Error while loading "Selective (CSL) TResNet-L" model

[enesmsahin]

Runtime Error occurs while loading state_dict for provided TResNet-L model. I think provided pretrained model and TResnetL class differ. Selective (CSL) - TResNet-M works without any problems.

Console Output

Traceback (most recent call last): File "infer.py", line 104, in main() File "infer.py", line 70, in main model.load_state_dict(state['model'], strict=True) File "/home/user/anaconda3/envs/partial_labeling_csl/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1482, in load_state_dict raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format( RuntimeError: Error(s) in loading state_dict for TResNet: Missing key(s) in state_dict: "body.layer1.3.conv1.0.weight", "body.layer1.3.conv1.1.weight", "body.layer1.3.conv1.1.bias", "body.layer1.3.conv1.1.running_mean", "body.layer1.3.conv1.1.running_var", "body.layer1.3.conv2.0.weight", "body.layer1.3.conv2.1.weight", "body.layer1.3.conv2.1.bias", "body.layer1.3.conv2.1.running_mean", "body.layer1.3.conv2.1.running_var", "body.layer1.3.se.fc1.weight", "body.layer1.3.se.fc1.bias", "body.layer1.3.se.fc2.weight", "body.layer1.3.se.fc2.bias", "body.layer2.0.conv1.0.0.weight", "body.layer2.0.conv1.0.1.weight", "body.layer2.0.conv1.0.1.bias", "body.layer2.0.conv1.0.1.running_mean", "body.layer2.0.conv1.0.1.running_var", "body.layer2.0.conv2.0.weight", "body.layer2.0.conv2.1.weight", "body.layer2.0.conv2.1.bias", "body.layer2.0.conv2.1.running_mean", "body.layer2.0.conv2.1.running_var", "body.layer2.4.conv1.0.weight", "body.layer2.4.conv1.1.weight", "body.layer2.4.conv1.1.bias", "body.layer2.4.conv1.1.running_mean", "body.layer2.4.conv1.1.running_var", "body.layer2.4.conv2.0.weight", "body.layer2.4.conv2.1.weight", "body.layer2.4.conv2.1.bias", "body.layer2.4.conv2.1.running_mean", "body.layer2.4.conv2.1.running_var", "body.layer2.4.se.fc1.weight", "body.layer2.4.se.fc1.bias", "body.layer2.4.se.fc2.weight", "body.layer2.4.se.fc2.bias". Unexpected key(s) in state_dict: "body.layer1.0.conv3.0.weight", "body.layer1.0.conv3.1.weight", "body.layer1.0.conv3.1.bias", "body.layer1.0.conv3.1.running_mean", "body.layer1.0.conv3.1.running_var", "body.layer1.0.conv3.1.num_batches_tracked", "body.layer1.0.downsample.0.0.weight", "body.layer1.0.downsample.0.1.weight", "body.layer1.0.downsample.0.1.bias", "body.layer1.0.downsample.0.1.running_mean", "body.layer1.0.downsample.0.1.running_var", "body.layer1.0.downsample.0.1.num_batches_tracked", "body.layer1.1.conv3.0.weight", "body.layer1.1.conv3.1.weight", "body.layer1.1.conv3.1.bias", "body.layer1.1.conv3.1.running_mean", "body.layer1.1.conv3.1.running_var", "body.layer1.1.conv3.1.num_batches_tracked", "body.layer1.2.conv3.0.weight", "body.layer1.2.conv3.1.weight", "body.layer1.2.conv3.1.bias", "body.layer1.2.conv3.1.running_mean", "body.layer1.2.conv3.1.running_var", "body.layer1.2.conv3.1.num_batches_tracked", "body.layer2.0.conv3.0.weight", "body.layer2.0.conv3.1.weight", "body.layer2.0.conv3.1.bias", "body.layer2.0.conv3.1.running_mean", "body.layer2.0.conv3.1.running_var", "body.layer2.0.conv3.1.num_batches_tracked", "body.layer2.0.conv1.0.weight", "body.layer2.0.conv1.1.weight", "body.layer2.0.conv1.1.bias", "body.layer2.0.conv1.1.running_mean", "body.layer2.0.conv1.1.running_var", "body.layer2.0.conv1.1.num_batches_tracked", "body.layer2.0.conv2.0.0.weight", "body.layer2.0.conv2.0.1.weight", "body.layer2.0.conv2.0.1.bias", "body.layer2.0.conv2.0.1.running_mean", "body.layer2.0.conv2.0.1.running_var", "body.layer2.0.conv2.0.1.num_batches_tracked", "body.layer2.1.conv3.0.weight", "body.layer2.1.conv3.1.weight", "body.layer2.1.conv3.1.bias", "body.layer2.1.conv3.1.running_mean", "body.layer2.1.conv3.1.running_var", "body.layer2.1.conv3.1.num_batches_tracked", "body.layer2.2.conv3.0.weight", "body.layer2.2.conv3.1.weight", "body.layer2.2.conv3.1.bias", "body.layer2.2.conv3.1.running_mean", "body.layer2.2.conv3.1.running_var", "body.layer2.2.conv3.1.num_batches_tracked", "body.layer2.3.conv3.0.weight", "body.layer2.3.conv3.1.weight", "body.layer2.3.conv3.1.bias", "body.layer2.3.conv3.1.running_mean", "body.layer2.3.conv3.1.running_var", "body.layer2.3.conv3.1.num_batches_tracked", "body.layer3.18.conv1.0.weight", "body.layer3.18.conv1.1.weight", "body.layer3.18.conv1.1.bias", "body.layer3.18.conv1.1.running_mean", "body.layer3.18.conv1.1.running_var", "body.layer3.18.conv1.1.num_batches_tracked", "body.layer3.18.conv2.0.weight", "body.layer3.18.conv2.1.weight", "body.layer3.18.conv2.1.bias", "body.layer3.18.conv2.1.running_mean", "body.layer3.18.conv2.1.running_var", "body.layer3.18.conv2.1.num_batches_tracked", "body.layer3.18.conv3.0.weight", "body.layer3.18.conv3.1.weight", "body.layer3.18.conv3.1.bias", "body.layer3.18.conv3.1.running_mean", "body.layer3.18.conv3.1.running_var", "body.layer3.18.conv3.1.num_batches_tracked", "body.layer3.18.se.fc1.weight", "body.layer3.18.se.fc1.bias", "body.layer3.18.se.fc2.weight", "body.layer3.18.se.fc2.bias", "body.layer3.19.conv1.0.weight", "body.layer3.19.conv1.1.weight", "body.layer3.19.conv1.1.bias", "body.layer3.19.conv1.1.running_mean", "body.layer3.19.conv1.1.running_var", "body.layer3.19.conv1.1.num_batches_tracked", "body.layer3.19.conv2.0.weight", "body.layer3.19.conv2.1.weight", "body.layer3.19.conv2.1.bias", "body.layer3.19.conv2.1.running_mean", "body.layer3.19.conv2.1.running_var", "body.layer3.19.conv2.1.num_batches_tracked", "body.layer3.19.conv3.0.weight", "body.layer3.19.conv3.1.weight", "body.layer3.19.conv3.1.bias", "body.layer3.19.conv3.1.running_mean", "body.layer3.19.conv3.1.running_var", "body.layer3.19.conv3.1.num_batches_tracked", "body.layer3.19.se.fc1.weight", "body.layer3.19.se.fc1.bias", "body.layer3.19.se.fc2.weight", "body.layer3.19.se.fc2.bias", "body.layer3.20.conv1.0.weight", "body.layer3.20.conv1.1.weight", "body.layer3.20.conv1.1.bias", "body.layer3.20.conv1.1.running_mean", "body.layer3.20.conv1.1.running_var", "body.layer3.20.conv1.1.num_batches_tracked", "body.layer3.20.conv2.0.weight", "body.layer3.20.conv2.1.weight", "body.layer3.20.conv2.1.bias", "body.layer3.20.conv2.1.running_mean", "body.layer3.20.conv2.1.running_var", "body.layer3.20.conv2.1.num_batches_tracked", "body.layer3.20.conv3.0.weight", "body.layer3.20.conv3.1.weight", "body.layer3.20.conv3.1.bias", "body.layer3.20.conv3.1.running_mean", "body.layer3.20.conv3.1.running_var", "body.layer3.20.conv3.1.num_batches_tracked", "body.layer3.20.se.fc1.weight", "body.layer3.20.se.fc1.bias", "body.layer3.20.se.fc2.weight", "body.layer3.20.se.fc2.bias", "body.layer3.21.conv1.0.weight", "body.layer3.21.conv1.1.weight", "body.layer3.21.conv1.1.bias", "body.layer3.21.conv1.1.running_mean", "body.layer3.21.conv1.1.running_var", "body.layer3.21.conv1.1.num_batches_tracked", "body.layer3.21.conv2.0.weight", "body.layer3.21.conv2.1.weight", "body.layer3.21.conv2.1.bias", "body.layer3.21.conv2.1.running_mean", "body.layer3.21.conv2.1.running_var", "body.layer3.21.conv2.1.num_batches_tracked", "body.layer3.21.conv3.0.weight", "body.layer3.21.conv3.1.weight", "body.layer3.21.conv3.1.bias", "body.layer3.21.conv3.1.running_mean", "body.layer3.21.conv3.1.running_var", "body.layer3.21.conv3.1.num_batches_tracked", "body.layer3.21.se.fc1.weight", "body.layer3.21.se.fc1.bias", "body.layer3.21.se.fc2.weight", "body.layer3.21.se.fc2.bias", "body.layer3.22.conv1.0.weight", "body.layer3.22.conv1.1.weight", "body.layer3.22.conv1.1.bias", "body.layer3.22.conv1.1.running_mean", "body.layer3.22.conv1.1.running_var", "body.layer3.22.conv1.1.num_batches_tracked", "body.layer3.22.conv2.0.weight", "body.layer3.22.conv2.1.weight", "body.layer3.22.conv2.1.bias", "body.layer3.22.conv2.1.running_mean", "body.layer3.22.conv2.1.running_var", "body.layer3.22.conv2.1.num_batches_tracked", "body.layer3.22.conv3.0.weight", "body.layer3.22.conv3.1.weight", "body.layer3.22.conv3.1.bias", "body.layer3.22.conv3.1.running_mean", "body.layer3.22.conv3.1.running_var", "body.layer3.22.conv3.1.num_batches_tracked", "body.layer3.22.se.fc1.weight", "body.layer3.22.se.fc1.bias", "body.layer3.22.se.fc2.weight", "body.layer3.22.se.fc2.bias". size