search

JacobYuan7 / DIN-Group-Activity-Recognition-Benchmark

[ICCV 2021] A new codebase containing various methods for Group Activity Recognition. Paper title: Spatio-Temporal Dynamic Inference Network for Group Activity Recognition.
MIT License
52 stars 15 forks source link

collective数据集第二阶段训练，模型载入报错 #15

Closed zengxunli closed 1 year ago

zengxunli commented 2 years ago

您好，感谢您开源的代码。VD的一二阶段训练都是顺利的，但是我在训练CAD时，第一阶段使用resnet18训练，但是在第二阶段遇到了权重载入的错误，模型配置文件完全是默认未改动的，您可以帮我看看这是为什么吗

    raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for MyRes18:
        Missing key(s) in state_dict: "features.0.weight", "features.1.weight", "features.1.bias", "features.1.running_mean", "features.1.running_var", "features.4.0.conv1.weight", "features.4.0.bn1.weight", "features.4.0.bn1.bias", "features.4.0.bn1.running_mean", "features.4.0.bn1.running_var", "features.4.0.conv2.weight", "features.4.0.bn2.weight", "features.4.0.bn2.bias", "features.4.0.bn2.running_mean", "features.4.0.bn2.running_var", "features.4.1.conv1.weight", "features.4.1.bn1.weight", "features.4.1.bn1.bias", "features.4.1.bn1.running_mean", "features.4.1.bn1.running_var", "features.4.1.conv2.weight", "features.4.1.bn2.weight", "features.4.1.bn2.bias", "features.4.1.bn2.running_mean", "features.4.1.bn2.running_var", "features.5.0.conv1.weight", "features.5.0.bn1.weight", "features.5.0.bn1.bias", "features.5.0.bn1.running_mean", "features.5.0.bn1.running_var", "features.5.0.conv2.weight", "features.5.0.bn2.weight", "features.5.0.bn2.bias", "features.5.0.bn2.running_mean", "features.5.0.bn2.running_var", "features.5.0.downsample.0.weight", "features.5.0.downsample.1.weight", "features.5.0.downsample.1.bias", "features.5.0.downsample.1.running_mean", "features.5.0.downsample.1.running_var", "features.5.1.conv1.weight", "features.5.1.bn1.weight", "features.5.1.bn1.bias", "features.5.1.bn1.running_mean", "features.5.1.bn1.running_var", "features.5.1.conv2.weight", "features.5.1.bn2.weight", "features.5.1.bn2.bias", "features.5.1.bn2.running_mean", "features.5.1.bn2.running_var", "features.6.0.conv1.weight", "features.6.0.bn1.weight", "features.6.0.bn1.bias", "features.6.0.bn1.running_mean", "features.6.0.bn1.running_var", "features.6.0.conv2.weight", "features.6.0.bn2.weight", "features.6.0.bn2.bias", "features.6.0.bn2.running_mean", "features.6.0.bn2.running_var", "features.6.0.downsample.0.weight", "features.6.0.downsample.1.weight", "features.6.0.downsample.1.bias", "features.6.0.downsample.1.running_mean", "features.6.0.downsample.1.running_var", "features.6.1.conv1.weight", "features.6.1.bn1.weight", "features.6.1.bn1.bias", "features.6.1.bn1.running_mean", "features.6.1.bn1.running_var", "features.6.1.conv2.weight", "features.6.1.bn2.weight", "features.6.1.bn2.bias", "features.6.1.bn2.running_mean", "features.6.1.bn2.running_var", "features.7.0.conv1.weight", "features.7.0.bn1.weight", "features.7.0.bn1.bias", "features.7.0.bn1.running_mean", "features.7.0.bn1.running_var", "features.7.0.conv2.weight", "features.7.0.bn2.weight", "features.7.0.bn2.bias", "features.7.0.bn2.running_mean", "features.7.0.bn2.running_var", "features.7.0.downsample.0.weight", "features.7.0.downsample.1.weight", "features.7.0.downsample.1.bias", "features.7.0.downsample.1.running_mean", "features.7.0.downsample.1.running_var", "features.7.1.conv1.weight", "features.7.1.bn1.weight", "features.7.1.bn1.bias", "features.7.1.bn1.running_mean", "features.7.1.bn1.running_var", "features.7.1.conv2.weight", "features.7.1.bn2.weight", "features.7.1.bn2.bias", "features.7.1.bn2.running_mean", "features.7.1.bn2.running_var". 
        Unexpected key(s) in state_dict: "Conv2d_1a_3x3.conv.weight", "Conv2d_1a_3x3.bn.weight", "Conv2d_1a_3x3.bn.bias", "Conv2d_1a_3x3.bn.running_mean", "Conv2d_1a_3x3.bn.running_var", "Conv2d_1a_3x3.bn.num_batches_tracked", "Conv2d_2a_3x3.conv.weight", "Conv2d_2a_3x3.bn.weight", "Conv2d_2a_3x3.bn.bias", "Conv2d_2a_3x3.bn.running_mean", "Conv2d_2a_3x3.bn.running_var", "Conv2d_2a_3x3.bn.num_batches_tracked", "Conv2d_2b_3x3.conv.weight", "Conv2d_2b_3x3.bn.weight", "Conv2d_2b_3x3.bn.bias", "Conv2d_2b_3x3.bn.running_mean", "Conv2d_2b_3x3.bn.running_var", "Conv2d_2b_3x3.bn.num_batches_tracked", "Conv2d_3b_1x1.conv.weight", "Conv2d_3b_1x1.bn.weight", "Conv2d_3b_1x1.bn.bias", "Conv2d_3b_1x1.bn.running_mean", "Conv2d_3b_1x1.bn.running_var", "Conv2d_3b_1x1.bn.num_batches_tracked", "Conv2d_4a_3x3.conv.weight", "Conv2d_4a_3x3.bn.weight", "Conv2d_4a_3x3.bn.bias", "Conv2d_4a_3x3.bn.running_mean", "Conv2d_4a_3x3.bn.running_var", "Conv2d_4a_3x3.bn.num_batches_tracked", "Mixed_5b.branch1x1.conv.weight", "Mixed_5b.branch1x1.bn.weight", "Mixed_5b.branch1x1.bn.bias", "Mixed_5b.branch1x1.bn.running_mean", "Mixed_5b.branch1x1.bn.running_var", "Mixed_5b.branch1x1.bn.num_batches_tracked", "Mixed_5b.branch5x5_1.conv.weight", "Mixed_5b.branch5x5_1.bn.weight", "Mixed_5b.branch5x5_1.bn.bias", "Mixed_5b.branch5x5_1.bn.running_mean", "Mixed_5b.branch5x5_1.bn.running_var", "Mixed_5b.branch5x5_1.bn.num_batches_tracked", "Mixed_5b.branch5x5_2.conv.weight", "Mixed_5b.branch5x5_2.bn.weight", "Mixed_5b.branch5x5_2.bn.bias", "Mixed_5b.branch5x5_2.bn.running_mean", "Mixed_5b.branch5x5_2.bn.running_var", "Mixed_5b.branch5x5_2.bn.num_batches_tracked", "Mixed_5b.branch3x3dbl_1.conv.weight", "Mixed_5b.branch3x3dbl_1.bn.weight", "Mixed_5b.branch3x3dbl_1.bn.bias", "Mixed_5b.branch3x3dbl_1.bn.running_mean", "Mixed_5b.branch3x3dbl_1.bn.running_var", "Mixed_5b.branch3x3dbl_1.bn.num_batches_tracked", "Mixed_5b.branch3x3dbl_2.conv.weight", "Mixed_5b.branch3x3dbl_2.bn.weight", "Mixed_5b.branch3x3dbl_2.bn.bias", "Mixed_5b.branch3x3dbl_2.bn.running_mean", "Mixed_5b.branch3x3dbl_2.bn.running_var", "Mixed_5b.branch3x3dbl_2.bn.num_batches_tracked", "Mixed_5b.branch3x3dbl_3.conv.weight", "Mixed_5b.branch3x3dbl_3.bn.weight", "Mixed_5b.branch3x3dbl_3.bn.bias", "Mixed_5b.branch3x3dbl_3.bn.running_mean", "Mixed_5b.branch3x3dbl_3.bn.running_var", "Mixed_5b.branch3x3dbl_3.bn.num_batches_tracked", "Mixed_5b.branch_pool.conv.weight", "Mixed_5b.branch_pool.bn.weight", "Mixed_5b.branch_pool.bn.bias", "Mixed_5b.branch_pool.bn.running_mean", "Mixed_5b.branch_pool.bn.running_var", "Mixed_5b.branch_pool.bn.num_batches_tracked", "Mixed_5c.branch1x1.conv.weight", "Mixed_5c.branch1x1.bn.weight", "Mixed_5c.branch1x1.bn.bias", "Mixed_5c.branch1x1.bn.running_mean", "Mixed_5c.branch1x1.bn.running_var", "Mixed_5c.branch1x1.bn.num_batches_tracked", "Mixed_5c.branch5x5_1.conv.weight", "Mixed_5c.branch5x5_1.bn.weight", "Mixed_5c.branch5x5_1.bn.bias", "Mixed_5c.branch5x5_1.bn.running_mean", "Mixed_5c.branch5x5_1.bn.running_var", "Mixed_5c.branch5x5_1