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res2net

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Sleeping

• "__main__.Res2Net",
• "timm.models.layers.activations.sigmoid",
• "torch.nn.modules.activation.ReLU",
• "torch.nn.modules.container.ModuleList",
• "torch._utils._rebuild_tensor_v2",
• "torch.nn.modules.conv.Conv2d",
• "torch.nn.modules.container.Sequential",
• "timm.models.layers.conv2d_same.Conv2dSame",
• "torch.nn.modules.activation.SiLU",
• "timm.models.layers.adaptive_avgmax_pool.SelectAdaptivePool2d",
• "torch.FloatStorage",
• "timm.models.efficientnet_blocks.DepthwiseSeparableConv",
• "torch.nn.modules.pooling.AdaptiveMaxPool2d",
• "torch.nn.modules.pooling.AvgPool2d",
• "timm.models.efficientnet_blocks.SqueezeExcite",
• "torch.nn.modules.linear.Linear",
• "torch.nn.modules.pooling.AdaptiveAvgPool2d",
• "torch.nn.modules.linear.Identity",
• "__main__.mutil_model",
• "__builtin__.set",
• "__main__.Bottle2neck",
• "torch.nn.modules.batchnorm.BatchNorm2d",
• "timm.models.efficientnet_blocks.InvertedResidual",
• "collections.OrderedDict",
• "torch._utils._rebuild_parameter",
• "torch.LongStorage",
• "timm.models.efficientnet.EfficientNet",
• "torch.nn.modules.pooling.MaxPool2d"

How to fix it?

• "torch._utils._rebuild_parameter",
• "torch.nn.modules.linear.Linear",
• "timm.models.efficientnet_blocks.DepthwiseSeparableConv",
• "timm.models.layers.activations.sigmoid",
• "torch.LongStorage",
• "torch.nn.modules.conv.Conv2d",
• "__builtin__.set",
• "torch.FloatStorage",
• "timm.models.efficientnet_blocks.InvertedResidual",
• "torch.nn.modules.activation.SiLU",
• "torch.nn.modules.container.Sequential",
• "timm.models.efficientnet.EfficientNet",
• "torch.nn.modules.pooling.AdaptiveMaxPool2d",
• "timm.models.layers.adaptive_avgmax_pool.SelectAdaptivePool2d",
• "torch.nn.modules.batchnorm.BatchNorm2d",
• "timm.models.layers.conv2d_same.Conv2dSame",
• "timm.models.efficientnet_blocks.SqueezeExcite",
• "collections.OrderedDict",
• "torch._utils._rebuild_tensor_v2",
• "torch.nn.modules.linear.Identity"

How to fix it?

• "torch._utils._rebuild_parameter",
• "torch.nn.modules.linear.Linear",
• "timm.models.efficientnet_blocks.DepthwiseSeparableConv",
• "timm.models.layers.activations.sigmoid",
• "torch.LongStorage",
• "__main__.Bottle2neck",
• "__main__.mutil_model",
• "torch.nn.modules.conv.Conv2d",
• "__main__.Res2Net",
• "__builtin__.set",
• "torch.FloatStorage",
• "torch.nn.modules.activation.ReLU",
• "timm.models.efficientnet_blocks.InvertedResidual",
• "torch.nn.modules.container.ModuleList",
• "torch.nn.modules.container.Sequential",
• "torch.nn.modules.activation.SiLU",
• "torch.nn.modules.pooling.MaxPool2d",
• "timm.models.efficientnet.EfficientNet",
• "torch.nn.modules.pooling.AdaptiveMaxPool2d",
• "timm.models.layers.adaptive_avgmax_pool.SelectAdaptivePool2d",
• "torch.nn.modules.batchnorm.BatchNorm2d",
• "torch.nn.modules.pooling.AvgPool2d",
• "torch.nn.modules.pooling.AdaptiveAvgPool2d",
• "timm.models.layers.conv2d_same.Conv2dSame",
• "timm.models.efficientnet_blocks.SqueezeExcite",
• "collections.OrderedDict",
• "torch._utils._rebuild_tensor_v2",
• "torch.nn.modules.linear.Identity"

How to fix it?