mismatch for body.conv1.0.weight: copying a param with shape torch.Size([64, 48, 3, 3]) from checkpoint, the shape in current model is torch.Size([76, 48, 3, 3]). size mismatch for body.conv1.1.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([76]). size mismatch for body.conv1.1.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([76]). size mismatch for body.conv1.1.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([76]). size mismatch for body.conv1.1.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([76]). size mismatch for body.layer1.0.conv1.0.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([76, 76, 3, 3]). size mismatch for body.layer1.0.conv1.1.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([76]). size mismatch for body.layer1.0.conv1.1.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([76]). size mismatch for body.layer1.0.conv1.1.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([76]). size mismatch for body.layer1.0.conv1.1.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([76]). size mismatch for body.layer1.0.conv2.0.weight: copying a param with shape torch.Size([64, 64, 3, 3]) from checkpoint, the shape in current model is torch.Size([76, 76, 3, 3]). size mismatch for body.layer1.0.conv2.1.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([76]). size mismatch for body.layer1.0.conv2.1.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([76]). size mismatch for body.layer1.0.conv2.1.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([76]). size mismatch for body.layer1.0.conv2.1.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([76]). size mismatch for body.layer1.0.se.fc1.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([64, 76, 1, 1]). size mismatch for body.layer1.0.se.fc2.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([76, 64, 1, 1]). size mismatch for body.layer1.0.se.fc2.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([76]). size mismatch for body.layer1.1.conv1.0.weight: copying a param with shape torch.Size([64, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([76, 76, 3, 3]). size mismatch for body.layer1.1.conv1.1.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([76]). size mismatch for body.layer1.1.conv1.1.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([76]). size mismatch for body.layer1.1.conv1.1.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([76]). size mismatch for body.layer1.1.conv1.1.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([76]). size mismatch for body.layer1.1.conv2.0.weight: copying a param with shape torch.Size([64, 64, 3, 3]) from checkpoint, the shape in current model is torch.Size([76, 76, 3, 3]). size mismatch for body.layer1.1.conv2.1.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([76]). size mismatch for body.layer1.1.conv2.1.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([76]). size mismatch for body.layer1.1.conv2.1.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([76]). size mismatch for body.layer1.1.conv2.1.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([76]). size mismatch for body.layer1.1.se.fc1.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([64, 76, 1, 1]). size mismatch for body.layer1.1.se.fc2.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([76, 64, 1, 1]). size mismatch for body.layer1.1.se.fc2.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([76]). size mismatch for body.layer1.2.conv1.0.weight: copying a param with shape torch.Size([64, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([76, 76, 3, 3]). size mismatch for body.layer1.2.conv1.1.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([76]). size mismatch for body.layer1.2.conv1.1.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([76]). size mismatch for body.layer1.2.conv1.1.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([76]). size mismatch for body.layer1.2.conv1.1.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([76]). size mismatch for body.layer1.2.conv2.0.weight: copying a param with shape torch.Size([64, 64, 3, 3]) from checkpoint, the shape in current model is torch.Size([76, 76, 3, 3]). size mismatch for body.layer1.2.conv2.1.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([76]). size mismatch for body.layer1.2.conv2.1.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([76]). size mismatch for body.layer1.2.conv2.1.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([76]). size mismatch for body.layer1.2.conv2.1.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([76]). size mismatch for body.layer1.2.se.fc1.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([64, 76, 1, 1]). size mismatch for body.layer1.2.se.fc2.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([76, 64, 1, 1]). size mismatch for body.layer1.2.se.fc2.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([76]). size mismatch for body.layer2.0.downsample.1.0.weight: copying a param with shape torch.Size([512, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([152, 76, 1, 1]). size mismatch for body.layer2.0.downsample.1.1.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer2.0.downsample.1.1.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer2.0.downsample.1.1.running_mean: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer2.0.downsample.1.1.running_var: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer2.0.se.fc1.weight: copying a param with shape torch.Size([64, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([64, 152, 1, 1]). size mismatch for body.layer2.0.se.fc2.weight: copying a param with shape torch.Size([128, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([152, 64, 1, 1]). size mismatch for body.layer2.0.se.fc2.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer2.1.conv1.0.weight: copying a param with shape torch.Size([128, 512, 1, 1]) from checkpoint, the shape in current model is torch.Size([152, 152, 3, 3]). size mismatch for body.layer2.1.conv1.1.weight: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer2.1.conv1.1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer2.1.conv1.1.running_mean: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer2.1.conv1.1.running_var: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer2.1.conv2.0.