.bn.num_batches_tracked", "Mixed_5c.branch5x5_2.conv.weight", "Mixed_5c.branch5x5_2.bn.weight", "Mixed_5c.branch5x5_2.bn.bias", "Mixed_5c.branch5x5_2.bn.running_mean", "Mixed_5c.branch5x5_2.bn.running_var", "Mixed_5c.branch5x5_2.bn.num_batches_tracked", "Mixed_5c.branch3x3dbl_1.conv.weight", "Mixed_5c.branch3x3dbl_1.bn.weight", "Mixed_5c.branch3x3dbl_1.bn.bias", "Mixed_5c.branch3x3dbl_1.bn.running_mean", "Mixed_5c.branch3x3dbl_1.bn.running_var", "Mixed_5c.branch3x3dbl_1.bn.num_batches_tracked", "Mixed_5c.branch3x3dbl_2.conv.weight", "Mixed_5c.branch3x3dbl_2.bn.weight", "Mixed_5c.branch3x3dbl_2.bn.bias", "Mixed_5c.branch3x3dbl_2.bn.running_mean", "Mixed_5c.branch3x3dbl_2.bn.running_var", "Mixed_5c.branch3x3dbl_2.bn.num_batches_tracked", "Mixed_5c.branch3x3dbl_3.conv.weight", "Mixed_5c.branch3x3dbl_3.bn.weight", "Mixed_5c.branch3x3dbl_3.bn.bias", "Mixed_5c.branch3x3dbl_3.bn.running_mean", "Mixed_5c.branch3x3dbl_3.bn.running_var", "Mixed_5c.branch3x3dbl_3.bn.num_batches_tracked", "Mixed_5c.branch_pool.conv.weight", "Mixed_5c.branch_pool.bn.weight", "Mixed_5c.branch_pool.bn.bias", "Mixed_5c.branch_pool.bn.running_mean", "Mixed_5c.branch_pool.bn.running_var", "Mixed_5c.branch_pool.bn.num_batches_tracked", "Mixed_5d.branch1x1.conv.weight", "Mixed_5d.branch1x1.bn.weight", "Mixed_5d.branch1x1.bn.bias", "Mixed_5d.branch1x1.bn.running_mean", "Mixed_5d.branch1x1.bn.running_var", "Mixed_5d.branch1x1.bn.num_batches_tracked", "Mixed_5d.branch5x5_1.conv.weight", "Mixed_5d.branch5x5_1.bn.weight", "Mixed_5d.branch5x5_1.bn.bias", "Mixed_5d.branch5x5_1.bn.running_mean", "Mixed_5d.branch5x5_1.bn.running_var", "Mixed_5d.branch5x5_1.bn.num_batches_tracked", "Mixed_5d.branch5x5_2.conv.weight", "Mixed_5d.branch5x5_2.bn.weight", "Mixed_5d.branch5x5_2.bn.bias", "Mixed_5d.branch5x5_2.bn.running_mean", "Mixed_5d.branch5x5_2.bn.running_var", "Mixed_5d.branch5x5_2.bn.num_batches_tracked", "Mixed_5d.branch3x3dbl_1.conv.weight", "Mixed_5d.branch3x3dbl_1.bn.weight", "Mixed_5d.branch3x3dbl_1.bn.bias", "Mixed_5d.branch3x3dbl_1.bn.running_mean", "Mixed_5d.branch3x3dbl_1.bn.running_var", "Mixed_5d.branch3x3dbl_1.bn.num_batches_tracked", "Mixed_5d.branch3x3dbl_2.conv.weight", "Mixed_5d.branch3x3dbl_2.bn.weight", "Mixed_5d.branch3x3dbl_2.bn.bias", "Mixed_5d.branch3x3dbl_2.bn.running_mean", "Mixed_5d.branch3x3dbl_2.bn.running_var", "Mixed_5d.branch3x3dbl_2.bn.num_batches_tracked", "Mixed_5d.branch3x3dbl_3.conv.weight", "Mixed_5d.branch3x3dbl_3.bn.weight", "Mixed_5d.branch3x3dbl_3.bn.bias", "Mixed_5d.branch3x3dbl_3.bn.running_mean", "Mixed_5d.branch3x3dbl_3.bn.running_var", "Mixed_5d.branch3x3dbl_3.bn.num_batches_tracked", "Mixed_5d.branch_pool.conv.weight", "Mixed_5d.branch_pool.bn.weight", "Mixed_5d.branch_pool.bn.bias", "Mixed_5d.branch_pool.bn.running_mean", "Mixed_5d.branch_pool.bn.running_var", "Mixed_5d.branch_pool.bn.num_batches_tracked", "Mixed_6a.branch3x3.conv.weight", "Mixed_6a.branch3x3.bn.weight", "Mixed_6a.branch3x3.bn.bias", "Mixed_6a.branch3x3.bn.running_mean", "Mixed_6a.branch3x3.bn.running_var", "Mixed_6a.branch3x3.bn.num_batches_tracked", "Mixed_6a.branch3x3dbl_1.conv.weight", "Mixed_6a.branch3x3dbl_1.bn.weight", "Mixed_6a.branch3x3dbl_1.bn.bias", "Mixed_6a.branch3x3dbl_1.bn.running_mean", "Mixed_6a.branch3x3dbl_1.bn.running_var", "Mixed_6a.branch3x3dbl_1.bn.num_batches_tracked", "Mixed_6a.branch3x3dbl_2.conv.weight", "Mixed_6a.branch3x3dbl_2.bn.weight", "Mixed_6a.branch3x3dbl_2.bn.bias", "Mixed_6a.branch3x3dbl_2.bn.running_mean", "Mixed_6a.branch3x3dbl_2.bn.running_var", "Mixed_6a.branch3x3dbl_2.bn.num_batches_tracked", "Mixed_6a.branch3x3dbl_3.conv.weight", "Mixed_6a.branch3x3dbl_3.bn.weight", "Mixed_6a.branch3x3dbl_3.bn.bias", "Mixed_6a.branch3x3dbl_3.bn.running_mean", "Mixed_6a.branch3x3dbl_3.bn.running_var", "Mixed_6a.branch3x3dbl_3.bn.num_batches_tracked", "Mixed_6b.branch1x1.conv.weight", "Mixed_6b.branch1x1.bn.weight", "Mixed_6b.branch1x1.bn.bias", "Mixed_6b.branch1x1.bn.running_mean", "Mixed_6b.branch1x1.bn.running_var", "Mixed_6b.branch1x1.bn.num_batches_tracked", "Mixed_6b.branch7x7_1.conv.weight", "Mixed_6b.branch7x7_1.bn.weight", "Mixed_6b.branch7x7_1.bn.bias", "Mixed_6b.branch7x7_1.bn.running_mean", "Mixed_6b.branch7x7_1.bn.running_var", "Mixed_6b.branch7x7_1.bn.num_batches_tracked", "Mixed_6b.branch7x7_2.conv.weight", "Mixed_6b.branch7x7_2.bn.weight", "Mixed_6b.branch7x7_2.bn.bias", "Mixed_6b.branch7x7_2.bn.running_mean", "Mixed_6b.branch7x7_2.bn.running_var", "Mixed_6b.branch7x7_2.bn.num_batches_tracked", "Mixed_6b.branch7x7_3.conv.weight", "Mixed_6b.branch7x7_3.bn.weight", "Mixed_6b.branch7x7_3.bn.bias", "Mixed_6b.branch7x7_3.bn.running_mean", "Mixed_6b.branch7x7_3.bn.running_var", "Mixed_6b.branch7x7_3.bn.num_batches_tracked", "Mixed_6b.branch7x7dbl_1.conv.weight", "Mixed_6b.branch7x7dbl_1.bn.weight", "Mixed_6b.branch7x7dbl_1.bn.bias", "Mixed_6b.branch7x7dbl_1.bn.running_mean", "Mixed_6b.branch7x7dbl_1.bn.running_var", "Mixed_6b.branch7x7dbl_1.bn.num_batches_tracked", "Mixed_6b.branch7x7dbl_2.conv.weight", "Mixed_6b.branch7x7dbl_2.bn.weight", "Mixed_6b.branch7x7dbl_2.bn.bias", "Mixed_6b.branch7x7dbl_2.bn.running_mean", "Mixed_6b.branch7x7dbl_2.bn.running_var", "Mixed_6b.branch7x7dbl_2.bn.num_batches_tracked", "Mixed_6b.branch7x7dbl_3.conv.weight", "Mixed_6b.branch7x7dbl_3.bn.weight", "Mixed_6b.branch7x7dbl_3.bn.bias", "Mixed_6b.branch7x7dbl_3.bn.running_mean", "Mixed_6b.branch7x7dbl_3.bn.running_var", "Mixed_6b.branch7x7dbl_3.bn.num_batches_tracked", "Mixed_6b.branch7x7dbl_4.conv.weight", "Mixed_6b.branch7x7dbl_4.bn.weight", "Mixed_6b.branch7x7dbl_4.bn.bias", "Mixed_6b.branch7x7dbl_4.bn.running_mean", "Mixed_6b.branch7x7dbl_4.bn.running_var", "Mixed_6b.branch7x7dbl_4.bn.num_batches_tracked", "Mixed_6b.branch7x7dbl_5.conv.weight", "Mixed_6b.branch7x7dbl_5.bn.weight", "Mixed_6b.branch7x7dbl_5.bn.bias", "Mixed_6b.branch7x7dbl_5.bn.running_mean", "Mixed_6b.branch7x7dbl_5.bn.running_var", "Mixed_6b.branch7x7dbl_5.bn.num_batches_tracked", "Mixed_6b.branch_pool.conv.weight", "Mixed_6b.branch_pool.bn.weight", "Mixed_6b.branch_pool.bn.bias", "Mixed_6b.branch_pool.bn.running_mean", "Mixed_6b.branch_pool.bn.running_var", "Mixed_6b.branch_pool.bn.num_batches_tracked", "Mixed_6c.branch1x1.conv.weight", "Mixed_6c.branch1x1.bn.weight", "Mixed_6c.branch1x1.bn.bias", "Mixed_6c.branch1x1.bn.running_mean", "Mixed_6c.branch1x1.bn.running_var", "Mixed_6c.branch1x1.bn.num_batches_tracked", "Mixed_6c.branch7x7_1.conv.weight", "Mixed_6c.branch7x7_1.bn.weight", "Mixed_6c.branch7x7_1.bn.bias", "Mixed_6c.branch7x7_1.bn.running_mean", "Mixed_6c.branch7x7_1.bn.running_var", "Mixed_6c.branch7x7_1.bn.num_batches_tracked", "Mixed_6c.branch7x7_2.conv.weight", "Mixed_6c.branch7x7_2.bn.weight", "Mixed_6c.branch7x7_2.bn.bias", "Mixed_6c.branch7x7_2.bn.running_mean", "Mixed_6c.branch7x7_2.bn.running_var", "Mixed_6c.branch7x7_2.bn.num_batches_tracked", "Mixed_6c.branch7x7_3.conv.weight", "Mixed_6c.branch7x7_3.bn.weight", "Mixed_6c.branch7x7_3.bn.bias", "Mixed_6c.branch7x7_3.bn.running_mean", "Mixed_6c.branch7x7_3.bn.running_var", "Mixed_6c.branch7x7_3.bn.num_batches_tracked", "Mixed_6c.branch7x7dbl_1.conv.weight", "Mixed_6c.branch7x7dbl_1.bn.weight", "Mixed_6c.branch7x7dbl_1.bn.bias", "Mixed_6c.branch7x7dbl_1.bn.running_mean", "Mixed_6c.branch7x7dbl_1.bn.running_var", "Mixed_6c.branch7x7dbl_1.bn.num_batches_tracked", "Mixed_6c.branch7x7dbl_2.conv.weight", "Mixed_6c.branch7x7dbl_2.bn.weight", "Mixed_6c.branch7x7dbl_2.bn.bias", "Mixed_6c.branch7x7dbl_2.bn.running_mean", "Mixed_6c.branch7x7dbl_2.bn.running_var", "Mixed_6c.branch7x7dbl_2.bn.num_batches_tracked", "Mixed_6c.branch7x7dbl_3.conv.weight", "Mixed_6c.branch7x7dbl_3.bn.weight", "Mixed_6c.branch7x7dbl_3.bn.bias", "Mixed_6c.branch7x7dbl_3.bn.running_mean", "Mixed_6c.branch7x7dbl_3.bn.running_var", "Mixed_6c.branch7x7dbl_3.bn.num_batches_tracked", "Mixed_6c.branch7x7dbl_4.conv.weight", "Mixed_6c.branch7x7dbl_4.bn.weight", "Mixed_6c.branch7x7dbl_4.bn.bias", "Mixed_6c.branch7x7dbl_4.bn.running_mean", "Mixed_6c.branch7x7dbl_4.bn.running_var", "Mixed_6c.branch7x7dbl_4.bn.num_batches_tracked", "Mixed_6c.branch7x7dbl_5.conv.weight", "Mixed_6c.branch7x7dbl_5.bn.weight", "Mixed_6c.branch7x7dbl_5.bn.bias", "Mixed_6c.branch7x7dbl_5.bn.running_mean", "Mixed_6c.branch7x7dbl_5.bn.running_var", "Mixed_6c.branch7x7dbl_5.bn.num_batches_tracked", "Mixed_6c.branch_pool.conv.weight", "Mixed_6c.branch_pool.bn.weight", "Mixed_6c.branch_pool.bn.bias", "Mixed_6c.branch_pool.bn.running_mean", "Mixed_6c.branch_pool.bn.running_var", "Mixed_6c.branch_pool.bn.num_batches_tracked", "Mixed_6d.branch1x1.conv.weight", "Mixed_6d.branch1x1.bn.weight", "Mixed_6d.branch1x1.bn.bias", "Mixed_6d.branch1x1.bn.running_mean", "Mixed_6d.branch1x1.bn.running_var", "Mixed_6d.branch1x1.bn.num_batches_tracked", "Mixed_6d.branch7x7_1.conv.weight", "Mixed_6d.branch7x7_1.bn.weight", "Mixed_6d.branch7x7_1.bn.bias", "Mixed_6d.branch7x7_1.bn.running_mean", "Mixed_6d.branch7x7_1.bn.running_var", "Mixed_6d.branch7x7_1.bn.num_batches_tracked", "Mixed_6d.branch7x7_2.conv.weight", "Mixed_6d.branch7x7_2.bn.weight", "Mixed_6d.branch7x7_2.bn.bias", "Mixed_6d.branch7x7_2.bn.running_mean", "Mixed_6d.branch7x7_2.bn.running_var", "Mixed_6d.branch7x7_2.bn.num_batches_tracked", "Mixed_6d.branch7x7_3.conv.weight", "Mixed_6d.branch7x7_3.bn.weight", "Mixed_6d.branch7x7_3.bn.bias", "Mixed_6d.branch7x7_3.bn.running_mean", "Mixed_6d.branch7x7_3.bn.running_var", "Mixed_6d.branch7x7_3.bn.num_batches_tracked", "Mixed_6d.branch7x7dbl_1.conv.weight", "Mixed_6d.branch7x7dbl_1.bn.weight", "Mixed_6d.branch7x7dbl_1.bn.bias", "Mixed_6d.branch7x7dbl_1.bn.running_mean", "Mixed_6d.branch7x7dbl_1.bn.running_var", "Mixed_6d.branch7x7dbl_1.bn.num_batches_tracked", "Mixed_6d.branch7x7dbl_2.conv.weight", "Mixed_6d.branch7x7dbl_2.bn.weight", "Mixed_6d.branch7x7dbl_2.bn.bias", "Mixed_6d.branch7x7dbl_2.bn.running_mean", "Mixed_6d.branch7x7dbl_2.bn.running_var", "Mixed_6d.branch7x7dbl_2.bn.num_batches_tracked", "Mixed_6d.branch7x7dbl_3.conv.weight", "Mixed_6d.branch7x7dbl_3.bn.weight", "Mixed_6d.branch7x7dbl_3.bn.bias", "Mixed_6d.branch7x7dbl_3.bn.running_mean", "Mixed_6d.branch7x7dbl_3.bn.running_var", "Mixed_6d.branch7x7dbl_3.bn.num_batches_tracked", "Mixed_6d.branch7x7dbl_4.conv.weight", "Mixed_6d.branch7x7dbl_4.bn.weight", "Mixed_6d.branch7x7dbl_4.bn.bias", "Mixed_6d.branch7x7dbl_4.bn.running_mean", "Mixed_6d.branch7x7dbl_4.bn.running_var", "Mixed_6d.branch7x7dbl_4.bn.num_batches_tracked", "Mixed_6d.branch7x7dbl_5.conv.weight", "Mixed_6d.branch7x7dbl_5.bn.weight", "Mixed_6d.branch7x7dbl_5.bn.bias", "Mixed_6d.branch7x7dbl_5.bn.running_mean", "Mixed_6d.branch7x7dbl_5.bn.running_var", "Mixed_6d.branch7x7dbl_5.bn.num_batches_tracked", "Mixed_6d.branch_pool.conv.weight", "Mixed_6d.branch_pool.bn.weight", "Mixed_6d.branch_pool.bn.bias", "Mixed_6d.branch_pool.bn.running_mean", "Mixed_6d.branch_pool.bn.running_var", "Mixed_6d.branch_pool.bn.num_batches_tracked", "Mixed_6e.branch1x1.conv.weight", "Mixed_6e.branch1x1.bn.weight", "Mixed_6e.branch1x1.bn.bias", "Mixed_6e.branch1x1.bn.running_mean", "Mixed_6e.branch1x1.bn.running_var", "Mixed_6e.branch1x1.bn.num_batches_tracked", "Mixed_6e.branch7x7_1.conv.weight", "Mixed_6e.branch7x7_1.bn.weight", "Mixed_6e.branch7x7_1.bn.bias", "Mixed_6e.branch7x7_1.bn.running_mean", "Mixed_6e.branch7x7_1.bn.running_var", "Mixed_6e.branch7x7_1.bn.num_batches_tracked", "Mixed_6e.branch7x7_2.conv.weight", "Mixed_6e.branch7x7_2.bn.weight", "Mixed_6e.branch7x7_2.bn.bias", "Mixed_6e.branch7x7_2.bn.running_mean", "Mixed_6e.branch7x7_2.bn.running_var", "Mixed_6e.branch7x7_2.bn.num_batches_tracked", "Mixed_6e.branch7x7_3.conv.weight", "Mixed_6e.branch7x7_3.bn.weight", "Mixed_6e.branch7x7_3.bn.bias", "Mixed_6e.branch7x7_3.bn.running_mean", "Mixed_6e.branch7x7_3.bn.running_var", "Mixed_6e.branch7x7_3.bn.num_batches_tracked", "Mixed_6e.branch7x7dbl_1.conv.weight", "Mixed_6e.branch7x7dbl_1.bn.weight", "Mixed_6e.branch7x7dbl_1.bn.bias", "Mixed_6e.branch7x7dbl_1.bn.running_mean", "Mixed_6e.branch7x7dbl_1.bn.running_var", "Mixed_6e.branch7x7dbl_1.bn.num_batches_tracked", "Mixed_6e.branch7x7dbl_2.conv.weight", "Mixed_6e.branch7x7dbl_2.bn.weight", "Mixed_6e.branch7x7dbl_2.bn.bias", "Mixed_6e.branch7x7dbl_2.bn.running_mean", "Mixed_6e.branch7x7dbl_2.bn.running_var", "Mixed_6e.branch7x7dbl_2.bn.num_batches_tracked", "Mixed_6e.branch7x7dbl_3.conv.weight", "Mixed_6e.branch7x7dbl_3.bn.weight", "Mixed_6e.branch7x7dbl_3.bn.bias", "Mixed_6e.branch7x7dbl_3.bn.running_mean", "Mixed_6e.branch7x7dbl_3.bn.running_var", "Mixed_6e.branch7x7dbl_3.bn.num_batches_tracked", "Mixed_6e.branch7x7dbl_4.conv.weight", "Mixed_6e.branch7x7dbl_4.bn.weight", "Mixed_6e.branch7x7dbl_4.bn.bias", "Mixed_6e.branch7x7dbl_4.bn.running_mean", "Mixed_6e.branch7x7dbl_4.bn.running_var", "Mixed_6e.branch7x7dbl_4.bn.num_batches_tracked", "Mixed_6e.branch7x7dbl_5.conv.weight", "Mixed_6e.branch7x7dbl_5.bn.weight", "Mixed_6e.branch7x7dbl_5.bn.bias", "Mixed_6e.branch7x7dbl_5.bn.running_mean", "Mixed_6e.branch7x7dbl_5.bn.running_var", "Mixed_6e.branch7x7dbl_5.bn.num_batches_tracked", "Mixed_6e.branch_pool.conv.weight", "Mixed_6e.branch_pool.bn.weight", "Mixed_6e.branch_pool.bn.bias", "Mixed_6e.branch_pool.bn.running_mean", "Mixed_6e.branch_pool.bn.running_var", "Mixed_6e.branch_pool.bn.num_batches_tracked".
zengxunli commented 2 years ago

