zylo117
commented
3 years ago I think some of your annotations are missing category_id but most of them aren't. So when the program tried to get their category_id, it crashed.
Open valterfsj opened 3 years ago
zylo117
commented
3 years ago I think some of your annotations are missing category_id but most of them aren't. So when the program tried to get their category_id, it crashed.
valterfsj
commented
3 years ago Just found out that img 17 had no Category_ID.
Now I managed to run but still got tons of errors, as following:
(effdetpy) E:\PorosityDetection\Yet-Another-EfficientDet-Pytorch-master\Yet-Another-EfficientDet-Pytorch-master>python train.py -c 2 -p PorosityDetection --batch_size 8 --lr 1e-3 --num_epochs 10 --load_weights E:/PorosityDetection/Yet-Another-EfficientDet-Pytorch-master/Yet-Another-EfficientDet-Pytorch-master/weights/efficientdet-d0.pth --head_only True loading annotations into memory... Done (t=0.00s) creating index... index created! loading annotations into memory... Done (t=0.00s) creating index... index created! [Warning] Ignoring Error(s) in loading state_dict for EfficientDetBackbone: size mismatch for bifpn.0.conv6_up.depthwise_conv.conv.weight: copying a param with shape torch.Size([64, 1, 3, 3]) from checkpoint, the shape in current model is torch.Size([112, 1, 3, 3]). size mismatch for bifpn.0.conv6_up.pointwise_conv.conv.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([112, 112, 1, 1]). size mismatch for bifpn.0.conv6_up.pointwise_conv.conv.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv6_up.bn.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv6_up.bn.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv6_up.bn.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv6_up.bn.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv5_up.depthwise_conv.conv.weight: copying a param with shape torch.Size([64, 1, 3, 3]) from checkpoint, the shape in current model is torch.Size([112, 1, 3, 3]). size mismatch for bifpn.0.conv5_up.pointwise_conv.conv.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([112, 112, 1, 1]). size mismatch for bifpn.0.conv5_up.pointwise_conv.conv.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv5_up.bn.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv5_up.bn.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv5_up.bn.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv5_up.bn.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv4_up.depthwise_conv.conv.weight: copying a param with shape torch.Size([64, 1, 3, 3]) from checkpoint, the shape in current model is torch.Size([112, 1, 3, 3]). size mismatch for bifpn.0.conv4_up.pointwise_conv.conv.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([112, 112, 1, 1]). size mismatch for bifpn.0.conv4_up.pointwise_conv.conv.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv4_up.bn.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv4_up.bn.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv4_up.bn.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv4_up.bn.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv3_up.depthwise_conv.conv.weight: copying a param with shape torch.Size([64, 1, 3, 3]) from checkpoint, the shape in current model is torch.Size([112, 1, 3, 3]). size mismatch for bifpn.0.conv3_up.pointwise_conv.conv.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([112, 112, 1, 1]). size mismatch for bifpn.0.conv3_up.pointwise_conv.conv.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv3_up.bn.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv3_up.bn.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv3_up.bn.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv3_up.bn.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv4_down.depthwise_conv.conv.weight: copying a param with shape torch.Size([64, 1, 3, 3]) from checkpoint, the shape in current model is torch.Size([112, 1, 3, 3]). size mismatch for bifpn.0.conv4_down.pointwise_conv.conv.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([112, 112, 1, 1]). size mismatch for bifpn.0.conv4_down.pointwise_conv.conv.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv4_down.bn.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv4_down.bn.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv4_down.bn.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv4_down.bn.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv5_down.depthwise_conv.conv.weight: copying a param with shape torch.Size([64, 1, 3, 3]) from checkpoint, the shape in current model is torch.Size([112, 1, 3, 3]). size mismatch for bifpn.0.conv5_down.pointwise_conv.conv.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([112, 112, 1, 1]). size mismatch for bifpn.0.conv5_down.pointwise_conv.conv.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv5_down.bn.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv5_down.bn.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv5_down.bn.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv5_down.bn.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv6_down.depthwise_conv.conv.weight: copying a param with shape torch.Size([64, 1, 3, 3]) from checkpoint, the shape in current model is torch.Size([112, 1, 3, 3]). size mismatch for bifpn.0.conv6_down.pointwise_conv.conv.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([112, 112, 1, 1]). size mismatch for bifpn.0.conv6_down.pointwise_conv.conv.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv6_down.bn.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv6_down.bn.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv6_down.bn.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv6_down.bn.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv7_down.depthwise_conv.conv.weight: copying a param with shape torch.Size([64, 1, 3, 3]) from checkpoint, the shape in current model is torch.Size([112, 1, 3, 3]). size mismatch for bifpn.0.conv7_down.pointwise_conv.conv.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([112, 112, 1, 1]). size mismatch for bifpn.0.conv7_down.pointwise_conv.conv.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv7_down.bn.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv7_down.bn.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv7_down.bn.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.conv7_down.bn.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.p5_down_channel.0.conv.weight: copying a param with shape torch.Size([64, 320, 1, 1]) from checkpoint, the shape in current model is torch.Size([112, 352, 1, 1]). size mismatch for bifpn.0.p5_down_channel.0.conv.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.p5_down_channel.1.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.p5_down_channel.1.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.p5_down_channel.1.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.p5_down_channel.1.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.p4_down_channel.0.conv.weight: copying a param with shape torch.Size([64, 112, 1, 1]) from checkpoint, the shape in current model is torch.Size([112, 120, 1, 1]). size mismatch for bifpn.0.p4_down_channel.0.conv.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.p4_down_channel.1.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.p4_down_channel.1.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.p4_down_channel.1.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.p4_down_channel.1.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.p3_down_channel.0.conv.weight: copying a param with shape torch.Size([64, 40, 1, 1]) from checkpoint, the shape in current model is torch.Size([112, 48, 1, 1]). size mismatch for bifpn.0.p3_down_channel.0.conv.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.p3_down_channel.1.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.p3_down_channel.1.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.p3_down_channel.1.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.p3_down_channel.1.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.p5_to_p6.0.conv.weight: copying a param with shape torch.Size([64, 320, 1, 1]) from checkpoint, the shape in current model is torch.Size([112, 352, 1, 1]). size mismatch for bifpn.0.p5_to_p6.0.conv.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.p5_to_p6.1.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.p5_to_p6.1.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.p5_to_p6.1.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.p5_to_p6.1.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.p4_down_channel_2.0.conv.weight: copying a param with shape torch.Size([64, 112, 1, 1]) from checkpoint, the shape in current model is torch.Size([112, 120, 1, 1]). size mismatch for bifpn.0.p4_down_channel_2.0.conv.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.p4_down_channel_2.1.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.p4_down_channel_2.1.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.p4_down_channel_2.1.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.p4_down_channel_2.1.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.p5_down_channel_2.0.conv.weight: copying a param with shape torch.Size([64, 320, 1, 1]) from checkpoint, the shape in current model is torch.Size([112, 352, 1, 1]). size mismatch for bifpn.0.p5_down_channel_2.0.conv.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.p5_down_channel_2.1.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.p5_down_channel_2.1.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.p5_down_channel_2.1.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.0.p5_down_channel_2.1.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv6_up.depthwise_conv.conv.weight: copying a param with shape torch.Size([64, 1, 3, 3]) from checkpoint, the shape in current model is torch.Size([112, 1, 3, 3]). size mismatch for bifpn.1.conv6_up.pointwise_conv.conv.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([112, 112, 1, 1]). size mismatch for bifpn.1.conv6_up.pointwise_conv.conv.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv6_up.bn.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv6_up.bn.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv6_up.bn.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv6_up.bn.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv5_up.depthwise_conv.conv.weight: copying a param with shape torch.Size([64, 1, 3, 3]) from checkpoint, the shape in current model is torch.Size([112, 1, 3, 3]). size mismatch for bifpn.1.conv5_up.pointwise_conv.conv.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([112, 112, 1, 1]). size mismatch for bifpn.1.conv5_up.pointwise_conv.conv.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv5_up.bn.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv5_up.bn.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv5_up.bn.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv5_up.bn.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv4_up.depthwise_conv.conv.weight: copying a param with shape torch.Size([64, 1, 3, 3]) from checkpoint, the shape in current model is torch.Size([112, 1, 3, 3]). size mismatch for bifpn.1.conv4_up.pointwise_conv.conv.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([112, 112, 1, 1]). size mismatch for bifpn.1.conv4_up.pointwise_conv.conv.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv4_up.bn.