm2d",
• "__torch__.torch.nn.modules.conv.___torch_mangle_29.Conv2d",
• "__torch__.torch.nn.modules.container.___torch_mangle_8.Sequential",
• "__torch__.torch.nn.modules.conv.___torch_mangle_13.Conv2d",
• "__torch__.torch.nn.modules.conv.___torch_mangle_26.Conv2d",
• "__torch__.model.mobilenet_v3.___torch_mangle_34.InvertedResidual",
• "__torch__.torch.nn.modules.container.___torch_mangle_14.Sequential",
• "__torch__.torch.nn.modules.conv.___torch_mangle_32.Conv2d",
• "__torch__.torch.nn.modules.conv.___torch_mangle_0.Conv2d",
• "__torch__.torch.nn.modules.batchnorm.___torch_mangle_4.BatchNorm2d",
• "torch.FloatStorage",
• "torch.jit._pickle.build_intlist",
• "__torch__.torch.nn.modules.conv.___torch_mangle_3.Conv2d",
• "__torch__.torch.nn.modules.conv.Conv1d",
• "__torch__.torch.nn.modules.batchnorm.___torch_mangle_11.BatchNorm2d",
• "torch._utils._rebuild_tensor_v2",
• "__torch__.model.mobilenet_v3.___torch_mangle_31.InvertedResidual",
• "__torch__.torch.nn.modules.conv.___torch_mangle_1.Conv2d",
• "__torch__.torch.nn.modules.conv.___torch_mangle_37.Conv2d",
• "__torch__.torch.nn.modules.batchnorm.___torch_mangle_27.BatchNorm2d",
• "__torch__.torch.nn.modules.conv.___torch_mangle_16.Conv2d",
• "__torch__.torch.nn.modules.activation.GELU",
• "__torch__.torch.nn.modules.container.___torch_mangle_39.Sequential",
• "__torch__.torch.nn.modules.activation.Sigmoid",
• "__torch__.torch.nn.modules.container.___torch_mangle_30.Sequential",
• "__torch__.torch.nn.modules.conv.___torch_mangle_23.Conv2d",
• "__torch__.torch.nn.modules.linear.Linear",
• "__torch__.torch.nn.modules.conv.___torch_mangle_6.Conv2d",
• "__torch__.model.mobilenet_v3.___torch_mangle_36.InvertedResidual",
• "__torch__.model.mobilenet_v3.MobileNetECA",
• "__torch__.model.mobilenet_v3.___torch_mangle_15.InvertedResidual",
• "__torch__.torch.nn.modules.container.Sequential",
• "collections.OrderedDict",
• "__torch__.torch.nn.modules.container.___torch_mangle_18.Sequential",
• "__torch__.torch.nn.modules.conv.___torch_mangle_17.Conv2d",
• "__torch__.torch.nn.modules.conv.___torch_mangle_22.Conv2d",
• "__torch__.model.mobilenet_v3.___torch_mangle_25.InvertedResidual",
• "__torch__.torch.nn.modules.conv.___torch_mangle_28.Conv2d",
• "__torch__.model.mobilenet_v3.InvertedResidual",
• "__torch__.torch.nn.modules.conv.___torch_mangle_20.Conv2d",
• "__torch__.torch.nn.modules.conv.___torch_mangle_10.Conv2d",
• "__torch__.torch.nn.modules.batchnorm.___torch_mangle_7.BatchNorm2d",
• "__torch__.torch.nn.modules.container.___torch_mangle_40.Sequential",
• "__torch__.torch.nn.modules.pooling.AdaptiveAvgPool2d",
• "__torch__.torch.nn.modules.conv.___torch_mangle_12.Conv2d"

How to fix it?