并且在您的base_model.py中，CAD所使用的base model是硬编码，使用的backbone是inv3，https://github.com/JacobYuan7/DIN-Group-Activity-Recognition-Benchmark/blob/main/base_model.py#:~:text=cfg.num_features_gcn-,self.backbone%3DMyInception_v3(transform_input%3DFalse%2Cpretrained,%23%20%20%20%20%20%20%20%20%20self.backbone%3DMyVGG16(pretrained%3DTrue),-if%20not%20self

当我将它改成ResNet18，并且重新开始一阶段训练时，它又产生了如下错误：

  File "/home/disk1/zxl/model/DIN-Group-Activity-Recognition-Benchmark-main/./base_model.py", line 260, in forward
    boxes_features_all=self.fc_emb_1(boxes_features_all)  # B*T,MAX_N, NFB
  File "/home/disk1/zxl/anaconda3/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/disk1/zxl/anaconda3/lib/python3.9/site-packages/torch/nn/modules/linear.py", line 103, in forward
    return F.linear(input, self.weight, self.bias)
RuntimeError: mat1 and mat2 shapes cannot be multiplied (52x12800 and 26400x1024)
JacobYuan7 commented 2 years ago

您好，感谢您开源的代码。VD的一二阶段训练都是顺利的，但是我在训练CAD时，第一阶段使用resnet18训练，但是在第二阶段遇到了权重载入的错误，模型配置文件完全是默认未改动的，您可以帮我看看这是为什么吗

    raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for MyRes18:
        Missing key(s) in state_dict: "features.0.weight", "features.1.weight", "features.1.bias", "features.1.running_mean", "features.1.running_var", "features.4.0.conv1.weight", "features.4.0.bn1.weight", "features.4.0.bn1.bias", "features.4.0.bn1.running_mean", "features.4.0.bn1.running_var", "features.4.0.conv2.weight", "features.4.0.bn2.weight", "features.4.0.bn2.bias", "features.4.0.bn2.running_mean", "features.4.0.bn2.running_var", "features.4.1.conv1.weight", "features.4.1.bn1.weight", "features.4.1.bn1.bias", "features.4.1.bn1.running_mean", "features.4.1.bn1.running_var", "features.4.1.conv2.weight", "features.4.1.bn2.weight", "features.4.1.bn2.bias", "features.4.1.bn2.running_mean", "features.4.1.bn2.running_var", "features.5.0.conv1.weight", "features.5.0.bn1.weight", "features.5.0.bn1.bias", "features.5.0.bn1.running_mean", "features.5.0.bn1.running_var", "features.5.0.conv2.weight", "features.5.0.bn2.weight", "features.5.0.bn2.bias", "features.5.0.bn2.running_mean", "features.5.0.bn2.running_var", "features.5.0.downsample.0.weight", "features.5.0.downsample.1.weight", "features.5.0.downsample.1.bias", "features.5.0.downsample.1.running_mean", "features.5.0.downsample.1.running_var", "features.5.1.conv1.weight", "features.5.1.bn1.weight", "features.5.1.bn1.bias", "features.5.1.bn1.running_mean", "features.5.1.bn1.running_var", "features.5.1.conv2.weight", "features.5.1.bn2.weight", "features.5.1.bn2.bias", "features.5.1.bn2.running_mean", "features.5.1.bn2.running_var", "features.6.0.conv1.weight", "features.6.0.bn1.weight", "features.6.0.bn1.bias", "features.6.0.bn1.running_mean", "features.6.0.bn1.running_var", "features.6.0.conv2.weight", "features.6.0.bn2.weight", "features.6.0.bn2.bias", "features.6.0.bn2.running_mean", "features.6.0.bn2.running_var", "features.6.0.downsample.0.weight", "features.6.0.downsample.1.weight", "features.6.0.downsample.1.bias", "features.6.0.downsample.1.running_mean", "features.6.0.downsample.1.running_var", "features.6.1.conv1.weight", "features.6.1.bn1.weight", "features.6.1.bn1.bias", "features.6.1.bn1.running_mean", "features.6.1.bn1.running_var", "features.6.1.conv2.weight", "features.6.1.bn2.weight", "features.6.1.bn2.bias", "features.6.1.bn2.running_mean", "features.6.1.bn2.running_var", "features.7.0.conv1.weight", "features.7.0.bn1.weight", "features.7.0.bn1.bias", "features.7.0.bn1.running_mean", "features.7.0.bn1.running_var", "features.7.0.conv2.weight", "features.7.0.bn2.weight", "features.7.0.bn2.bias", "features.7.0.bn2.running_mean", "features.7.0.bn2.running_var", "features.7.0.downsample.0.weight", "features.7.0.downsample.1.weight", "features.7.0.downsample.1.bias", "features.7.0.downsample.1.running_mean", "features.7.0.downsample.1.running_var", "features.7.1.conv1.weight", "features.7.1.bn1.weight", "features.7.1.bn1.bias", "features.7.1.bn1.running_mean", "features.7.1.bn1.running_var", "features.7.1.conv2.weight", "features.7.1.bn2.weight", "features.7.1.bn2.bias", "features.7.1.bn2.running_mean", "features.7.1.bn2.running_var". 
        Unexpected key(s) in state_dict: "Conv2d_1a_3x3.conv.weight", "Conv2d_1a_3x3.bn.weight", "Conv2d_1a_3x3.bn.bias", "Conv2d_1a_3x3.bn.running_mean", "Conv2d_1a_3x3.bn.running_var", "Conv2d_1a_3x3.bn.num_batches_tracked", "Conv2d_2a_3x3.conv.weight", "Conv2d_2a_3x3.bn.weight", "Conv2d_2a_3x3.bn.bias", "Conv2d_2a_3x3.bn.running_mean", "Conv2d_2a_3x3.bn.running_var", "Conv2d_2a_3x3.bn.num_batches_tracked", "Conv2d_2b_3x3.conv.weight", "Conv2d_2b_3x3.bn.weight", "Conv2d_2b_3x3.bn.bias", "Conv2d_2b_3x3.bn.running_mean", "Conv2d_2b_3x3.bn.running_var", "Conv2d_2b_3x3.bn.num_batches_tracked", "Conv2d_3b_1x1.conv.weight", "Conv2d_3b_1x1.bn.weight", "Conv2d_3b_1x1.bn.bias", "Conv2d_3b_1x1.bn.running_mean", "Conv2d_3b_1x1.bn.running_var", "Conv2d_3b_1x1.bn.num_batches_tracked", "Conv2d_4a_3x3.conv.weight", "Conv2d_4a_3x3.bn.weight", "Conv2d_4a_3x3.bn.bias", "Conv2d_4a_3x3.bn.running_mean", "Conv2d_4a_3x3.bn.running_var", "Conv2d_4a_3x3.bn.num_batches_tracked", "Mixed_5b.branch1x1.conv.weight", "Mixed_5b.branch1x1.bn.weight", "Mixed_5b.branch1x1.bn.bias", "Mixed_5b.branch1x1.bn.running_mean", "Mixed_5b.branch1x1.bn.running_var", "Mixed_5b.branch1x1.bn.num_batches_tracked", "Mixed_5b.branch5x5_1.conv.weight", "Mixed_5b.branch5x5_1.bn.weight", "Mixed_5b.branch5x5_1.bn.bias", "Mixed_5b.branch5x5_1.bn.running_mean", "Mixed_5b.branch5x5_1.bn.running_var", "Mixed_5b.branch5x5_1.bn.num_batches_tracked", "Mixed_5b.branch5x5_2.conv.weight", "Mixed_5b.branch5x5_2.bn.weight", "Mixed_5b.branch5x5_2.bn.bias", "Mixed_5b.branch5x5_2.bn.running_mean", "Mixed_5b.branch5x5_2.bn.running_var", "Mixed_5b.branch5x5_2.bn.num_batches_tracked", "Mixed_5b.branch3x3dbl_1.conv.weight", "Mixed_5b.branch3x3dbl_1.bn.weight", "Mixed_5b.branch3x3dbl_1.bn.bias", "Mixed_5b.branch3x3dbl_1.bn.running_mean", "Mixed_5b.branch3x3dbl_1.bn.running_var", "Mixed_5b.branch3x3dbl_1.bn.num_batches_tracked", "Mixed_5b.branch3x3dbl_2.conv.weight", "Mixed_5b.branch3x3dbl_2.bn.weight", "Mixed_5b.branch3x3dbl_2.bn.bias", "Mixed_5b.branch3x3dbl_2.bn.running_mean", "Mixed_5b.branch3x3dbl_2.bn.running_var", "Mixed_5b.branch3x3dbl_2.bn.num_batches_tracked", "Mixed_5b.branch3x3dbl_3.conv.weight", "Mixed_5b.branch3x3dbl_3.bn.weight", "Mixed_5b.branch3x3dbl_3.bn.bias", "Mixed_5b.branch3x3dbl_3.bn.running_mean", "Mixed_5b.branch3x3dbl_3.bn.running_var", "Mixed_5b.branch3x3dbl_3.bn.num_batches_tracked", "Mixed_5b.branch_pool.conv.weight", "Mixed_5b.branch_pool.bn.weight", "Mixed_5b.branch_pool.bn.bias", "Mixed_5b.branch_pool.bn.running_mean", "Mixed_5b.branch_pool.bn.running_var", "Mixed_5b.branch_pool.bn.num_batches_tracked", "Mixed_5c.branch1x1.conv.weight", "Mixed_5c.branch1x1.bn.weight", "Mixed_5c.branch1x1.bn.bias", "Mixed_5c.branch1x1.bn.running_mean", "Mixed_5c.branch1x1.bn.running_var", "Mixed_5c.branch1x1.bn.num_batches_tracked", "Mixed_5c.branch5x5_1.conv.weight", "Mixed_5c.branch5x5_1.bn.weight", "Mixed_5c.branch5x5_1.bn.bias", "Mixed_5c.branch5x5_1.bn.running_mean", "Mixed_5c.branch5x5_1.bn.running_var", "Mixed_5c.branch5x5_1.bn.num_batches_tracked", "Mixed_5c.branch5x5_2.conv.weight", "Mixed_5c.branch5x5_2.bn.weight", "Mixed_5c.branch5x5_2.bn.bias", "Mixed_5c.branch5x5_2.bn.running_mean", "Mixed_5c.branch5x5_2.bn.running_var", "Mixed_5c.branch5x5_2.bn.num_batches_tracked", "Mixed_5c.branch3x3dbl_1.conv.weight", "Mixed_5c.branch3x3