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv4_up.bn.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv4_up.bn.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv4_up.bn.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv3_up.depthwise_conv.conv.weight: copying a param with shape torch.Size([64, 1, 3, 3]) from checkpoint, the shape in current model is torch.Size([112, 1, 3, 3]). size mismatch for bifpn.1.conv3_up.pointwise_conv.conv.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([112, 112, 1, 1]). size mismatch for bifpn.1.conv3_up.pointwise_conv.conv.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv3_up.bn.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv3_up.bn.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv3_up.bn.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv3_up.bn.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv4_down.depthwise_conv.conv.weight: copying a param with shape torch.Size([64, 1, 3, 3]) from checkpoint, the shape in current model is torch.Size([112, 1, 3, 3]). size mismatch for bifpn.1.conv4_down.pointwise_conv.conv.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([112, 112, 1, 1]). size mismatch for bifpn.1.conv4_down.pointwise_conv.conv.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv4_down.bn.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv4_down.bn.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv4_down.bn.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv4_down.bn.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv5_down.depthwise_conv.conv.weight: copying a param with shape torch.Size([64, 1, 3, 3]) from checkpoint, the shape in current model is torch.Size([112, 1, 3, 3]). size mismatch for bifpn.1.conv5_down.pointwise_conv.conv.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([112, 112, 1, 1]). size mismatch for bifpn.1.conv5_down.pointwise_conv.conv.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv5_down.bn.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv5_down.bn.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv5_down.bn.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv5_down.bn.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv6_down.depthwise_conv.conv.weight: copying a param with shape torch.Size([64, 1, 3, 3]) from checkpoint, the shape in current model is torch.Size([112, 1, 3, 3]). size mismatch for bifpn.1.conv6_down.pointwise_conv.conv.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([112, 112, 1, 1]). size mismatch for bifpn.1.conv6_down.pointwise_conv.conv.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv6_down.bn.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv6_down.bn.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv6_down.bn.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv6_down.bn.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv7_down.depthwise_conv.conv.weight: copying a param with shape torch.Size([64, 1, 3, 3]) from checkpoint, the shape in current model is torch.Size([112, 1, 3, 3]). size mismatch for bifpn.1.conv7_down.pointwise_conv.conv.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([112, 112, 1, 1]). size mismatch for bifpn.1.conv7_down.pointwise_conv.conv.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv7_down.bn.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv7_down.bn.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv7_down.bn.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.1.conv7_down.bn.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv6_up.depthwise_conv.conv.weight: copying a param with shape torch.Size([64, 1, 3, 3]) from checkpoint, the shape in current model is torch.Size([112, 1, 3, 3]). size mismatch for bifpn.2.conv6_up.pointwise_conv.conv.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([112, 112, 1, 1]). size mismatch for bifpn.2.conv6_up.pointwise_conv.conv.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv6_up.bn.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv6_up.bn.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv6_up.bn.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv6_up.bn.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv5_up.depthwise_conv.conv.weight: copying a param with shape torch.Size([64, 1, 3, 3]) from checkpoint, the shape in current model is torch.Size([112, 1, 3, 3]). size mismatch for bifpn.2.conv5_up.pointwise_conv.conv.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([112, 112, 1, 1]). size mismatch for bifpn.2.conv5_up.pointwise_conv.conv.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv5_up.bn.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv5_up.bn.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv5_up.bn.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv5_up.bn.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv4_up.depthwise_conv.conv.weight: copying a param with shape torch.Size([64, 1, 3, 3]) from checkpoint, the shape in current model is torch.Size([112, 1, 3, 3]). size mismatch for bifpn.2.conv4_up.pointwise_conv.conv.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([112, 112, 1, 1]). size mismatch for bifpn.2.conv4_up.pointwise_conv.conv.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv4_up.bn.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv4_up.bn.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv4_up.bn.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv4_up.bn.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv3_up.depthwise_conv.conv.weight: copying a param with shape torch.Size([64, 1, 3, 3]) from checkpoint, the shape in current model is torch.Size([112, 1, 3, 3]). size mismatch for bifpn.2.conv3_up.pointwise_conv.conv.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([112, 112, 1, 1]). size mismatch for bifpn.2.conv3_up.pointwise_conv.conv.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv3_up.bn.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv3_up.bn.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv3_up.bn.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv3_up.bn.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv4_down.depthwise_conv.conv.weight: copying a param with shape torch.Size([64, 1, 3, 3]) from checkpoint, the shape in current model is torch.Size([112, 1, 3, 3]). size mismatch for bifpn.2.conv4_down.pointwise_conv.conv.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([112, 112, 1, 1]). size mismatch for bifpn.2.conv4_down.pointwise_conv.conv.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv4_down.bn.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv4_down.bn.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv4_down.bn.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv4_down.bn.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv5_down.depthwise_conv.conv.weight: copying a param with shape torch.Size([64, 1, 3, 3]) from checkpoint, the shape in current model is torch.Size([112, 1, 3, 3]). size mismatch for bifpn.2.conv5_down.pointwise_conv.conv.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([112, 112, 1, 1]). size mismatch for bifpn.2.conv5_down.pointwise_conv.conv.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv5_down.bn.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv5_down.bn.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv5_down.bn.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv5_down.bn.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv6_down.depthwise_conv.conv.weight: copying a param with shape torch.Size([64, 1, 3, 3]) from checkpoint, the shape in current model is torch.Size([112, 1, 3, 3]). size mismatch for bifpn.2.conv6_down.pointwise_conv.conv.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([112, 112, 1, 1]). size mismatch for bifpn.2.conv6_down.pointwise_conv.conv.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv6_down.bn.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv6_down.bn.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv6_down.bn.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv6_down.bn.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv7_down.depthwise_conv.conv.weight: copying a param with shape torch.Size([64, 1, 3, 3]) from checkpoint, the shape in current model is torch.Size([112, 1, 3, 3]). size mismatch for bifpn.2.conv7_down.pointwise_conv.conv.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([112, 112, 1, 1]). size mismatch for bifpn.2.conv7_down.pointwise_conv.conv.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv7_down.bn.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv7_down.bn.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv7_down.bn.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for bifpn.2.conv7_down.bn.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.conv_list.0.depthwise_conv.conv.weight: copying a param with shape torch.Size([64, 1, 3, 3]) from checkpoint, the shape in current model is torch.Size([112, 1, 3, 3]). size mismatch for regressor.conv_list.0.pointwise_conv.conv.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([112, 112, 1, 1]). size mismatch for regressor.conv_list.0.pointwise_conv.conv.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.conv_list.1.depthwise_conv.conv.weight: copying a param with shape torch.Size([64, 1, 3, 3]) from checkpoint, the shape in current model is torch.Size([112, 1, 3, 3]). size mismatch for regressor.conv_list.1.pointwise_conv.conv.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([112, 112, 1, 1]). size mismatch for regressor.conv_list.1.pointwise_conv.conv.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.conv_list.2.depthwise_conv.conv.weight: copying a param with shape torch.Size([64, 1, 3, 3]) from checkpoint, the shape in current model is torch.Size([112, 1, 3, 3]). size mismatch for regressor.conv_list.2.pointwise_conv.conv.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([112, 112, 1, 1]). size mismatch for regressor.conv_list.2.pointwise_conv.conv.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.0.0.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.0.0.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.0.0.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.0.0.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.0.1.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.0.1.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.0.1.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.0.1.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.0.2.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.0.2.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.0.2.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.0.2.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.1.0.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.1.0.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.1.0.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.1.0.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.1.1.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.1.1.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.1.1.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.1.1.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.1.2.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.1.2.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.1.2.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.1.2.