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([152, 152, 3, 3]). size mismatch for body.layer2.1.conv2.1.weight: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer2.1.conv2.1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer2.1.conv2.1.running_mean: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer2.1.conv2.1.running_var: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer2.1.se.fc1.weight: copying a param with shape torch.Size([64, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([64, 152, 1, 1]). size mismatch for body.layer2.1.se.fc2.weight: copying a param with shape torch.Size([128, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([152, 64, 1, 1]). size mismatch for body.layer2.1.se.fc2.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer2.2.conv1.0.weight: copying a param with shape torch.Size([128, 512, 1, 1]) from checkpoint, the shape in current model is torch.Size([152, 152, 3, 3]). size mismatch for body.layer2.2.conv1.1.weight: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer2.2.conv1.1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer2.2.conv1.1.running_mean: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer2.2.conv1.1.running_var: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer2.2.conv2.0.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([152, 152, 3, 3]). size mismatch for body.layer2.2.conv2.1.weight: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer2.2.conv2.1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer2.2.conv2.1.running_mean: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer2.2.conv2.1.running_var: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer2.2.se.fc1.weight: copying a param with shape torch.Size([64, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([64, 152, 1, 1]). size mismatch for body.layer2.2.se.fc2.weight: copying a param with shape torch.Size([128, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([152, 64, 1, 1]). size mismatch for body.layer2.2.se.fc2.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer2.3.conv1.0.weight: copying a param with shape torch.Size([128, 512, 1, 1]) from checkpoint, the shape in current model is torch.Size([152, 152, 3, 3]). size mismatch for body.layer2.3.conv1.1.weight: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer2.3.conv1.1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer2.3.conv1.1.running_mean: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer2.3.conv1.1.running_var: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer2.3.conv2.0.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([152, 152, 3, 3]). size mismatch for body.layer2.3.conv2.1.weight: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer2.3.conv2.1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer2.3.conv2.1.running_mean: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer2.3.conv2.1.running_var: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer2.3.se.fc1.weight: copying a param with shape torch.Size([64, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([64, 152, 1, 1]). size mismatch for body.layer2.3.se.fc2.weight: copying a param with shape torch.Size([128, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([152, 64, 1, 1]). size mismatch for body.layer2.3.se.fc2.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer3.0.conv1.0.weight: copying a param with shape torch.Size([256, 512, 1, 1]) from checkpoint, the shape in current model is torch.Size([304, 152, 1, 1]). size mismatch for body.layer3.0.conv1.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.0.conv1.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.0.conv1.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.0.conv1.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.0.conv2.0.0.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([304, 304, 3, 3]). size mismatch for body.layer3.0.conv2.0.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.0.conv2.0.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.0.conv2.0.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.0.conv2.0.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.0.conv3.0.weight: copying a param with shape torch.Size([1024, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([1216, 304, 1, 1]). size mismatch for body.layer3.0.conv3.1.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.0.conv3.1.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.0.conv3.1.running_mean: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.0.conv3.1.running_var: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.0.downsample.1.0.weight: copying a param with shape torch.Size([1024, 512, 1, 1]) from checkpoint, the shape in current model is torch.Size([1216, 152, 1, 1]). size mismatch for body.layer3.0.downsample.1.1.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.0.downsample.1.1.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.0.downsample.1.1.running_mean: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.0.downsample.1.1.running_var: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.0.se.fc1.weight: copying a param with shape torch.Size([128, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([152, 304, 1, 1]). size mismatch for body.layer3.0.se.fc1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer3.0.se.fc2.weight: copying a param with shape torch.Size([256, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([304, 152, 1, 1]). size mismatch for body.layer3.0.se.fc2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.1.conv1.0.weight: copying a param with shape torch.Size([256, 1024, 1, 1]) from checkpoint, the shape in current model is torch.Size([304, 1216, 1, 1]). size mismatch for body.layer3.1.conv1.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.1.conv1.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.1.conv1.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.1.conv1.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.1.conv2.0.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([304, 304, 3, 3]). size mismatch for body.layer3.1.conv2.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.1.conv2.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.1.conv2.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.1.conv2.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.1.conv3.0.weight: copying a param with shape torch.Size([1024, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([1216, 304, 1, 1]). size mismatch for body.layer3.1.conv3.1.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.1.conv3.1.