dbl_1.bn.weight", "Mixed_5c.branch3x3dbl_1.bn.bias", "Mixed_5c.branch3x3dbl_1.bn.running_mean", "Mixed_5c.branch3x3dbl_1.bn.running_var", "Mixed_5c.branch3x3dbl_1.bn.num_batches_tracked", "Mixed_5c.branch3x3dbl_2.conv.weight", "Mixed_5c.branch3x3dbl_2.bn.weight", "Mixed_5c.branch3x3dbl_2.bn.bias", "Mixed_5c.branch3x3dbl_2.bn.running_mean", "Mixed_5c.branch3x3dbl_2.bn.running_var", "Mixed_5c.branch3x3dbl_2.bn.num_batches_tracked", "Mixed_5c.branch3x3dbl_3.conv.weight", "Mixed_5c.branch3x3dbl_3.bn.weight", "Mixed_5c.branch3x3dbl_3.bn.bias", "Mixed_5c.branch3x3dbl_3.bn.running_mean", "Mixed_5c.branch3x3dbl_3.bn.running_var", "Mixed_5c.branch3x3dbl_3.bn.num_batches_tracked", "Mixed_5c.branch_pool.conv.weight", "Mixed_5c.branch_pool.bn.weight", "Mixed_5c.branch_pool.bn.bias", "Mixed_5c.branch_pool.bn.running_mean", "Mixed_5c.branch_pool.bn.running_var", "Mixed_5c.branch_pool.bn.num_batches_tracked", "Mixed_5d.branch1x1.conv.weight", "Mixed_5d.branch1x1.bn.weight", "Mixed_5d.branch1x1.bn.bias", "Mixed_5d.branch1x1.bn.running_mean", "Mixed_5d.branch1x1.bn.running_var", "Mixed_5d.branch1x1.bn.num_batches_tracked", "Mixed_5d.branch5x5_1.conv.weight", "Mixed_5d.branch5x5_1.bn.weight", "Mixed_5d.branch5x5_1.bn.bias", "Mixed_5d.branch5x5_1.bn.running_mean", "Mixed_5d.branch5x5_1.bn.running_var", "Mixed_5d.branch5x5_1.bn.num_batches_tracked", "Mixed_5d.branch5x5_2.conv.weight", "Mixed_5d.branch5x5_2.bn.weight", "Mixed_5d.branch5x5_2.bn.bias", "Mixed_5d.branch5x5_2.bn.running_mean", "Mixed_5d.branch5x5_2.bn.running_var", "Mixed_5d.branch5x5_2.bn.num_batches_tracked", "Mixed_5d.branch3x3dbl_1.conv.weight", "Mixed_5d.branch3x3dbl_1.bn.weight", "Mixed_5d.branch3x3dbl_1.bn.bias", "Mixed_5d.branch3x3dbl_1.bn.running_mean", "Mixed_5d.branch3x3dbl_1.bn.running_var", "Mixed_5d.branch3x3dbl_1.bn.num_batches_tracked", "Mixed_5d.branch3x3dbl_2.conv.weight", "Mixed_5d.branch3x3dbl_2.bn.weight", "Mixed_5d.branch3x3dbl_2.bn.bias", "Mixed_5d.branch3x3dbl_2.bn.running_mean", "Mixed_5d.branch3x3dbl_2.bn.running_var", "Mixed_5d.branch3x3dbl_2.bn.num_batches_tracked", "Mixed_5d.branch3x3dbl_3.conv.weight", "Mixed_5d.branch3x3dbl_3.bn.weight", "Mixed_5d.branch3x3dbl_3.bn.bias", "Mixed_5d.branch3x3dbl_3.bn.running_mean", "Mixed_5d.branch3x3dbl_3.bn.running_var", "Mixed_5d.branch3x3dbl_3.bn.num_batches_tracked", "Mixed_5d.branch_pool.conv.weight", "Mixed_5d.branch_pool.bn.weight", "Mixed_5d.branch_pool.bn.bias", "Mixed_5d.branch_pool.bn.running_mean", "Mixed_5d.branch_pool.bn.running_var", "Mixed_5d.branch_pool.bn.num_batches_tracked", "Mixed_6a.branch3x3.conv.weight", "Mixed_6a.branch3x3.bn.weight", "Mixed_6a.branch3x3.bn.bias", "Mixed_6a.branch3x3.bn.running_mean", "Mixed_6a.branch3x3.bn.running_var", "Mixed_6a.branch3x3.bn.num_batches_tracked", "Mixed_6a.branch3x3dbl_1.conv.weight", "Mixed_6a.branch3x3dbl_1.bn.weight", "Mixed_6a.branch3x3dbl_1.bn.bias", "Mixed_6a.branch3x3dbl_1.bn.running_mean", "Mixed_6a.branch3x3dbl_1.bn.running_var", "Mixed_6a.branch3x3dbl_1.bn.num_batches_tracked", "Mixed_6a.branch3x3dbl_2.conv.weight", "Mixed_6a.branch3x3dbl_2.bn.weight", "Mixed_6a.branch3x3dbl_2.bn.bias", "Mixed_6a.branch3x3dbl_2.bn.running_mean", "Mixed_6a.branch3x3dbl_2.bn.running_var", "Mixed_6a.branch3x3dbl_2.bn.num_batches_tracked", "Mixed_6a.branch3x3dbl_3.conv.weight", "Mixed_6a.branch3x3dbl_3.bn.weight", "Mixed_6a.branch3x3dbl_3.bn.bias", "Mixed_6a.branch3x3dbl_3.bn.running_mean", "Mixed_6a.branch3x3dbl_3.bn.running_var", "Mixed_6a.branch3x3dbl_3.bn.num_batches_tracked", "Mixed_6b.branch1x1.conv.weight", "Mixed_6b.branch1x1.bn.weight", "Mixed_6b.branch1x1.bn.bias", "Mixed_6b.branch1x1.bn.running_mean", "Mixed_6b.branch1x1.bn.running_var", "Mixed_6b.branch1x1.bn.num_batches_tracked", "Mixed_6b.branch7x7_1.conv.weight", "Mixed_6b.branch7x7_1.bn.weight", "Mixed_6b.branch7x7_1.bn.bias", "Mixed_6b.branch7x7_1.bn.running_mean", "Mixed_6b.branch7x7_1.bn.running_var", "Mixed_6b.branch7x7_1.bn.num_batches_tracked", "Mixed_6b.branch7x7_2.conv.weight", "Mixed_6b.branch7x7_2.bn.weight", "Mixed_6b.branch7x7_2.bn.bias", "Mixed_6b.branch7x7_2.bn.running_mean", "Mixed_6b.branch7x7_2.bn.running_var", "Mixed_6b.branch7x7_2.bn.num_batches_tracked", "Mixed_6b.branch7x7_3.conv.weight", "Mixed_6b.branch7x7_3.bn.weight", "Mixed_6b.branch7x7_3.bn.bias", "Mixed_6b.branch7x7_3.bn.running_mean", "Mixed_6b.branch7x7_3.bn.running_var", "Mixed_6b.branch7x7_3.bn.num_batches_tracked", "Mixed_6b.branch7x7dbl_1.conv.weight", "Mixed_6b.branch7x7dbl_1.bn.weight", "Mixed_6b.branch7x7dbl_1.bn.bias", "Mixed_6b.branch7x7dbl_1.bn.running_mean", "Mixed_6b.branch7x7dbl_1.bn.running_var", "Mixed_6b.branch7x7dbl_1.bn.num_batches_tracked", "Mixed_6b.branch7x7dbl_2.conv.weight", "Mixed_6b.branch7x7dbl_2.bn.weight", "Mixed_6b.branch7x7dbl_2.bn.bias", "Mixed_6b.branch7x7dbl_2.bn.running_mean", "Mixed_6b.branch7x7dbl_2.bn.running_var", "Mixed_6b.branch7x7dbl_2.bn.num_batches_tracked", "Mixed_6b.branch7x7dbl_3.conv.weight", "Mixed_6b.branch7x7dbl_3.bn.weight", "Mixed_6b.branch7x7dbl_3.bn.bias", "Mixed_6b.branch7x7dbl_3.bn.running_mean", "Mixed_6b.branch7x7dbl_3.bn.running_var", "Mixed_6b.branch7x7dbl_3.bn.num_batches_tracked", "Mixed_6b.branch7x7dbl_4.conv.weight", "Mixed_6b.branch7x7dbl_4.bn.weight", "Mixed_6b.branch7x7dbl_4.bn.bias", "Mixed_6b.branch7x7dbl_4.bn.running_mean", "Mixed_6b.branch7x7dbl_4.bn.running_var", "Mixed_6b.branch7x7dbl_4.bn.num_batches_tracked", "Mixed_6b.branch7x7dbl_5.conv.weight", "Mixed_6b.branch7x7dbl_5.bn.weight", "Mixed_6b.branch7x7dbl_5.bn.bias", "Mixed_6b.branch7x7dbl_5.bn.running_mean", "Mixed_6b.branch7x7dbl_5.bn.running_var", "Mixed_6b.branch7x7dbl_5.bn.num_batches_tracked", "Mixed_6b.branch_pool.conv.weight", "Mixed_6b.branch_pool.bn.weight", "Mixed_6b.branch_pool.bn.bias", "Mixed_6b.branch_pool.bn.running_mean", "Mixed_6b.branch_pool.bn.running_var", "Mixed_6b.branch_pool.bn.num_batches_tracked", "Mixed_6c.branch1x1.conv.weight", "Mixed_6c.branch1x1.bn.weight", "Mixed_6c.branch1x1.bn.bias", "Mixed_6c.branch1x1.bn.running_mean", "Mixed_6c.branch1x1.bn.running_var", "Mixed_6c.branch1x1.bn.num_batches_tracked", "Mixed_6c.branch7x7_1.conv.weight", "Mixed_6c.branch7x7_1.bn.weight", "Mixed_6c.branch7x7_1.bn.bias", "Mixed_6c.branch7x7_1.bn.running_mean", "Mixed_6c.branch7x7_1.bn.running_var", "Mixed_6c.branch7x7_1.bn.num_batches_tracked", "Mixed_6c.branch7x7_2.conv.weight", "Mixed_6c.branch7x7_2.bn.weight", "Mixed_6c.branch7x7_2.bn.bias", "Mixed_6c.branch7x7_2.bn.running_mean", "Mixed_6c.branch7x7_2.