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.2.0.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.2.0.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.2.0.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.2.0.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.2.1.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.2.1.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.2.1.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.2.1.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.2.2.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.2.2.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.2.2.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.2.2.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.3.0.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.3.0.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.3.0.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.3.0.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.3.1.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.3.1.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.3.1.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.3.1.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.3.2.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.3.2.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.3.2.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.3.2.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.4.0.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.4.0.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.4.0.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.4.0.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.4.1.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.4.1.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.4.1.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.4.1.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.4.2.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.4.2.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.4.2.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.bn_list.4.2.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for regressor.header.depthwise_conv.conv.weight: copying a param with shape torch.Size([64, 1, 3, 3]) from checkpoint, the shape in current model is torch.Size([112, 1, 3, 3]). size mismatch for regressor.header.pointwise_conv.conv.weight: copying a param with shape torch.Size([36, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([36, 112, 1, 1]). size mismatch for classifier.conv_list.0.depthwise_conv.conv.weight: copying a param with shape torch.Size([64, 1, 3, 3]) from checkpoint, the shape in current model is torch.Size([112, 1, 3, 3]). size mismatch for classifier.conv_list.0.pointwise_conv.conv.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([112, 112, 1, 1]). size mismatch for classifier.conv_list.0.pointwise_conv.conv.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.conv_list.1.depthwise_conv.conv.weight: copying a param with shape torch.Size([64, 1, 3, 3]) from checkpoint, the shape in current model is torch.Size([112, 1, 3, 3]). size mismatch for classifier.conv_list.1.pointwise_conv.conv.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([112, 112, 1, 1]). size mismatch for classifier.conv_list.1.pointwise_conv.conv.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.conv_list.2.depthwise_conv.conv.weight: copying a param with shape torch.Size([64, 1, 3, 3]) from checkpoint, the shape in current model is torch.Size([112, 1, 3, 3]). size mismatch for classifier.conv_list.2.pointwise_conv.conv.weight: copying a param with shape torch.Size([64, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([112, 112, 1, 1]). size mismatch for classifier.conv_list.2.pointwise_conv.conv.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.0.0.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.0.0.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.0.0.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.0.0.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.0.1.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.0.1.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.0.1.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.0.1.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.0.2.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.0.2.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.0.2.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.0.2.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.1.0.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.1.0.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.1.0.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.1.0.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.1.1.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.1.1.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.1.1.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.1.1.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.1.2.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.1.2.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.1.2.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.1.2.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.2.0.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.2.0.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.2.0.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.2.0.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.2.1.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.2.1.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.2.1.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.2.1.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.2.2.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.2.2.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.2.2.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.2.2.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.3.0.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.3.0.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.3.0.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.3.0.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.3.1.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.3.1.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.3.1.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.3.1.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.3.2.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.3.2.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.3.2.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.3.2.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.4.0.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.4.0.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.4.0.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.4.0.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.4.1.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.4.1.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.4.1.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.4.1.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.4.2.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.4.2.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.4.2.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.bn_list.4.2.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([112]). size mismatch for classifier.header.depthwise_conv.conv.weight: copying a param with shape torch.Size([64, 1, 3, 3]) from checkpoint, the shape in current model is torch.Size([112, 1, 3, 3]). size mismatch for classifier.header.pointwise_conv.conv.weight: copying a param with shape torch.Size([810, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([9, 112, 1, 1]). size mismatch for classifier.header.pointwise_conv.conv.bias: copying a param with shape torch.Size([810]) from checkpoint, the shape in current model is torch.Size([9]). size mismatch for backbone_net.model._blocks.1._depthwise_conv.conv.weight: copying a param with shape torch.Size([96, 1, 3, 3]) from checkpoint, the shape in current model is torch.Size([16, 1, 3, 3]). size mismatch for backbone_net.model._blocks.1._bn1.weight: copying a param with shape torch.Size([96]) from checkpoint, the shape in current model is torch.Size([16]). size mismatch for backbone_net.model._blocks.1._bn1.bias: copying a param with shape torch.Size([96]) from checkpoint, the shape in current model is torch.Size([16]). size mismatch for backbone_net.model._blocks.1._bn1.running_mean: copying a param with shape torch.Size([96]) from checkpoint, the shape in current model is torch.Size([16]). size mismatch for backbone_net.model._blocks.1._bn1.running_var: copying a param with shape torch.Size([96]) from checkpoint, the shape in current model is torch.Size([16]). size mismatch for backbone_net.model._blocks.1._se_reduce.conv.weight: copying a param with shape torch.Size([4, 96, 1, 1]) from checkpoint, the shape in current model is torch.Size([4, 16, 1, 1]). size mismatch for backbone_net.model._blocks.1._se_expand.conv.weight: copying a param with shape torch.Size([96, 4, 1, 1]) from checkpoint, the shape in current model is torch.Size([16, 4, 1, 1]). size mismatch for backbone_net.model._blocks.1._se_expand.conv.bias: copying a param with shape torch.Size([96]) from checkpoint, the shape in current model is torch.Size([16]). size mismatch for backbone_net.model._blocks.1._project_conv.conv.weight: copying a param with shape torch.Size([24, 96, 1, 1]) from checkpoint, the shape in current model is torch.Size([16, 16, 1, 1]). size mismatch for backbone_net.model._blocks.1._bn2.weight: copying a param with shape torch.Size([24]) from checkpoint, the shape in current model is torch.Size([16]). size mismatch for backbone_net.model._blocks.1._bn2.bias: copying a param with shape torch.Size([24]) from checkpoint, the shape in current model is torch.Size([16]). size mismatch for backbone_net.model._blocks.1._bn2.running_mean: copying a param with shape torch.Size([24]) from checkpoint, the shape in current model is torch.Size([16]). size mismatch for backbone_net.model._blocks.1._bn2.running_var: copying a param with shape torch.Size([24]) from checkpoint, the shape in current model is torch.Size([16]). size mismatch for backbone_net.model._blocks.2._expand_conv.conv.weight: copying a param with shape torch.Size([144, 24, 1, 1]) from checkpoint, the shape in current model is torch.Size([96, 16, 1, 1]). size mismatch for backbone_net.model._blocks.2._bn0.weight: copying a param with shape torch.Size([144]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for backbone_net.model._blocks.2._bn0.bias: copying a param with shape torch.Size([144]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for backbone_net.model._blocks.2._bn0.running_mean: copying a param with shape torch.Size([144]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for backbone_net.model._blocks.2._bn0.running_var: copying a param with shape torch.Size([144]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for backbone_net.model._blocks.2._depthwise_conv.conv.weight: copying a param with shape torch.Size([144, 1, 3, 3]) from checkpoint, the shape in current model is torch.Size([96, 1, 3, 3]). size mismatch for backbone_net.model._blocks.2._bn1.weight: copying a param with shape torch.Size([144]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for