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.1.conv3.1.running_mean: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.1.conv3.1.running_var: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.1.se.fc1.weight: copying a param with shape torch.Size([128, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([152, 304, 1, 1]). size mismatch for body.layer3.1.se.fc1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer3.1.se.fc2.weight: copying a param with shape torch.Size([256, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([304, 152, 1, 1]). size mismatch for body.layer3.1.se.fc2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.2.conv1.0.weight: copying a param with shape torch.Size([256, 1024, 1, 1]) from checkpoint, the shape in current model is torch.Size([304, 1216, 1, 1]). size mismatch for body.layer3.2.conv1.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.2.conv1.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.2.conv1.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.2.conv1.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.2.conv2.0.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([304, 304, 3, 3]). size mismatch for body.layer3.2.conv2.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.2.conv2.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.2.conv2.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.2.conv2.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.2.conv3.0.weight: copying a param with shape torch.Size([1024, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([1216, 304, 1, 1]). size mismatch for body.layer3.2.conv3.1.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.2.conv3.1.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.2.conv3.1.running_mean: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.2.conv3.1.running_var: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.2.se.fc1.weight: copying a param with shape torch.Size([128, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([152, 304, 1, 1]). size mismatch for body.layer3.2.se.fc1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer3.2.se.fc2.weight: copying a param with shape torch.Size([256, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([304, 152, 1, 1]). size mismatch for body.layer3.2.se.fc2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.3.conv1.0.weight: copying a param with shape torch.Size([256, 1024, 1, 1]) from checkpoint, the shape in current model is torch.Size([304, 1216, 1, 1]). size mismatch for body.layer3.3.conv1.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.3.conv1.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.3.conv1.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.3.conv1.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.3.conv2.0.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([304, 304, 3, 3]). size mismatch for body.layer3.3.conv2.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.3.conv2.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.3.conv2.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.3.conv2.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.3.conv3.0.weight: copying a param with shape torch.Size([1024, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([1216, 304, 1, 1]). size mismatch for body.layer3.3.conv3.1.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.3.conv3.1.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.3.conv3.1.running_mean: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.3.conv3.1.running_var: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.3.se.fc1.weight: copying a param with shape torch.Size([128, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([152, 304, 1, 1]). size mismatch for body.layer3.3.se.fc1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer3.3.se.fc2.weight: copying a param with shape torch.Size([256, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([304, 152, 1, 1]). size mismatch for body.layer3.3.se.fc2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.4.conv1.0.weight: copying a param with shape torch.Size([256, 1024, 1, 1]) from checkpoint, the shape in current model is torch.Size([304, 1216, 1, 1]). size mismatch for body.layer3.4.conv1.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.4.conv1.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.4.conv1.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.4.conv1.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.4.conv2.0.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([304, 304, 3, 3]). size mismatch for body.layer3.4.conv2.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.4.conv2.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.4.conv2.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.4.conv2.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.4.conv3.0.weight: copying a param with shape torch.Size([1024, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([1216, 304, 1, 1]). size mismatch for body.layer3.4.conv3.1.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.4.conv3.1.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.4.conv3.1.running_mean: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.4.conv3.1.running_var: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.4.se.fc1.weight: copying a param with shape torch.Size([128, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([152, 304, 1, 1]). size mismatch for body.layer3.4.se.fc1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer3.4.se.fc2.weight: copying a param with shape torch.Size([256, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([304, 152, 1, 1]). size mismatch for body.layer3.4.se.fc2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.5.conv1.0.weight: copying a param with shape torch.Size([256, 1024, 1, 1]) from checkpoint, the shape in current model is torch.Size([304, 1216, 1, 1]). size mismatch for body.layer3.5.conv1.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.5.conv1.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.5.conv1.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.5.conv1.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.5.conv2.0.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([304, 304, 3, 3]). size mismatch for body.layer3.5.conv2.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.5.conv2.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.5.conv2.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.5.conv2.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.5.conv3.0.weight: copying a param with shape torch.Size([1024, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([1216, 304, 1, 1]). size mismatch for body.layer3.5.conv3.1.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.5.conv3.1.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.5.conv3.1.running_mean: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.5.conv3.1.running_var: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.5.se.fc1.weight: copying a param with shape torch.Size([128, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([152, 304, 1, 1]). size mismatch for body.layer3.5.se.fc1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer3.5.se.fc2.weight: copying a param with shape torch.Size([256, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([304, 152, 1, 1]). size mismatch for body.layer3.5.se.fc2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.6.conv1.0.weight: copying a param with shape torch.Size([256, 1024, 1, 1]) from checkpoint, the shape in current model is torch.Size([304, 1216, 1, 1]). size mismatch for body.layer3.6.conv1.