bn.running_var", "Mixed_6c.branch7x7_2.bn.num_batches_tracked", "Mixed_6c.branch7x7_3.conv.weight", "Mixed_6c.branch7x7_3.bn.weight", "Mixed_6c.branch7x7_3.bn.bias", "Mixed_6c.branch7x7_3.bn.running_mean", "Mixed_6c.branch7x7_3.bn.running_var", "Mixed_6c.branch7x7_3.bn.num_batches_tracked", "Mixed_6c.branch7x7dbl_1.conv.weight", "Mixed_6c.branch7x7dbl_1.bn.weight", "Mixed_6c.branch7x7dbl_1.bn.bias", "Mixed_6c.branch7x7dbl_1.bn.running_mean", "Mixed_6c.branch7x7dbl_1.bn.running_var", "Mixed_6c.branch7x7dbl_1.bn.num_batches_tracked", "Mixed_6c.branch7x7dbl_2.conv.weight", "Mixed_6c.branch7x7dbl_2.bn.weight", "Mixed_6c.branch7x7dbl_2.bn.bias", "Mixed_6c.branch7x7dbl_2.bn.running_mean", "Mixed_6c.branch7x7dbl_2.bn.running_var", "Mixed_6c.branch7x7dbl_2.bn.num_batches_tracked", "Mixed_6c.branch7x7dbl_3.conv.weight", "Mixed_6c.branch7x7dbl_3.bn.weight", "Mixed_6c.branch7x7dbl_3.bn.bias", "Mixed_6c.branch7x7dbl_3.bn.running_mean", "Mixed_6c.branch7x7dbl_3.bn.running_var", "Mixed_6c.branch7x7dbl_3.bn.num_batches_tracked", "Mixed_6c.branch7x7dbl_4.conv.weight", "Mixed_6c.branch7x7dbl_4.bn.weight", "Mixed_6c.branch7x7dbl_4.bn.bias", "Mixed_6c.branch7x7dbl_4.bn.running_mean", "Mixed_6c.branch7x7dbl_4.bn.running_var", "Mixed_6c.branch7x7dbl_4.bn.num_batches_tracked", "Mixed_6c.branch7x7dbl_5.conv.weight", "Mixed_6c.branch7x7dbl_5.bn.weight", "Mixed_6c.branch7x7dbl_5.bn.bias", "Mixed_6c.branch7x7dbl_5.bn.running_mean", "Mixed_6c.branch7x7dbl_5.bn.running_var", "Mixed_6c.branch7x7dbl_5.bn.num_batches_tracked", "Mixed_6c.branch_pool.conv.weight", "Mixed_6c.branch_pool.bn.weight", "Mixed_6c.branch_pool.bn.bias", "Mixed_6c.branch_pool.bn.running_mean", "Mixed_6c.branch_pool.bn.running_var", "Mixed_6c.branch_pool.bn.num_batches_tracked", "Mixed_6d.branch1x1.conv.weight", "Mixed_6d.branch1x1.bn.weight", "Mixed_6d.branch1x1.bn.bias", "Mixed_6d.branch1x1.bn.running_mean", "Mixed_6d.branch1x1.bn.running_var", "Mixed_6d.branch1x1.bn.num_batches_tracked", "Mixed_6d.branch7x7_1.conv.weight", "Mixed_6d.branch7x7_1.bn.weight", "Mixed_6d.branch7x7_1.bn.bias", "Mixed_6d.branch7x7_1.bn.running_mean", "Mixed_6d.branch7x7_1.bn.running_var", "Mixed_6d.branch7x7_1.bn.num_batches_tracked", "Mixed_6d.branch7x7_2.conv.weight", "Mixed_6d.branch7x7_2.bn.weight", "Mixed_6d.branch7x7_2.bn.bias", "Mixed_6d.branch7x7_2.bn.running_mean", "Mixed_6d.branch7x7_2.bn.running_var", "Mixed_6d.branch7x7_2.bn.num_batches_tracked", "Mixed_6d.branch7x7_3.conv.weight", "Mixed_6d.branch7x7_3.bn.weight", "Mixed_6d.branch7x7_3.bn.bias", "Mixed_6d.branch7x7_3.bn.running_mean", "Mixed_6d.branch7x7_3.bn.running_var", "Mixed_6d.branch7x7_3.bn.num_batches_tracked", "Mixed_6d.branch7x7dbl_1.conv.weight", "Mixed_6d.branch7x7dbl_1.bn.weight", "Mixed_6d.branch7x7dbl_1.bn.bias", "Mixed_6d.branch7x7dbl_1.bn.running_mean", "Mixed_6d.branch7x7dbl_1.bn.running_var", "Mixed_6d.branch7x7dbl_1.bn.num_batches_tracked", "Mixed_6d.branch7x7dbl_2.conv.weight", "Mixed_6d.branch7x7dbl_2.bn.weight", "Mixed_6d.branch7x7dbl_2.bn.bias", "Mixed_6d.branch7x7dbl_2.bn.running_mean", "Mixed_6d.branch7x7dbl_2.bn.running_var", "Mixed_6d.branch7x7dbl_2.bn.num_batches_tracked", "Mixed_6d.branch7x7dbl_3.conv.weight", "Mixed_6d.branch7x7dbl_3.bn.weight", "Mixed_6d.branch7x7dbl_3.bn.bias", "Mixed_6d.branch7x7dbl_3.bn.running_mean", "Mixed_6d.branch7x7dbl_3.bn.running_var", "Mixed_6d.branch7x7dbl_3.bn.num_batches_tracked", "Mixed_6d.branch7x7dbl_4.conv.weight", "Mixed_6d.branch7x7dbl_4.bn.weight", "Mixed_6d.branch7x7dbl_4.bn.bias", "Mixed_6d.branch7x7dbl_4.bn.running_mean", "Mixed_6d.branch7x7dbl_4.bn.running_var", "Mixed_6d.branch7x7dbl_4.bn.num_batches_tracked", "Mixed_6d.branch7x7dbl_5.conv.weight", "Mixed_6d.branch7x7dbl_5.bn.weight", "Mixed_6d.branch7x7dbl_5.bn.bias", "Mixed_6d.branch7x7dbl_5.bn.running_mean", "Mixed_6d.branch7x7dbl_5.bn.running_var", "Mixed_6d.branch7x7dbl_5.bn.num_batches_tracked", "Mixed_6d.branch_pool.conv.weight", "Mixed_6d.branch_pool.bn.weight", "Mixed_6d.branch_pool.bn.bias", "Mixed_6d.branch_pool.bn.running_mean", "Mixed_6d.branch_pool.bn.running_var", "Mixed_6d.branch_pool.bn.num_batches_tracked", "Mixed_6e.branch1x1.conv.weight", "Mixed_6e.branch1x1.bn.weight", "Mixed_6e.branch1x1.bn.bias", "Mixed_6e.branch1x1.bn.running_mean", "Mixed_6e.branch1x1.bn.running_var", "Mixed_6e.branch1x1.bn.num_batches_tracked", "Mixed_6e.branch7x7_1.conv.weight", "Mixed_6e.branch7x7_1.bn.weight", "Mixed_6e.branch7x7_1.bn.bias", "Mixed_6e.branch7x7_1.bn.running_mean", "Mixed_6e.branch7x7_1.bn.running_var", "Mixed_6e.branch7x7_1.bn.num_batches_tracked", "Mixed_6e.branch7x7_2.conv.weight", "Mixed_6e.branch7x7_2.bn.weight", "Mixed_6e.branch7x7_2.bn.bias", "Mixed_6e.branch7x7_2.bn.running_mean", "Mixed_6e.branch7x7_2.bn.running_var", "Mixed_6e.branch7x7_2.bn.num_batches_tracked", "Mixed_6e.branch7x7_3.conv.weight", "Mixed_6e.branch7x7_3.bn.weight", "Mixed_6e.branch7x7_3.bn.bias", "Mixed_6e.branch7x7_3.bn.running_mean", "Mixed_6e.branch7x7_3.bn.running_var", "Mixed_6e.branch7x7_3.bn.num_batches_tracked", "Mixed_6e.branch7x7dbl_1.conv.weight", "Mixed_6e.branch7x7dbl_1.bn.weight", "Mixed_6e.branch7x7dbl_1.bn.bias", "Mixed_6e.branch7x7dbl_1.bn.running_mean", "Mixed_6e.branch7x7dbl_1.bn.running_var", "Mixed_6e.branch7x7dbl_1.bn.num_batches_tracked", "Mixed_6e.branch7x7dbl_2.conv.weight", "Mixed_6e.branch7x7dbl_2.bn.weight", "Mixed_6e.branch7x7dbl_2.bn.bias", "Mixed_6e.branch7x7dbl_2.bn.running_mean", "Mixed_6e.branch7x7dbl_2.bn.running_var", "Mixed_6e.branch7x7dbl_2.bn.num_batches_tracked", "Mixed_6e.branch7x7dbl_3.conv.weight", "Mixed_6e.branch7x7dbl_3.bn.weight", "Mixed_6e.branch7x7dbl_3.bn.bias", "Mixed_6e.branch7x7dbl_3.bn.running_mean", "Mixed_6e.branch7x7dbl_3.bn.running_var", "Mixed_6e.branch7x7dbl_3.bn.num_batches_tracked", "Mixed_6e.branch7x7dbl_4.conv.weight", "Mixed_6e.branch7x7dbl_4.bn.weight", "Mixed_6e.branch7x7dbl_4.bn.bias", "Mixed_6e.branch7x7dbl_4.bn.running_mean", "Mixed_6e.branch7x7dbl_4.bn.running_var", "Mixed_6e.branch7x7dbl_4.bn.num_batches_tracked", "Mixed_6e.branch7x7dbl_5.conv.weight", "Mixed_6e.branch7x7dbl_5.bn.weight", "Mixed_6e.branch7x7dbl_5.bn.bias", "Mixed_6e.branch7x7dbl_5.bn.running_mean", "Mixed_6e.branch7x7dbl_5.bn.running_var", "Mixed_6e.branch7x7dbl_5.bn.num_batches_tracked", "Mixed_6e.branch_pool.conv.weight", "Mixed_6e.branch_pool.bn.weight", "Mixed_6e.branch_pool.bn.bias", "Mixed_6e.branch_pool.bn.running_mean", "Mixed_6e.branch_pool.bn.running_var", "Mixed_6e.branch_pool.bn.num_batches_tracked".