backbone_net.model._blocks.2._bn1.bias: copying a param with shape torch.Size([144]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for backbone_net.model._blocks.2._bn1.running_mean: copying a param with shape torch.Size([144]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for backbone_net.model._blocks.2._bn1.running_var: copying a param with shape torch.Size([144]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for backbone_net.model._blocks.2._se_reduce.conv.weight: copying a param with shape torch.Size([6, 144, 1, 1]) from checkpoint, the shape in current model is torch.Size([4, 96, 1, 1]). size mismatch for backbone_net.model._blocks.2._se_reduce.conv.bias: copying a param with shape torch.Size([6]) from checkpoint, the shape in current model is torch.Size([4]). size mismatch for backbone_net.model._blocks.2._se_expand.conv.weight: copying a param with shape torch.Size([144, 6, 1, 1]) from checkpoint, the shape in current model is torch.Size([96, 4, 1, 1]). size mismatch for backbone_net.model._blocks.2._se_expand.conv.bias: copying a param with shape torch.Size([144]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for backbone_net.model._blocks.2._project_conv.conv.weight: copying a param with shape torch.Size([24, 144, 1, 1]) from checkpoint, the shape in current model is torch.Size([24, 96, 1, 1]). size mismatch for backbone_net.model._blocks.3._depthwise_conv.conv.weight: copying a param with shape torch.Size([144, 1, 5, 5]) from checkpoint, the shape in current model is torch.Size([144, 1, 3, 3]). size mismatch for backbone_net.model._blocks.3._project_conv.conv.weight: copying a param with shape torch.Size([40, 144, 1, 1]) from checkpoint, the shape in current model is torch.Size([24, 144, 1, 1]). size mismatch for backbone_net.model._blocks.3._bn2.weight: copying a param with shape torch.Size([40]) from checkpoint, the shape in current model is torch.Size([24]). size mismatch for backbone_net.model._blocks.3._bn2.bias: copying a param with shape torch.Size([40]) from checkpoint, the shape in current model is torch.Size([24]). size mismatch for backbone_net.model._blocks.3._bn2.running_mean: copying a param with shape torch.Size([40]) from checkpoint, the shape in current model is torch.Size([24]). size mismatch for backbone_net.model._blocks.3._bn2.running_var: copying a param with shape torch.Size([40]) from checkpoint, the shape in current model is torch.Size([24]). size mismatch for backbone_net.model._blocks.4._expand_conv.conv.weight: copying a param with shape torch.Size([240, 40, 1, 1]) from checkpoint, the shape in current model is torch.Size([144, 24, 1, 1]). size mismatch for backbone_net.model._blocks.4._bn0.weight: copying a param with shape torch.Size([240]) from checkpoint, the shape in current model is torch.Size([144]). size mismatch for backbone_net.model._blocks.4._bn0.bias: copying a param with shape torch.Size([240]) from checkpoint, the shape in current model is torch.Size([144]). size mismatch for backbone_net.model._blocks.4._bn0.running_mean: copying a param with shape torch.Size([240]) from checkpoint, the shape in current model is torch.Size([144]). size mismatch for backbone_net.model._blocks.4._bn0.running_var: copying a param with shape torch.Size([240]) from checkpoint, the shape in current model is torch.Size([144]). size mismatch for backbone_net.model._blocks.4._depthwise_conv.conv.weight: copying a param with shape torch.Size([240, 1, 5, 5]) from checkpoint, the shape in current model is torch.Size([144, 1, 3, 3]). size mismatch for backbone_net.model._blocks.4._bn1.weight: copying a param with shape torch.Size([240]) from checkpoint, the shape in current model is torch.Size([144]). size mismatch for backbone_net.model._blocks.4._bn1.bias: copying a param with shape torch.Size([240]) from checkpoint, the shape in current model is torch.Size([144]). size mismatch for backbone_net.model._blocks.4._bn1.running_mean: copying a param with shape torch.Size([240]) from checkpoint, the shape in current model is torch.Size([144]). size mismatch for backbone_net.model._blocks.4._bn1.running_var: copying a param with shape torch.Size([240]) from checkpoint, the shape in current model is torch.Size([144]). size mismatch for backbone_net.model._blocks.4._se_reduce.conv.weight: copying a param with shape torch.Size([10, 240, 1, 1]) from checkpoint, the shape in current model is torch.Size([6, 144, 1, 1]). size mismatch for backbone_net.model._blocks.4._se_reduce.conv.bias: copying a param with shape torch.Size([10]) from checkpoint, the shape in current model is torch.Size([6]). size mismatch for backbone_net.model._blocks.4._se_expand.conv.weight: copying a param with shape torch.Size([240, 10, 1, 1]) from checkpoint, the shape in current model is torch.Size([144, 6, 1, 1]). size mismatch for backbone_net.model._blocks.4._se_expand.conv.bias: copying a param with shape torch.Size([240]) from checkpoint, the shape in current model is torch.Size([144]). size mismatch for backbone_net.model._blocks.4._project_conv.conv.weight: copying a param with shape torch.Size([40, 240, 1, 1]) from checkpoint, the shape in current model is torch.Size([24, 144, 1, 1]). size mismatch for backbone_net.model._blocks.4._bn2.weight: copying a param with shape torch.Size([40]) from checkpoint, the shape in current model is torch.Size([24]). size mismatch for backbone_net.model._blocks.4._bn2.bias: copying a param with shape torch.Size([40]) from checkpoint, the shape in current model is torch.Size([24]). size mismatch for backbone_net.model._blocks.4._bn2.running_mean: copying a param with shape torch.Size([40]) from checkpoint, the shape in current model is torch.Size([24]). size mismatch for backbone_net.model._blocks.4._bn2.running_var: copying a param with shape torch.Size([40]) from checkpoint, the shape in current model is torch.Size([24]). size mismatch for backbone_net.model._blocks.5._expand_conv.conv.weight: copying a param with shape torch.Size([240, 40, 1, 1]) from checkpoint, the shape in current model is torch.Size([144, 24, 1, 1]). size mismatch for backbone_net.model._blocks.5._bn0.weight: copying a param with shape torch.Size([240]) from checkpoint, the shape in current model is torch.Size([144]). size mismatch for backbone_net.model._blocks.5._bn0.bias: copying a param with shape torch.Size([240]) from checkpoint, the shape in current model is torch.Size([144]). size mismatch for backbone_net.model._blocks.5._bn0.running_mean: copying a param with shape torch.Size([240]) from checkpoint, the shape in current model is torch.Size([144]). size mismatch for backbone_net.model._blocks.5._bn0.running_var: copying a param with shape torch.Size([240]) from checkpoint, the shape in current model is torch.Size([144]). size mismatch for backbone_net.model._blocks.5._depthwise_conv.conv.weight: copying a param with shape torch.Size([240, 1, 3, 3]) from checkpoint, the shape in current model is torch.Size([144, 1, 5, 5]). size mismatch for backbone_net.model._blocks.5._bn1.weight: copying a param with shape torch.Size([240]) from checkpoint, the shape in current model is torch.Size([144]). size mismatch for backbone_net.model._blocks.5._bn1.bias: copying a param with shape torch.Size([240]) from checkpoint, the shape in current model is torch.Size([144]). size mismatch for backbone_net.model._blocks.5._bn1.running_mean: copying a param with shape torch.Size([240]) from checkpoint, the shape in current model is torch.Size([144]). size mismatch for backbone_net.model._blocks.5._bn1.running_var: copying a param with shape torch.Size([240]) from checkpoint, the shape in current model is torch.Size([144]). size mismatch for backbone_net.model._blocks.5._se_reduce.conv.weight: copying a param with shape torch.Size([10, 240, 1, 1]) from checkpoint, the shape in current model is torch.Size([6, 144, 1, 1]). size mismatch for backbone_net.model._blocks.5._se_reduce.conv.bias: copying a param with shape torch.Size([10]) from checkpoint, the shape in current model is torch.Size([6]). size mismatch for backbone_net.model._blocks.5._se_expand.conv.weight: copying a param with shape torch.Size([240, 10, 1, 1]) from checkpoint, the shape in current model is torch.Size([144, 6, 1, 1]). size mismatch for backbone_net.model._blocks.5._se_expand.conv.bias: copying a param with shape torch.Size([240]) from checkpoint, the shape in current model is torch.Size([144]). size mismatch for backbone_net.model._blocks.5._project_conv.conv.weight: copying a param with shape torch.Size([80, 240, 1, 1]) from checkpoint, the shape in current model is torch.Size([48, 144, 1, 1]). size mismatch for backbone_net.model._blocks.5._bn2.weight: copying a param with shape torch.Size([80]) from checkpoint, the shape in current model is torch.Size([48]). size mismatch for backbone_net.model._blocks.5._bn2.bias: copying a param with shape torch.Size([80]) from checkpoint, the shape in current model is torch.Size([48]). size mismatch for backbone_net.model._blocks.5._bn2.running_mean: copying a param with shape torch.Size([80]) from checkpoint, the shape in current model is torch.Size([48]). size mismatch for backbone_net.model._blocks.5._bn2.running_var: copying a param with shape torch.Size([80]) from checkpoint, the shape in current model is torch.Size([48]). size mismatch for backbone_net.model._blocks.6._expand_conv.conv.weight: copying a param with shape torch.Size([480, 80, 1, 1]) from checkpoint, the shape in current model is torch.Size([288, 48, 1, 1]). size mismatch for backbone_net.model._blocks.6._bn0.weight: copying a param with shape torch.Size([480]) from checkpoint, the shape in current model is torch.Size([288]). size mismatch for backbone_net.model._blocks.6._bn0.bias: copying a param with shape torch.Size([480]) from checkpoint, the shape in current model is torch.Size([288]). size mismatch for backbone_net.model._blocks.6._bn0.running_mean: copying a param with shape torch.Size([480]) from checkpoint, the shape in current model is torch.Size([288]). size mismatch for backbone_net.model._blocks.6._bn0.running_var: copying a param with shape torch.Size([480]) from checkpoint, the shape in current model is torch.Size([288]). size mismatch for backbone_net.model._blocks.6._depthwise_conv.conv.weight: copying a param with shape torch.Size([480, 1, 3, 3]) from checkpoint, the shape in current model is torch.Size([288, 1, 5, 5]). size mismatch for backbone_net.model._blocks.6._bn1.weight: copying a param with shape torch.Size([480]) from checkpoint, the shape in current model is torch.Size([288]). size mismatch for backbone_net.model._blocks.6._bn1.bias: copying a param with shape torch.Size([480]) from checkpoint, the shape in current model is torch.Size([288]). size mismatch for backbone_net.model._blocks.6._bn1.running_mean: copying a param with shape torch.Size([480]) from checkpoint, the shape in current model is torch.Size([288]). size mismatch for backbone_net.model._blocks.6._bn1.running_var: copying a param with shape torch.Size([480]) from checkpoint, the shape in current model is torch.Size([288]). size mismatch for backbone_net.model._blocks.6._se_reduce.conv.weight: copying a param with shape torch.Size([20, 480, 1, 1]) from checkpoint, the shape in current model is torch.Size([12, 288, 1, 1]). size mismatch