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.6.conv1.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.6.conv1.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.6.conv1.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.6.conv2.0.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([304, 304, 3, 3]). size mismatch for body.layer3.6.conv2.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.6.conv2.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.6.conv2.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.6.conv2.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.6.conv3.0.weight: copying a param with shape torch.Size([1024, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([1216, 304, 1, 1]). size mismatch for body.layer3.6.conv3.1.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.6.conv3.1.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.6.conv3.1.running_mean: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.6.conv3.1.running_var: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.6.se.fc1.weight: copying a param with shape torch.Size([128, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([152, 304, 1, 1]). size mismatch for body.layer3.6.se.fc1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer3.6.se.fc2.weight: copying a param with shape torch.Size([256, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([304, 152, 1, 1]). size mismatch for body.layer3.6.se.fc2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.7.conv1.0.weight: copying a param with shape torch.Size([256, 1024, 1, 1]) from checkpoint, the shape in current model is torch.Size([304, 1216, 1, 1]). size mismatch for body.layer3.7.conv1.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.7.conv1.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.7.conv1.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.7.conv1.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.7.conv2.0.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([304, 304, 3, 3]). size mismatch for body.layer3.7.conv2.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.7.conv2.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.7.conv2.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.7.conv2.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.7.conv3.0.weight: copying a param with shape torch.Size([1024, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([1216, 304, 1, 1]). size mismatch for body.layer3.7.conv3.1.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.7.conv3.1.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.7.conv3.1.running_mean: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.7.conv3.1.running_var: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.7.se.fc1.weight: copying a param with shape torch.Size([128, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([152, 304, 1, 1]). size mismatch for body.layer3.7.se.fc1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer3.7.se.fc2.weight: copying a param with shape torch.Size([256, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([304, 152, 1, 1]). size mismatch for body.layer3.7.se.fc2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.8.conv1.0.weight: copying a param with shape torch.Size([256, 1024, 1, 1]) from checkpoint, the shape in current model is torch.Size([304, 1216, 1, 1]). size mismatch for body.layer3.8.conv1.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.8.conv1.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.8.conv1.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.8.conv1.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.8.conv2.0.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([304, 304, 3, 3]). size mismatch for body.layer3.8.conv2.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.8.conv2.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.8.conv2.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.8.conv2.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.8.conv3.0.weight: copying a param with shape torch.Size([1024, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([1216, 304, 1, 1]). size mismatch for body.layer3.8.conv3.1.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.8.conv3.1.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.8.conv3.1.running_mean: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.8.conv3.1.running_var: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.8.se.fc1.weight: copying a param with shape torch.Size([128, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([152, 304, 1, 1]). size mismatch for body.layer3.8.se.fc1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer3.8.se.fc2.weight: copying a param with shape torch.Size([256, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([304, 152, 1, 1]). size mismatch for body.layer3.8.se.fc2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.9.conv1.0.weight: copying a param with shape torch.Size([256, 1024, 1, 1]) from checkpoint, the shape in current model is torch.Size([304, 1216, 1, 1]). size mismatch for body.layer3.9.conv1.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.9.conv1.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.9.conv1.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.9.conv1.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.9.conv2.0.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([304, 304, 3, 3]). size mismatch for body.layer3.9.conv2.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.9.conv2.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.9.conv2.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.9.conv2.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.9.conv3.0.weight: copying a param with shape torch.Size([1024, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([1216, 304, 1, 1]). size mismatch for body.layer3.9.conv3.1.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.9.conv3.1.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.9.conv3.1.running_mean: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.9.conv3.1.running_var: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.9.se.fc1.weight: copying a param with shape torch.Size([128, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([152, 304, 1, 1]). size mismatch for body.layer3.9.se.fc1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer3.9.se.fc2.weight: copying a param with shape torch.Size([256, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([304, 152, 1, 1]). size mismatch for body.layer3.9.se.fc2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.10.conv1.0.weight: copying a param with shape torch.Size([256, 1024, 1, 1]) from checkpoint, the shape in current model is torch.Size([304, 1216, 1, 1]). size mismatch for body.layer3.10.conv1.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.10.conv1.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.10.conv1.