I think the model and the parameters you are using seem different. One is for ResNet-18 and the other is for Inception-v3.

zengxunli commented 2 years ago

是的，读过代码后发现，第二阶段载入的模型是resnet18，第一阶段的模型是固定了的inv3 https://github.com/JacobYuan7/DIN-Group-Activity-Recognition-Benchmark/blob/4648310a42ca7b66013da9d623e9f856a483f30c/base_model.py#L158

并且在您的base_model.py中，CAD所使用的base model是硬编码，使用的backbone是inv3，https://github.com/JacobYuan7/DIN-Group-Activity-Recognition-Benchmark/blob/main/base_model.py#:~:text=cfg.num_features_gcn-,self.backbone%3DMyInception_v3(transform_input%3DFalse%2Cpretrained,%23%20%20%20%20%20%20%20%20%20self.backbone%3DMyVGG16(pretrained%3DTrue),-if%20not%20self

当我将它改成ResNet18，并且重新开始一阶段训练时，它又产生了如下错误：

  File "/home/disk1/zxl/model/DIN-Group-Activity-Recognition-Benchmark-main/./base_model.py", line 260, in forward
    boxes_features_all=self.fc_emb_1(boxes_features_all)  # B*T,MAX_N, NFB
  File "/home/disk1/zxl/anaconda3/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/disk1/zxl/anaconda3/lib/python3.9/site-packages/torch/nn/modules/linear.py", line 103, in forward
    return F.linear(input, self.weight, self.bias)
RuntimeError: mat1 and mat2 shapes cannot be multiplied (52x12800 and 26400x1024)
JacobYuan7 commented 2 years ago

并且在您的base_model.py中，CAD所使用的base model是硬编码，使用的backbone是inv3，https://github.com/JacobYuan7/DIN-Group-Activity-Recognition-Benchmark/blob/main/base_model.py#:~:text=cfg.num_features_gcn-,self.backbone%3DMyInception_v3(transform_input%3DFalse%2Cpretrained,%23%20%20%20%20%20%20%20%20%20self.backbone%3DMyVGG16(pretrained%3DTrue),-if%20not%20self

当我将它改成ResNet18，并且重新开始一阶段训练时，它又产生了如下错误：

  File "/home/disk1/zxl/model/DIN-Group-Activity-Recognition-Benchmark-main/./base_model.py", line 260, in forward
    boxes_features_all=self.fc_emb_1(boxes_features_all)  # B*T,MAX_N, NFB
  File "/home/disk1/zxl/anaconda3/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/disk1/zxl/anaconda3/lib/python3.9/site-packages/torch/nn/modules/linear.py", line 103, in forward
    return F.linear(input, self.weight, self.bias)
RuntimeError: mat1 and mat2 shapes cannot be multiplied (52x12800 and 26400x1024)

You may need to add codes for stage1 to this part by copying from base_volleyball. It should work. If you are training with resnet-18, you also need to change the out_size in the script to align it with the actual output size from resnet-18.

zengxunli commented 2 years ago

并且在您的base_model.py中，CAD所使用的base model是硬编码，使用的backbone是inv3，https://github.com/JacobYuan7/DIN-Group-Activity-Recognition-Benchmark/blob/main/base_model.py#:~:text=cfg.num_features_gcn-,self.backbone%3DMyInception_v3(transform_input%3DFalse%2Cpretrained,%23%20%20%20%20%20%20%20%20%20self.backbone%3DMyVGG16(pretrained%3DTrue),-if%20not%20self 当我将它改成ResNet18，并且重新开始一阶段训练时，它又产生了如下错误：

  File "/home/disk1/zxl/model/DIN-Group-Activity-Recognition-Benchmark-main/./base_model.py", line 260, in forward
    boxes_features_all=self.fc_emb_1(boxes_features_all)  # B*T,MAX_N, NFB
  File "/home/disk1/zxl/anaconda3/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/disk1/zxl/anaconda3/lib/python3.9/site-packages/torch/nn/modules/linear.py", line 103, in forward
    return F.linear(input, self.weight, self.bias)
RuntimeError: mat1 and mat2 shapes cannot be multiplied (52x12800 and 26400x1024)

You may need to add codes for stage1 to this part by copying from base_volleyball. It should work. If you are training with resnet-18, you also need to change the out_size in the script to align it with the actual output size from resnet-18.

嗯嗯，好的，感谢您的回复，我这就去试试

zengxunli commented 2 years ago

您好，我完成了以上的代码修改，resnet18作为backbone的CAD一阶段训练最佳结果：93.02%，但是第二阶段训练过拟合严重，训练精度在15epoch左右基本达到了100%，而测试最佳：89.41%。这是怎么回事呢，超参数我只因为显存不够而减小了batch_size。顺便要说的是模型在VD上一、二阶段的训练结果是和论文指标一致的，并且同样减小了batch_size。期待您的回复

JacobYuan7 commented 1 year ago

您好，我完成了以上的代码修改，resnet18作为backbone的CAD一阶段训练最佳结果：93.02%，但是第二阶段训练过拟合严重，训练精度在15epoch左右基本达到了100%，而测试最佳：89.41%。这是怎么回事呢，超参数我只因为显存不够而减小了batch_size。顺便要说的是模型在VD上一、二阶段的训练结果是和论文指标一致的，并且同样减小了batch_size。期待您的回复

CAD is a dataset that easily overfits and encounters performance fluctuation because of the small dataset size. Two-stage pre-training makes this situation even worse. Usually, you need to use early stopping to achieve high performance. The performance in the 2nd stage should be better than the 1st stage.