for backbone_net.model._blocks.6._se_reduce.conv.bias: copying a param with shape torch.Size([20]) from checkpoint, the shape in current model is torch.Size([12]). size mismatch for backbone_net.model._blocks.6._se_expand.conv.weight: copying a param with shape torch.Size([480, 20, 1, 1]) from checkpoint, the shape in current model is torch.Size([288, 12, 1, 1]). size mismatch for backbone_net.model._blocks.6._se_expand.conv.bias: copying a param with shape torch.Size([480]) from checkpoint, the shape in current model is torch.Size([288]). size mismatch for backbone_net.model._blocks.6._project_conv.conv.weight: copying a param with shape torch.Size([80, 480, 1, 1]) from checkpoint, the shape in current model is torch.Size([48, 288, 1, 1]). size mismatch for backbone_net.model._blocks.6._bn2.weight: copying a param with shape torch.Size([80]) from checkpoint, the shape in current model is torch.Size([48]). size mismatch for backbone_net.model._blocks.6._bn2.bias: copying a param with shape torch.Size([80]) from checkpoint, the shape in current model is torch.Size([48]). size mismatch for backbone_net.model._blocks.6._bn2.running_mean: copying a param with shape torch.Size([80]) from checkpoint, the shape in current model is torch.Size([48]). size mismatch for backbone_net.model._blocks.6._bn2.running_var: copying a param with shape torch.Size([80]) from checkpoint, the shape in current model is torch.Size([48]). size mismatch for backbone_net.model._blocks.7._expand_conv.conv.weight: copying a param with shape torch.Size([480, 80, 1, 1]) from checkpoint, the shape in current model is torch.Size([288, 48, 1, 1]). size mismatch for backbone_net.model._blocks.7._bn0.weight: copying a param with shape torch.Size([480]) from checkpoint, the shape in current model is torch.Size([288]). size mismatch for backbone_net.model._blocks.7._bn0.bias: copying a param with shape torch.Size([480]) from checkpoint, the shape in current model is torch.Size([288]). size mismatch for backbone_net.model._blocks.7._bn0.running_mean: copying a param with shape torch.Size([480]) from checkpoint, the shape in current model is torch.Size([288]). size mismatch for backbone_net.model._blocks.7._bn0.running_var: copying a param with shape torch.Size([480]) from checkpoint, the shape in current model is torch.Size([288]). size mismatch for backbone_net.model._blocks.7._depthwise_conv.conv.weight: copying a param with shape torch.Size([480, 1, 3, 3]) from checkpoint, the shape in current model is torch.Size([288, 1, 5, 5]). size mismatch for backbone_net.model._blocks.7._bn1.weight: copying a param with shape torch.Size([480]) from checkpoint, the shape in current model is torch.Size([288]). size mismatch for backbone_net.model._blocks.7._bn1.bias: copying a param with shape torch.Size([480]) from checkpoint, the shape in current model is torch.Size([288]). size mismatch for backbone_net.model._blocks.7._bn1.running_mean: copying a param with shape torch.Size([480]) from checkpoint, the shape in current model is torch.Size([288]). size mismatch for backbone_net.model._blocks.7._bn1.running_var: copying a param with shape torch.Size([480]) from checkpoint, the shape in current model is torch.Size([288]). size mismatch for backbone_net.model._blocks.7._se_reduce.conv.weight: copying a param with shape torch.Size([20, 480, 1, 1]) from checkpoint, the shape in current model is torch.Size([12, 288, 1, 1]). size mismatch for backbone_net.model._blocks.7._se_reduce.conv.bias: copying a param with shape torch.Size([20]) from checkpoint, the shape in current model is torch.Size([12]). size mismatch for backbone_net.model._blocks.7._se_expand.conv.weight: copying a param with shape torch.Size([480, 20, 1, 1]) from checkpoint, the shape in current model is torch.Size([288, 12, 1, 1]). size mismatch for backbone_net.model._blocks.7._se_expand.conv.bias: copying a param with shape torch.Size([480]) from checkpoint, the shape in current model is torch.Size([288]). size mismatch for backbone_net.model._blocks.7._project_conv.conv.weight: copying a param with shape torch.Size([80, 480, 1, 1]) from checkpoint, the shape in current model is torch.Size([48, 288, 1, 1]). size mismatch for backbone_net.model._blocks.7._bn2.weight: copying a param with shape torch.Size([80]) from checkpoint, the shape in current model is torch.Size([48]). size mismatch for backbone_net.model._blocks.7._bn2.bias: copying a param with shape torch.Size([80]) from checkpoint, the shape in current model is torch.Size([48]). size mismatch for backbone_net.model._blocks.7._bn2.running_mean: copying a param with shape torch.Size([80]) from checkpoint, the shape in current model is torch.Size([48]). size mismatch for backbone_net.model._blocks.7._bn2.running_var: copying a param with shape torch.Size([80]) from checkpoint, the shape in current model is torch.Size([48]). size mismatch for backbone_net.model._blocks.8._expand_conv.conv.weight: copying a param with shape torch.Size([480, 80, 1, 1]) from checkpoint, the shape in current model is torch.Size([288, 48, 1, 1]). size mismatch for backbone_net.model._blocks.8._bn0.weight: copying a param with shape torch.Size([480]) from checkpoint, the shape in current model is torch.Size([288]). size mismatch for backbone_net.model._blocks.8._bn0.bias: copying a param with shape torch.Size([480]) from checkpoint, the shape in current model is torch.Size([288]). size mismatch for backbone_net.model._blocks.8._bn0.running_mean: copying a param with shape torch.Size([480]) from checkpoint, the shape in current model is torch.Size([288]). size mismatch for backbone_net.model._blocks.8._bn0.running_var: copying a param with shape torch.Size([480]) from checkpoint, the shape in current model is torch.Size([288]). size mismatch for backbone_net.model._blocks.8._depthwise_conv.conv.weight: copying a param with shape torch.Size([480, 1, 5, 5]) from checkpoint, the shape in current model is torch.Size([288, 1, 3, 3]). size mismatch for backbone_net.model._blocks.8._bn1.weight: copying a param with shape torch.Size([480]) from checkpoint, the shape in current model is torch.Size([288]). size mismatch for backbone_net.model._blocks.8._bn1.bias: copying a param with shape torch.Size([480]) from checkpoint, the shape in current model is torch.Size([288]). size mismatch for backbone_net.model._blocks.8._bn1.running_mean: copying a param with shape torch.Size([480]) from checkpoint, the shape in current model is torch.Size([288]). size mismatch for backbone_net.model._blocks.8._bn1.running_var: copying a param with shape torch.Size([480]) from checkpoint, the shape in current model is torch.Size([288]). size mismatch for backbone_net.model._blocks.8._se_reduce.conv.weight: copying a param with shape torch.Size([20, 480, 1, 1]) from checkpoint, the shape in current model is torch.Size([12, 288, 1, 1]). size mismatch for backbone_net.model._blocks.8._se_reduce.conv.bias: copying a param with shape torch.Size([20]) from checkpoint, the shape in current model is torch.Size([12]). size mismatch for backbone_net.model._blocks.8._se_expand.conv.weight: copying a param with shape torch.Size([480, 20, 1, 1]) from checkpoint, the shape in current model is torch.Size([288, 12, 1, 1]). size mismatch for backbone_net.model._blocks.8._se_expand.conv.bias: copying a param with shape torch.Size([480]) from checkpoint, the shape in current model is torch.Size([288]). size mismatch for backbone_net.model._blocks.8._project_conv.conv.weight: copying a param with shape torch.Size([112, 480, 1, 1]) from checkpoint, the shape in current model is torch.Size([88, 288, 1, 1]). size mismatch for backbone_net.model._blocks.8._bn2.weight: copying a param with shape torch.Size([112]) from checkpoint, the shape in current model is torch.Size([88]). size mismatch for backbone_net.model._blocks.8._bn2.bias: copying a param with shape torch.Size([112]) from checkpoint, the shape in current model is torch.Size([88]). size mismatch for backbone_net.model._blocks.8._bn2.running_mean: copying a param with shape torch.Size([112]) from checkpoint, the shape in current model is torch.Size([88]). size mismatch for backbone_net.model._blocks.8._bn2.running_var: copying a param with shape torch.Size([112]) from checkpoint, the shape in current model is torch.Size([88]). size mismatch for backbone_net.model._blocks.9._expand_conv.conv.weight: copying a param with shape torch.Size([672, 112, 1, 1]) from checkpoint, the shape in current model is torch.Size([528, 88, 1, 1]). size mismatch for backbone_net.model._blocks.9._bn0.weight: copying a param with shape torch.Size([672]) from checkpoint, the shape in current model is torch.Size([528]). size mismatch for backbone_net.model._blocks.9._bn0.bias: copying a param with shape torch.Size([672]) from checkpoint, the shape in current model is torch.Size([528]). size mismatch for backbone_net.model._blocks.9._bn0.running_mean: copying a param with shape torch.Size([672]) from checkpoint, the shape in current model is torch.Size([528]). size mismatch for backbone_net.model._blocks.9._bn0.running_var: copying a param with shape torch.Size([672]) from checkpoint, the shape in current model is torch.Size([528]). size mismatch for backbone_net.model._blocks.9._depthwise_conv.conv.weight: copying a param with shape torch.Size([672, 1, 5, 5]) from checkpoint, the shape in current model is torch.Size([528, 1, 3, 3]). size mismatch for backbone_net.model._blocks.9._bn1.weight: copying a param with shape torch.Size([672]) from checkpoint, the shape in current model is torch.Size([528]). size mismatch for backbone_net.model._blocks.9._bn1.bias: copying a param with shape torch.Size([672]) from checkpoint, the shape in current model is torch.Size([528]). size mismatch for backbone_net.model._blocks.9._bn1.running_mean: copying a param with shape torch.Size([672]) from checkpoint, the shape in current model is torch.Size([528]). size mismatch for backbone_net.model._blocks.9._bn1.running_var: copying a param with shape torch.Size([672]) from checkpoint, the shape in current model is torch.Size([528]). size mismatch for backbone_net.model._blocks.9._se_reduce.conv.weight: copying a param with shape torch.Size([28, 672, 1, 1]) from checkpoint, the shape in current model is torch.Size([22, 528, 1, 1]). size mismatch for backbone_net.model._blocks.9._se_reduce.conv.bias: copying a param with shape torch.Size([28]) from checkpoint, the shape in current model is torch.Size([22]). size mismatch for backbone_net.model._blocks.9._se_expand.conv.weight: copying a param with shape torch.Size([672, 28, 1, 1]) from checkpoint, the shape in current model is torch.Size([528, 22, 1, 1]). size mismatch for backbone_net.model._blocks.9._se_expand.conv.bias: copying a param with shape torch.Size([672]) from checkpoint, the shape in current model is torch.Size([528]). size mismatch for backbone_net.model._blocks.9._project_conv.conv.weight: copying a param with shape torch.Size([112, 672, 1, 1]) from checkpoint, the shape in current model is torch.Size([88, 528, 1, 1]). size mismatch for backbone_net.model._blocks.9._bn2.weight: copying a param with shape torch.Size([112]) from checkpoint, the shape in current model is torch.Size([88]). size mismatch for backbone_net.model._blocks.9._bn2.bias: copying a param with shape