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.10.conv1.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.10.conv2.0.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([304, 304, 3, 3]). size mismatch for body.layer3.10.conv2.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.10.conv2.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.10.conv2.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.10.conv2.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.10.conv3.0.weight: copying a param with shape torch.Size([1024, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([1216, 304, 1, 1]). size mismatch for body.layer3.10.conv3.1.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.10.conv3.1.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.10.conv3.1.running_mean: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.10.conv3.1.running_var: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.10.se.fc1.weight: copying a param with shape torch.Size([128, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([152, 304, 1, 1]). size mismatch for body.layer3.10.se.fc1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer3.10.se.fc2.weight: copying a param with shape torch.Size([256, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([304, 152, 1, 1]). size mismatch for body.layer3.10.se.fc2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.11.conv1.0.weight: copying a param with shape torch.Size([256, 1024, 1, 1]) from checkpoint, the shape in current model is torch.Size([304, 1216, 1, 1]). size mismatch for body.layer3.11.conv1.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.11.conv1.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.11.conv1.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.11.conv1.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.11.conv2.0.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([304, 304, 3, 3]). size mismatch for body.layer3.11.conv2.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.11.conv2.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.11.conv2.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.11.conv2.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.11.conv3.0.weight: copying a param with shape torch.Size([1024, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([1216, 304, 1, 1]). size mismatch for body.layer3.11.conv3.1.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.11.conv3.1.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.11.conv3.1.running_mean: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.11.conv3.1.running_var: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.11.se.fc1.weight: copying a param with shape torch.Size([128, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([152, 304, 1, 1]). size mismatch for body.layer3.11.se.fc1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer3.11.se.fc2.weight: copying a param with shape torch.Size([256, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([304, 152, 1, 1]). size mismatch for body.layer3.11.se.fc2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.12.conv1.0.weight: copying a param with shape torch.Size([256, 1024, 1, 1]) from checkpoint, the shape in current model is torch.Size([304, 1216, 1, 1]). size mismatch for body.layer3.12.conv1.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.12.conv1.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.12.conv1.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.12.conv1.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.12.conv2.0.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([304, 304, 3, 3]). size mismatch for body.layer3.12.conv2.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.12.conv2.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.12.conv2.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.12.conv2.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.12.conv3.0.weight: copying a param with shape torch.Size([1024, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([1216, 304, 1, 1]). size mismatch for body.layer3.12.conv3.1.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.12.conv3.1.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.12.conv3.1.running_mean: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.12.conv3.1.running_var: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.12.se.fc1.weight: copying a param with shape torch.Size([128, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([152, 304, 1, 1]). size mismatch for body.layer3.12.se.fc1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer3.12.se.fc2.weight: copying a param with shape torch.Size([256, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([304, 152, 1, 1]). size mismatch for body.layer3.12.se.fc2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.13.conv1.0.weight: copying a param with shape torch.Size([256, 1024, 1, 1]) from checkpoint, the shape in current model is torch.Size([304, 1216, 1, 1]). size mismatch for body.layer3.13.conv1.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.13.conv1.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.13.conv1.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.13.conv1.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.13.conv2.0.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([304, 304, 3, 3]). size mismatch for body.layer3.13.conv2.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.13.conv2.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.13.conv2.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.13.conv2.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.13.conv3.0.weight: copying a param with shape torch.Size([1024, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([1216, 304, 1, 1]). size mismatch for body.layer3.13.conv3.1.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.13.conv3.1.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.13.conv3.1.running_mean: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.13.conv3.1.running_var: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.13.se.fc1.weight: copying a param with shape torch.Size([128, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([152, 304, 1, 1]). size mismatch for body.layer3.13.se.fc1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer3.13.se.fc2.weight: copying a param with shape torch.Size([256, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([304, 152, 1, 1]). size mismatch for body.layer3.13.se.fc2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.14.conv1.0.weight: copying a param with shape torch.Size([256, 1024, 1, 1]) from checkpoint, the shape in current model is torch.Size([304, 1216, 1, 1]). size mismatch for body.layer3.14.conv1.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.14.conv1.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.14.conv1.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.14.conv1.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.14.conv2.0.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([304, 304, 3, 3]). size mismatch for body.layer3.14.conv2.