torch.Size([112]) from checkpoint, the shape in current model is torch.Size([88]). size mismatch for backbone_net.model._blocks.9._bn2.running_mean: copying a param with shape torch.Size([112]) from checkpoint, the shape in current model is torch.Size([88]). size mismatch for backbone_net.model._blocks.9._bn2.running_var: copying a param with shape torch.Size([112]) from checkpoint, the shape in current model is torch.Size([88]). size mismatch for backbone_net.model._blocks.10._expand_conv.conv.weight: copying a param with shape torch.Size([672, 112, 1, 1]) from checkpoint, the shape in current model is torch.Size([528, 88, 1, 1]). size mismatch for backbone_net.model._blocks.10._bn0.weight: copying a param with shape torch.Size([672]) from checkpoint, the shape in current model is torch.Size([528]). size mismatch for backbone_net.model._blocks.10._bn0.bias: copying a param with shape torch.Size([672]) from checkpoint, the shape in current model is torch.Size([528]). size mismatch for backbone_net.model._blocks.10._bn0.running_mean: copying a param with shape torch.Size([672]) from checkpoint, the shape in current model is torch.Size([528]). size mismatch for backbone_net.model._blocks.10._bn0.running_var: copying a param with shape torch.Size([672]) from checkpoint, the shape in current model is torch.Size([528]). size mismatch for backbone_net.model._blocks.10._depthwise_conv.conv.weight: copying a param with shape torch.Size([672, 1, 5, 5]) from checkpoint, the shape in current model is torch.Size([528, 1, 3, 3]). size mismatch for backbone_net.model._blocks.10._bn1.weight: copying a param with shape torch.Size([672]) from checkpoint, the shape in current model is torch.Size([528]). size mismatch for backbone_net.model._blocks.10._bn1.bias: copying a param with shape torch.Size([672]) from checkpoint, the shape in current model is torch.Size([528]). size mismatch for backbone_net.model._blocks.10._bn1.running_mean: copying a param with shape torch.Size([672]) from checkpoint, the shape in current model is torch.Size([528]). size mismatch for backbone_net.model._blocks.10._bn1.running_var: copying a param with shape torch.Size([672]) from checkpoint, the shape in current model is torch.Size([528]). size mismatch for backbone_net.model._blocks.10._se_reduce.conv.weight: copying a param with shape torch.Size([28, 672, 1, 1]) from checkpoint, the shape in current model is torch.Size([22, 528, 1, 1]). size mismatch for backbone_net.model._blocks.10._se_reduce.conv.bias: copying a param with shape torch.Size([28]) from checkpoint, the shape in current model is torch.Size([22]). size mismatch for backbone_net.model._blocks.10._se_expand.conv.weight: copying a param with shape torch.Size([672, 28, 1, 1]) from checkpoint, the shape in current model is torch.Size([528, 22, 1, 1]). size mismatch for backbone_net.model._blocks.10._se_expand.conv.bias: copying a param with shape torch.Size([672]) from checkpoint, the shape in current model is torch.Size([528]). size mismatch for backbone_net.model._blocks.10._project_conv.conv.weight: copying a param with shape torch.Size([112, 672, 1, 1]) from checkpoint, the shape in current model is torch.Size([88, 528, 1, 1]). size mismatch for backbone_net.model._blocks.10._bn2.weight: copying a param with shape torch.Size([112]) from checkpoint, the shape in current model is torch.Size([88]). size mismatch for backbone_net.model._blocks.10._bn2.bias: copying a param with shape torch.Size([112]) from checkpoint, the shape in current model is torch.Size([88]). size mismatch for backbone_net.model._blocks.10._bn2.running_mean: copying a param with shape torch.Size([112]) from checkpoint, the shape in current model is torch.Size([88]). size mismatch for backbone_net.model._blocks.10._bn2.running_var: copying a param with shape torch.Size([112]) from checkpoint, the shape in current model is torch.Size([88]). size mismatch for backbone_net.model._blocks.11._expand_conv.conv.weight: copying a param with shape torch.Size([672, 112, 1, 1]) from checkpoint, the shape in current model is torch.Size([528, 88, 1, 1]). size mismatch for backbone_net.model._blocks.11._bn0.weight: copying a param with shape torch.Size([672]) from checkpoint, the shape in current model is torch.Size([528]). size mismatch for backbone_net.model._blocks.11._bn0.bias: copying a param with shape torch.Size([672]) from checkpoint, the shape in current model is torch.Size([528]). size mismatch for backbone_net.model._blocks.11._bn0.running_mean: copying a param with shape torch.Size([672]) from checkpoint, the shape in current model is torch.Size([528]). size mismatch for backbone_net.model._blocks.11._bn0.running_var: copying a param with shape torch.Size([672]) from checkpoint, the shape in current model is torch.Size([528]). size mismatch for backbone_net.model._blocks.11._depthwise_conv.conv.weight: copying a param with shape torch.Size([672, 1, 5, 5]) from checkpoint, the shape in current model is torch.Size([528, 1, 3, 3]). size mismatch for backbone_net.model._blocks.11._bn1.weight: copying a param with shape torch.Size([672]) from checkpoint, the shape in current model is torch.Size([528]). size mismatch for backbone_net.model._blocks.11._bn1.bias: copying a param with shape torch.Size([672]) from checkpoint, the shape in current model is torch.Size([528]). size mismatch for backbone_net.model._blocks.11._bn1.running_mean: copying a param with shape torch.Size([672]) from checkpoint, the shape in current model is torch.Size([528]). size mismatch for backbone_net.model._blocks.11._bn1.running_var: copying a param with shape torch.Size([672]) from checkpoint, the shape in current model is torch.Size([528]). size mismatch for backbone_net.model._blocks.11._se_reduce.conv.weight: copying a param with shape torch.Size([28, 672, 1, 1]) from checkpoint, the shape in current model is torch.Size([22, 528, 1, 1]). size mismatch for backbone_net.model._blocks.11._se_reduce.conv.bias: copying a param with shape torch.Size([28]) from checkpoint, the shape in current model is torch.Size([22]). size mismatch for backbone_net.model._blocks.11._se_expand.conv.weight: copying a param with shape torch.Size([672, 28, 1, 1]) from checkpoint, the shape in current model is torch.Size([528, 22, 1, 1]). size mismatch for backbone_net.model._blocks.11._se_expand.conv.bias: copying a param with shape torch.Size([672]) from checkpoint, the shape in current model is torch.Size([528]). size mismatch for backbone_net.model._blocks.11._project_conv.conv.weight: copying a param with shape torch.Size([192, 672, 1, 1]) from checkpoint, the shape in current model is torch.Size([88, 528, 1, 1]). size mismatch for backbone_net.model._blocks.11._bn2.weight: copying a param with shape torch.Size([192]) from checkpoint, the shape in current model is torch.Size([88]). size mismatch for backbone_net.model._blocks.11._bn2.bias: copying a param with shape torch.Size([192]) from checkpoint, the shape in current model is torch.Size([88]). size mismatch for backbone_net.model._blocks.11._bn2.running_mean: copying a param with shape torch.Size([192]) from checkpoint, the shape in current model is torch.Size([88]). size mismatch for backbone_net.model._blocks.11._bn2.running_var: copying a param with shape torch.Size([192]) from checkpoint, the shape in current model is torch.Size([88]). size mismatch for backbone_net.model._blocks.12._expand_conv.conv.weight: copying a param with shape torch.Size([1152, 192, 1, 1]) from checkpoint, the shape in current model is torch.Size([528, 88, 1, 1]). size mismatch for backbone_net.model._blocks.12._bn0.weight: copying a param with shape torch.Size([1152]) from checkpoint, the shape in current model is torch.Size([528]). size mismatch for backbone_net.model._blocks.12._bn0.bias: copying a param with shape torch.Size([1152]) from checkpoint, the shape in current model is torch.Size([528]). size mismatch for backbone_net.model._blocks.12._bn0.running_mean: copying a param with shape torch.Size([1152]) from checkpoint, the shape in current model is torch.Size([528]). size mismatch for backbone_net.model._blocks.12._bn0.running_var: copying a param with shape torch.Size([1152]) from checkpoint, the shape in current model is torch.Size([528]). size mismatch for backbone_net.model._blocks.12._depthwise_conv.conv.weight: copying a param with shape torch.Size([1152, 1, 5, 5]) from checkpoint, the shape in current model is torch.Size([528, 1, 5, 5]). size mismatch for backbone_net.model._blocks.12._bn1.weight: copying a param with shape torch.Size([1152]) from checkpoint, the shape in current model is torch.Size([528]). size mismatch for backbone_net.model._blocks.12._bn1.bias: copying a param with shape torch.Size([1152]) from checkpoint, the shape in current model is torch.Size([528]). size mismatch for backbone_net.model._blocks.12._bn1.running_mean: copying a param with shape torch.Size([1152]) from checkpoint, the shape in current model is torch.Size([528]). size mismatch for backbone_net.model._blocks.12._bn1.running_var: copying a param with shape torch.Size([1152]) from checkpoint, the shape in current model is torch.Size([528]). size mismatch for backbone_net.model._blocks.12._se_reduce.conv.weight: copying a param with shape torch.Size([48, 1152, 1, 1]) from checkpoint, the shape in current model is torch.Size([22, 528, 1, 1]). size mismatch for backbone_net.model._blocks.12._se_reduce.conv.bias: copying a param with shape torch.Size([48]) from checkpoint, the shape in current model is torch.Size([22]). size mismatch for backbone_net.model._blocks.12._se_expand.conv.weight: copying a param with shape torch.Size([1152, 48, 1, 1]) from checkpoint, the shape in current model is torch.Size([528, 22, 1, 1]). size mismatch for backbone_net.model._blocks.12._se_expand.conv.bias: copying a param with shape torch.Size([1152]) from checkpoint, the shape in current model is torch.Size([528]). size mismatch for backbone_net.model._blocks.12._project_conv.conv.weight: copying a param with shape torch.Size([192, 1152, 1, 1]) from checkpoint, the shape in current model is torch.Size([120, 528, 1, 1]). size mismatch for backbone_net.model._blocks.12._bn2.weight: copying a param with shape torch.Size([192]) from checkpoint, the shape in current model is torch.Size([120]). size mismatch for backbone_net.model._blocks.12._bn2.bias: copying a param with shape torch.Size([192]) from checkpoint, the shape in current model is torch.Size([120]). size mismatch for backbone_net.model._blocks.12._bn2.running_mean: copying a param with shape torch.Size([192]) from checkpoint, the shape in current model is torch.Size([120]). size mismatch for backbone_net.model._blocks.12._bn2.running_var: copying a param with shape torch.Size([192]) from checkpoint, the shape in current model is torch.Size([120]). size mismatch for backbone_net.model._blocks.13._expand_conv.conv.weight: copying a param with shape torch.Size([1152, 192, 1, 1]) from checkpoint, the shape in current model is torch.Size([720, 120, 1, 1]). size mismatch for backbone_net.model._blocks.13._bn0.weight: copying a param with shape torch.Size([1152]) from checkpoint, the shape in current model is torch.Size([720]). size mismatch for backbone_net.model._blocks.13._bn0.bias: copying a param with shape torch.Size([1152]) from checkpoint, the shape in current model is torch.Size([720]). size mismatch for backbone_net.model._blocks.13._bn0.running_mean: copying a param with shape torch.Size([1152]) from checkpoint, the shape in current model is torch.Size([720]). size mismatch for backbone_net.model._blocks.13._bn0.running_var: copying a param with shape torch.Size([1152]) from checkpoint, the shape in current model is torch.Size([720]). size mismatch for backbone_net.model._blocks.13._depthwise_conv.conv.weight: copying a param with shape torch.Size([1152, 1, 5, 5]) from checkpoint, the shape in current model is torch.Size([720, 1, 5, 5]). size mismatch for backbone_net.model._blocks.13._bn1.weight: copying a param with shape torch.Size([1152]) from checkpoint, the shape in current model is torch.Size([720]). size mismatch for backbone_net.model._blocks.13._bn1.bias: copying a param with shape torch.Size([1152]) from checkpoint, the shape in current model is torch.Size([720]). size mismatch for backbone_net.model._blocks.13._bn1.running_mean: copying a param with shape torch.Size([1152]) from checkpoint, the shape in current model is torch.Size([720]). size mismatch for backbone_net.model._blocks.13._bn1.running_var: copying a param with shape torch.Size([1152]) from checkpoint, the shape in current model is torch.Size([720]). size mismatch for backbone_net.model._blocks.13._se_reduce.conv.weight: copying a param with shape torch.Size([48, 1152, 1, 1]) from checkpoint, the shape in current model is torch.Size([30, 720, 1, 1]). size mismatch for backbone_net.model._blocks.13._se_reduce.conv.bias: copying a param with shape torch.Size([48]) from checkpoint, the shape in current model is torch.Size([30]). size mismatch for backbone_net.model._blocks.13._se_expand.conv.weight: copying a param with shape torch.Size([1152, 48, 1, 1]) from checkpoint, the shape in current model is torch.Size([720, 30, 1, 1]). size mismatch for backbone_net.model._blocks.13._se_expand.conv.bias: copying a param with shape torch.Size([1152]) from checkpoint, the shape in current model is torch.Size([720]). size mismatch for backbone_net.model._blocks.13._project_conv.conv.weight: copying a param with shape torch.Size([192, 1152, 1, 1]) from checkpoint, the shape in current model is torch.Size([120, 720, 1, 1]). size mismatch for backbone_net.model._blocks.13._bn2.weight: copying a param with shape torch.Size([192]) from checkpoint, the shape in current model is torch.Size([120]). size mismatch for backbone_net.model._blocks.13._bn2.bias: copying a param with shape torch.Size([192]) from checkpoint, the shape in current model is torch.Size([120]). size mismatch for backbone_net.model._blocks.13._bn2.running_mean: copying a param with shape torch.Size([192]) from checkpoint, the shape in current model is torch.Size([120]). size mismatch for backbone_net.model._blocks.13._bn2.running_var: copying a param with shape torch.Size([192]) from checkpoint, the shape in current model is torch.Size([120]). size mismatch for backbone_net.model._blocks.14._expand_conv.conv.weight: copying a param with shape torch.Size([1152, 192, 1, 1]) from checkpoint, the shape in current model is torch.Size([720, 120, 1, 1]). size mismatch for backbone_net.model._blocks.14._bn0.weight: copying a param with shape torch.Size([1152]) from checkpoint, the shape in current model is torch.Size([720]). size mismatch for backbone_net.model._blocks.14._bn0.bias: copying a param with shape torch.Size([1152]) from checkpoint, the shape in current model is torch.Size([720]). size mismatch for backbone_net.model._blocks.14._bn0.running_mean: copying a param with shape torch.Size([1152]) from checkpoint, the shape in current model is torch.Size([720]). size mismatch for backbone_net.model._blocks.14._bn0.running_var: copying a param with shape torch.Size([1152]) from checkpoint, the shape in current model is torch.Size([720]). size mismatch for backbone_net.model._blocks.14._depthwise_conv.conv.weight: copying a param with shape torch.Size([1152, 1, 5, 5]) from checkpoint, the shape in current model is torch.Size([720, 1, 5, 5]). size mismatch for backbone_net.model._blocks.14._bn1.weight: copying a param with shape torch.Size([1152]) from checkpoint, the shape in current model is torch.Size([720]). size mismatch for backbone_net.model._blocks.14._bn1.bias: copying a param with shape torch.Size([1152]) from checkpoint, the shape in current model is torch.Size([720]). size mismatch for backbone_net.model._blocks.14._bn1.running_mean: copying a param with shape torch.Size([1152]) from checkpoint, the shape in current model is torch.Size([720]). size mismatch for backbone_net.model._blocks.14._bn1.running_var: copying a param with shape torch.Size([1152]) from checkpoint, the shape in current model is torch.Size([720]). size mismatch for backbone_net.model._blocks.14._se_reduce.conv.weight: copying a param with shape torch.Size([48, 1152, 1, 1]) from checkpoint, the shape in current model is torch.Size([30, 720, 1, 1]). size mismatch for backbone_net.model._blocks.14._se_reduce.conv.bias: copying a param with shape torch.Size([48]) from checkpoint, the shape in current model is torch.Size([30]). size mismatch for backbone_net.model._blocks.14._se_expand.conv.weight: copying a param with shape torch.Size([1152, 48, 1, 1]) from checkpoint, the shape in current model is torch.Size([720, 30, 1, 1]). size mismatch for backbone_net.model._blocks.14._se_expand.conv.bias: copying a param with shape torch.Size([1152]) from checkpoint, the shape in current model is torch.Size([720]). size mismatch for backbone_net.model._blocks.14._project_conv.conv.weight: copying a param with shape torch.Size([192, 1152, 1, 1]) from checkpoint, the shape in current model is torch.Size([120, 720, 1, 1]). size mismatch for backbone_net.model._blocks.14._bn2.weight: copying a param with shape torch.Size([192]) from checkpoint, the shape in current model is torch.Size([120]). size mismatch for backbone_net.model._blocks.14._bn2.bias: copying a param with shape torch.Size([192]) from checkpoint, the shape in current model is torch.Size([120]). size mismatch for backbone_net.model._blocks.14._bn2.running_mean: copying a param with shape torch.Size([192]) from checkpoint, the shape in current model is torch.Size([120]). size mismatch for backbone_net.model._blocks.14._bn2.running_var: copying a param with shape torch.Size([192]) from checkpoint, the shape in current model is torch.Size([120]). size mismatch for backbone_net.model._blocks.15._expand_conv.conv.weight: copying a param with shape torch.Size([1152, 192, 1, 1]) from checkpoint, the shape in current model is torch.Size([720, 120, 1, 1]). size mismatch for backbone_net.model._blocks.15._bn0.weight: copying a param with shape torch.Size([1152]) from checkpoint, the shape in current model is torch.Size([720]). size mismatch for backbone_net.model._blocks.15._bn0.bias: copying a param with shape torch.Size([1152]) from checkpoint, the shape in current model is torch.Size([720]). size mismatch for backbone_net.model._blocks.15._bn0.running_mean: copying a param with shape torch.Size([1152]) from checkpoint, the shape in current model is torch.Size([720]). size mismatch for backbone_net.model._blocks.15._bn0.running_var: copying a param with shape torch.Size([1152]) from checkpoint, the shape in current model is torch.Size([720]). size mismatch for backbone_net.model._blocks.15._depthwise_conv.conv.weight: copying a param with shape torch.Size([1152, 1, 3, 3]) from checkpoint, the shape in current model is torch.Size([720, 1, 5, 5]). size mismatch for backbone_net.model._blocks.15._bn1.weight: copying a param with shape torch.Size([1152]) from checkpoint, the shape in current model is torch.Size([720]). size mismatch for backbone_net.model._blocks.15._bn1.bias: copying a param with shape torch.Size([1152]) from checkpoint, the shape in current model is torch.Size([720]). size mismatch for backbone_net.model._blocks.15._bn1.running_mean: copying a param with shape torch.Size([1152]) from checkpoint, the shape in current model is torch.Size([720]). size mismatch for backbone_net.model._blocks.15._bn1.running_var: copying a param with shape torch.Size([1152]) from checkpoint, the shape in current model is torch.Size([720]). size mismatch for backbone_net.model._blocks.15._se_reduce.conv.weight: copying a param with shape torch.Size([48, 1152, 1, 1]) from checkpoint, the shape in current model is torch.Size([30, 720, 1, 1]). size mismatch for backbone_net.model._blocks.15._se_reduce.conv.bias: copying a param with shape torch.Size([48]) from checkpoint, the shape in current model is torch.Size([30]). size mismatch for backbone_net.model._blocks.15._se_expand.conv.weight: copying a param with shape torch.Size([1152, 48, 1, 1]) from checkpoint, the shape in current model is torch.Size([720, 30, 1, 1]). size mismatch for backbone_net.model._blocks.15._se_expand.conv.bias: copying a param with shape torch.Size([1152]) from checkpoint, the shape in current model is torch.Size([720]). size mismatch for backbone_net.model._blocks.15._project_conv.conv.weight: copying a param with shape torch.Size([320, 1152, 1, 1]) from checkpoint, the shape in current model is torch.Size([120, 720, 1, 1]). size mismatch for backbone_net.model._blocks.15._bn2.weight: copying a param with shape torch.Size([320]) from checkpoint, the shape in current model is torch.Size([120]). size mismatch for backbone_net.model._blocks.15._bn2.bias: copying a param with shape torch.Size([320]) from checkpoint, the shape in current model is torch.Size([120]). size mismatch for backbone_net.model._blocks.15._bn2.running_mean: copying a param with shape torch.Size([320]) from checkpoint, the shape in current model is torch.Size([120]). size mismatch for backbone_net.model._blocks.15._bn2.running_var: copying a param with shape torch.Size([320]) from checkpoint, the shape in current model is torch.Size([120]). [Warning] Don't panic if you see this, this might be because you load a pretrained weights with different number of classes. The rest of the weights should be loaded already. [Info] loaded weights: efficientdet-d0.pth, resuming checkpoint from step: 0 [Info] freezed backbone 0%| | 0/3 [00:00<?, ?it/s]C:\ProgramData\Anaconda3\envs\effdetpy\lib\site-packages\torch\cuda\nccl.py:16: UserWarning: PyTorch is not compiled with NCCL support warnings.warn('PyTorch is not compiled with NCCL support') Step: 2. Epoch: 0/10. Iteration: 3/3. Cls loss: 592.75928. Reg loss: 9.23222. Total loss: 601.99152: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:08<00:00, 2.94s/it] C:\ProgramData\Anaconda3\envs\effdetpy\lib\site-packages\numpy\core\fromnumeric.py:3372: RuntimeWarning: Mean of empty slice. return _methods._mean(a, axis=axis, dtype=dtype, C:\ProgramData\Anaconda3\envs\effdetpy\lib\site-packages\numpy\core\_methods.py:170: RuntimeWarning: invalid value encountered in double_scalars ret = ret.dtype.type(ret / rcount) Val. Epoch: 0/10. Classification loss: nan. Regression loss: nan. Total loss: nan WARNING:root:NaN or Inf found in input tensor. WARNING:root:NaN or Inf found in input tensor. WARNING:root:NaN or Inf found in input tensor. WARNING:root:NaN or Inf found in input tensor. WARNING:root:NaN or Inf found in input tensor. WARNING:root:NaN or Inf found in input tensor.