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.14.conv2.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.14.conv2.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.14.conv2.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.14.conv3.0.weight: copying a param with shape torch.Size([1024, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([1216, 304, 1, 1]). size mismatch for body.layer3.14.conv3.1.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.14.conv3.1.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.14.conv3.1.running_mean: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.14.conv3.1.running_var: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.14.se.fc1.weight: copying a param with shape torch.Size([128, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([152, 304, 1, 1]). size mismatch for body.layer3.14.se.fc1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer3.14.se.fc2.weight: copying a param with shape torch.Size([256, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([304, 152, 1, 1]). size mismatch for body.layer3.14.se.fc2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.15.conv1.0.weight: copying a param with shape torch.Size([256, 1024, 1, 1]) from checkpoint, the shape in current model is torch.Size([304, 1216, 1, 1]). size mismatch for body.layer3.15.conv1.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.15.conv1.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.15.conv1.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.15.conv1.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.15.conv2.0.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([304, 304, 3, 3]). size mismatch for body.layer3.15.conv2.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.15.conv2.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.15.conv2.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.15.conv2.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.15.conv3.0.weight: copying a param with shape torch.Size([1024, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([1216, 304, 1, 1]). size mismatch for body.layer3.15.conv3.1.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.15.conv3.1.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.15.conv3.1.running_mean: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.15.conv3.1.running_var: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.15.se.fc1.weight: copying a param with shape torch.Size([128, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([152, 304, 1, 1]). size mismatch for body.layer3.15.se.fc1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer3.15.se.fc2.weight: copying a param with shape torch.Size([256, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([304, 152, 1, 1]). size mismatch for body.layer3.15.se.fc2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.16.conv1.0.weight: copying a param with shape torch.Size([256, 1024, 1, 1]) from checkpoint, the shape in current model is torch.Size([304, 1216, 1, 1]). size mismatch for body.layer3.16.conv1.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.16.conv1.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.16.conv1.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.16.conv1.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.16.conv2.0.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([304, 304, 3, 3]). size mismatch for body.layer3.16.conv2.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.16.conv2.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.16.conv2.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.16.conv2.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.16.conv3.0.weight: copying a param with shape torch.Size([1024, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([1216, 304, 1, 1]). size mismatch for body.layer3.16.conv3.1.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.16.conv3.1.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.16.conv3.1.running_mean: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.16.conv3.1.running_var: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.16.se.fc1.weight: copying a param with shape torch.Size([128, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([152, 304, 1, 1]). size mismatch for body.layer3.16.se.fc1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer3.16.se.fc2.weight: copying a param with shape torch.Size([256, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([304, 152, 1, 1]). size mismatch for body.layer3.16.se.fc2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.17.conv1.0.weight: copying a param with shape torch.Size([256, 1024, 1, 1]) from checkpoint, the shape in current model is torch.Size([304, 1216, 1, 1]). size mismatch for body.layer3.17.conv1.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.17.conv1.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.17.conv1.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.17.conv1.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.17.conv2.0.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([304, 304, 3, 3]). size mismatch for body.layer3.17.conv2.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.17.conv2.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.17.conv2.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.17.conv2.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer3.17.conv3.0.weight: copying a param with shape torch.Size([1024, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([1216, 304, 1, 1]). size mismatch for body.layer3.17.conv3.1.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.17.conv3.1.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.17.conv3.1.running_mean: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.17.conv3.1.running_var: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1216]). size mismatch for body.layer3.17.se.fc1.weight: copying a param with shape torch.Size([128, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([152, 304, 1, 1]). size mismatch for body.layer3.17.se.fc1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([152]). size mismatch for body.layer3.17.se.fc2.weight: copying a param with shape torch.Size([256, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([304, 152, 1, 1]). size mismatch for body.layer3.17.se.fc2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([304]). size mismatch for body.layer4.0.conv1.0.weight: copying a param with shape torch.Size([512, 1024, 1, 1]) from checkpoint, the shape in current model is torch.Size([608, 1216, 1, 1]). size mismatch for body.layer4.0.conv1.1.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([608]). size mismatch for body.layer4.0.conv1.1.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([608]). size mismatch for body.layer4.0.conv1.1.running_mean: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([608]). size mismatch for body.layer4.0.conv1.1.running_var: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([608]). size mismatch for body.layer4.0.conv2.0.0.weight: copying a param with shape torch.Size([512, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([608, 608, 3, 3]). size mismatch for body.layer4.0.conv2.0.1.