The first chunk of errors, is due the pretreined weights having more classes than my dataset, but after it starts training, the "WARNING:root:NaN or Inf found in input tensor." I couldnt find out what does it mean and after I let it train, there's no resulting weight saved.
zylo117
commented
3 years ago -c 2 means running on a D2 model while you loaded a D0 pretrained weights
Hello there,
I've been struggling to start training due my dataset/annotations. I currently have my imgs (2k+) annotated in YOLO txt format and tried to convert it to COCO JSON unsucessfully, then, tried to re-label it on COCO with a small dataset to "try" the efficientdet. My Dataset is private and I can't share IT, but, I can share the resulting JSON, as it seems that is the root cause for KeyError: 'category_id' error.
The error is the following:
(effdetpy) E:\PorosityDetection\Yet-Another-EfficientDet-Pytorch-master\Yet-Another-EfficientDet-Pytorch-master>python train.py -c 2 -p PorosityDetection --batch_size 8 --lr 1e-3 --num_epochs 10 --load_weights E:/PorosityDetection/Yet-Another-EfficientDet-Pytorch-master/Yet-Another-EfficientDet-Pytorch-master/weights/efficientdet-d8.pth --head_only True loading annotations into memory... Done (t=0.00s) creating index... Traceback (most recent call last): File "train.py", line 326, in <module> train(opt) File "train.py", line 113, in train training_set = CocoDataset(root_dir=os.path.join(opt.data_path, params.project_name), set=params.train_set, File "E:\PorosityDetection\Yet-Another-EfficientDet-Pytorch-master\Yet-Another-EfficientDet-Pytorch-master\efficientdet\dataset.py", line 17, in __init__ self.coco = COCO(os.path.join(self.root_dir, 'annotations', 'instances_' + self.set_name + '.json')) File "C:\ProgramData\Anaconda3\envs\effdetpy\lib\site-packages\pycocotools\coco.py", line 89, in __init__ self.createIndex() File "C:\ProgramData\Anaconda3\envs\effdetpy\lib\site-packages\pycocotools\coco.py", line 111, in createIndex catToImgs[ann['category_id']].append(ann['image_id']) KeyError: 'category_id'I did the annotations using (makesense.ai) that resulted the following:
For train
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{"info":{"description":"PorosityDetection"},"images":[{"id":1,"width":1000,"height":1000,"file_name":"38%20(HD)%20(3)..jpg"},{"id":2,"width":1000,"height":1000,"file_name":"38%20(HD)%20(4)..jpg"},{"id":3,"width":1010,"height":557,"file_name":"38.jpg"},{"id":4,"width":1220,"height":769,"file_name":"38_2-4mm_(HD).JPG"},{"id":5,"width":1086,"height":516,"file_name":"38_6-8mm_(HD).JPG"},{"id":6,"width":1000,"height":1000,"file_name":"38-1_HD_4%20a%206..jpg"},{"id":7,"width":1172,"height":584,"file_name":"39_2-4mm_(HD)%20(2).JPG"}],"annotations":[{"id":0,"iscrowd":0,"image_id":1,"category_id": 1,"segmentation":[[926.7461669505963,570.6984667802385,890.1192504258944,579.2163543441227,916.5247018739352,596.252129471891]],"bbox":[890.1192504258944,570.6984667802385,36.62691652470187,25.55366269165245],"area":424.4432900231877},{"id":1,"iscrowd":0,"image_id":2,"category_id": 1,"segmentation":[[949.7444633730835,655.87734241908,924.190800681431,674.6166950596252,954.855195911414,683.9863713798978,966.7802385008517,673.7649063032368]],"bbox":[924.190800681431,655.87734241908,42.58943781942071,28.109028960817795],"area":600.7505028020532},{"id":2,"iscrowd":0,"image_id":3,"category_id": 1,"segmentation":[[530.8974358974359,345.4017094017094,622.0779914529915,364.2852564102564,608.0502136752136,412.84294871794873,534.1346153846154,407.9871794871795]],"bbox":[530.8974358974359,345.4017094017094,91.18055555555554,67.44123931623932],"area":4651.367515660387},{"id":3,"iscrowd":0,"image_id":4,"category_id": 1,"segmentation":[[462.61925042589434,642.5800681431006,539.2572402044293,646.5102214650767,539.2572402044293,688.4318568994889,464.5843270868824,686.4667802385009,443.62350936967624,661.5758091993185]],"bbox":[443.62350936967624,642.5800681431006,95.63373083475307,45.85178875638837],"area":3678.5328435668907},{"id":4,"iscrowd":0,"image_id":5,"category_id": 1,"segmentation":[[384.62500000000006,365.32371794871796,346.9166666666667,443.06089743589746,392.1666666666667,460.4647435897436,467.58333333333337,393.16987179487177]],"bbox":[346.9166666666667,365.32371794871796,120.66666666666669,95.14102564102564],"area":5928.305956196582},{"id":5,"iscrowd":0,"image_id":5,"category_id": 1,"segmentation":[[637.5608974358975,382.7275641025641,603.3333333333334,442.4807692307692,663.0865384615386,470.90705128205127,733.2820512820514,415.2147435897436]],"bbox":[603.3333333333334,382.7275641025641,129.948717948718,88.17948717948718],"area":6077.397045529251},{"id":6,"iscrowd":0,"image_id":6,"category_id": 1,"segmentation":[[314.31005110732536,742.7597955706984,199.31856899488926,764.9063032367973,214.65076660988075,838.160136286201,264.05451448040884,822.8279386712095,335.6047700170358,754.6848381601363]],"bbox":[199.31856899488926,742.7597955706984,136.2862010221465,95.40034071550258],"area":7126.294007876506},{"id":7,"iscrowd":0,"image_id":7,"category_id": 1,"segmentation":[[471.4294871794872,412.20512820512823,443.2564102564103,479.8205128205129,495.84615384615387,492.9679487179488,511.4978632478632,421.59615384615387]],"bbox":[443.2564102564103,412.20512820512823,68.24145299145295,80.76282051282055],"area":3466.508492220033},{"id":8,"iscrowd":0,"image_id":7,"category_id": 1,"segmentation":[[801.9935897435897,430.98717948717956,863.3482905982906,487.95940170940173,818.2713675213676,535.5405982905984,774.4465811965812,508.61965811965814,772.5683760683761,451.64743589743597]],"bbox":[772.5683760683761,430.98717948717956,90.77991452991455,104.55341880341882],"area":5673.252365037617}],"categories":[{"id":1,"name":"Porosity"}]}My Yaml
`project_name: PorosityDetection # also the folder name of the dataset that under data_path folder train_set: train_porosity val_set: val_porosity num_gpus: 2
mean and std in RGB order, actually this part should remain unchanged as long as your dataset is similar to coco. mean: [0.485, 0.456, 0.406] std: [0.229, 0.224, 0.225]
this is coco anchors, change it if necessary anchors_scales: '[2 0, 2 (1.0 / 3.0), 2 ** (2.0 / 3.0)]' anchors_ratios: '[(1.0, 1.0), (1.4, 0.7), (0.7, 1.4)]'
must match your dataset's category_id. category_id is one_indexed, obj_list: [ 'Porosity']`
I double checked and Category_ID is an integer, and I cant figure out what is generating the error. Also, if necessary, I can relabel my images with another software and would be really pleased if you indicate one that works flawlessly.