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([608]). size mismatch for body.layer4.0.conv2.0.1.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([608]). size mismatch for body.layer4.0.conv2.0.1.running_mean: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([608]). size mismatch for body.layer4.0.conv2.0.1.running_var: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([608]). size mismatch for body.layer4.0.conv3.0.weight: copying a param with shape torch.Size([2048, 512, 1, 1]) from checkpoint, the shape in current model is torch.Size([2432, 608, 1, 1]). size mismatch for body.layer4.0.conv3.1.weight: copying a param with shape torch.Size([2048]) from checkpoint, the shape in current model is torch.Size([2432]). size mismatch for body.layer4.0.conv3.1.bias: copying a param with shape torch.Size([2048]) from checkpoint, the shape in current model is torch.Size([2432]). size mismatch for body.layer4.0.conv3.1.running_mean: copying a param with shape torch.Size([2048]) from checkpoint, the shape in current model is torch.Size([2432]). size mismatch for body.layer4.0.conv3.1.running_var: copying a param with shape torch.Size([2048]) from checkpoint, the shape in current model is torch.Size([2432]). size mismatch for body.layer4.0.downsample.1.0.weight: copying a param with shape torch.Size([2048, 1024, 1, 1]) from checkpoint, the shape in current model is torch.Size([2432, 1216, 1, 1]). size mismatch for body.layer4.0.downsample.1.1.weight: copying a param with shape torch.Size([2048]) from checkpoint, the shape in current model is torch.Size([2432]). size mismatch for body.layer4.0.downsample.1.1.bias: copying a param with shape torch.Size([2048]) from checkpoint, the shape in current model is torch.Size([2432]). size mismatch for body.layer4.0.downsample.1.1.running_mean: copying a param with shape torch.Size([2048]) from checkpoint, the shape in current model is torch.Size([2432]). size mismatch for body.layer4.0.downsample.1.1.running_var: copying a param with shape torch.Size([2048]) from checkpoint, the shape in current model is torch.Size([2432]). size mismatch for body.layer4.1.conv1.0.weight: copying a param with shape torch.Size([512, 2048, 1, 1]) from checkpoint, the shape in current model is torch.Size([608, 2432, 1, 1]). size mismatch for body.layer4.1.conv1.1.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([608]). size mismatch for body.layer4.1.conv1.1.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([608]). size mismatch for body.layer4.1.conv1.1.running_mean: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([608]). size mismatch for body.layer4.1.conv1.1.running_var: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([608]). size mismatch for body.layer4.1.conv2.0.weight: copying a param with shape torch.Size([512, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([608, 608, 3, 3]). size mismatch for body.layer4.1.conv2.1.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([608]). size mismatch for body.layer4.1.conv2.1.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([608]). size mismatch for body.layer4.1.conv2.1.running_mean: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([608]). size mismatch for body.layer4.1.conv2.1.running_var: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([608]). size mismatch for body.layer4.1.conv3.0.weight: copying a param with shape torch.Size([2048, 512, 1, 1]) from checkpoint, the shape in current model is torch.Size([2432, 608, 1, 1]). size mismatch for body.layer4.1.conv3.1.weight: copying a param with shape torch.Size([2048]) from checkpoint, the shape in current model is torch.Size([2432]). size mismatch for body.layer4.1.conv3.1.bias: copying a param with shape torch.Size([2048]) from checkpoint, the shape in current model is torch.Size([2432]). size mismatch for body.layer4.1.conv3.1.running_mean: copying a param with shape torch.Size([2048]) from checkpoint, the shape in current model is torch.Size([2432]). size mismatch for body.layer4.1.conv3.1.running_var: copying a param with shape torch.Size([2048]) from checkpoint, the shape in current model is torch.Size([2432]). size mismatch for body.layer4.2.conv1.0.weight: copying a param with shape torch.Size([512, 2048, 1, 1]) from checkpoint, the shape in current model is torch.Size([608, 2432, 1, 1]). size mismatch for body.layer4.2.conv1.1.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([608]). size mismatch for body.layer4.2.conv1.1.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([608]). size mismatch for body.layer4.2.conv1.1.running_mean: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([608]). size mismatch for body.layer4.2.conv1.1.running_var: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([608]). size mismatch for body.layer4.2.conv2.0.weight: copying a param with shape torch.Size([512, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([608, 608, 3, 3]). size mismatch for body.layer4.2.conv2.1.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([608]). size mismatch for body.layer4.2.conv2.1.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([608]). size mismatch for body.layer4.2.conv2.1.running_mean: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([608]). size mismatch for body.layer4.2.conv2.1.running_var: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([608]). size mismatch for body.layer4.2.conv3.0.weight: copying a param with shape torch.Size([2048, 512, 1, 1]) from checkpoint, the shape in current model is torch.Size([2432, 608, 1, 1]). size mismatch for body.layer4.2.conv3.1.weight: copying a param with shape torch.Size([2048]) from checkpoint, the shape in current model is torch.Size([2432]). size mismatch for body.layer4.2.conv3.1.bias: copying a param with shape torch.Size([2048]) from checkpoint, the shape in current model is torch.Size([2432]). size mismatch for body.layer4.2.conv3.1.running_mean: copying a param with shape torch.Size([2048]) from checkpoint, the shape in current model is torch.Size([2432]). size mismatch for body.layer4.2.conv3.1.running_var: copying a param with shape torch.Size([2048]) from checkpoint, the shape in current model is torch.Size([2432]). size mismatch for head.fc.embedding_generator.0.weight: copying a param with shape torch.Size([512, 2048]) from checkpoint, the shape in current model is torch.Size([512, 2432]).

Environment

OS: Ubuntu 18.04 PyTorch: 1.10.1 CUDA: 10.2

Command to Reproduce

python infer.py --dataset_type=OpenImages --model_name=tresnet_l --model_path=ltresnet_v2_opim_87.34.pth --pic_path=test_img.jpg

[ebenbaruch]

Hi, Thanks for noticing that. Indeed, there is a problem in loading the pre-trained model for the TResNet-L model. We will fix that soon. In the meantime, you can use TResNet-M.

[Leterax]

Any update on this? im still running into the same problem

[sohamjoshi017]

I am still getting an error while loading the TResNet-L model. Could you please give the updated checkpoint? @ebenbaruch @mrT23 Thank you!