Error in inference after re-training the model

[OmkarThawakar]

After re-training, the model following error occurs in inference.py

training params , --backbone resnet101, --pretrained_weights 384_coco_r101.pth

Error :

Traceback (most recent call last):
File "inference.py", line 258, in
main(args)
File "inference.py", line 190, in main
model.load_state_dict(state_dict)
File "/home/omkarthawakar/anaconda3/envs/vistr/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1045, in load_state_dict
self.class.name, "\n\t".join(error_msgs)))
RuntimeError: Error(s) in loading state_dict for VisTR:
Missing key(s) in state_dict: "transformer.encoder.layers.3.self_attn.in_proj_weight", "transformer.encoder.layers.3.self_attn.in_proj_bias", "transformer.encoder.layers.3.self_attn.out_proj.weight", "transformer.encoder.layers.3.self_attn.out_proj.bias", "transformer.encoder.layers.3.linear1.weight", "transformer.encoder.layers.3.linear1.bias", "transformer.encoder.layers.3.linear2.weight", "transformer.encoder.layers.3.linear2.bias", "transformer.encoder.layers.3.norm1.weight", "transformer.encoder.layers.3.norm1.bias", "transformer.encoder.layers.3.norm2.weight", "transformer.encoder.layers.3.norm2.bias", "transformer.encoder.layers.4.self_attn.in_proj_weight", "transformer.encoder.layers.4.self_attn.in_proj_bias", "transformer.encoder.layers.4.self_attn.out_proj.weight", "transformer.encoder.layers.4.self_attn.out_proj.bias", "transformer.encoder.layers.4.linear1.weight", "transformer.encoder.layers.4.linear1.bias", "transformer.encoder.layers.4.linear2.weight", "transformer.encoder.layers.4.linear2.bias", "transformer.encoder.layers.4.norm1.weight", "transformer.encoder.layers.4.norm1.bias", "transformer.encoder.layers.4.norm2.weight", "transformer.encoder.layers.4.norm2.bias", "transformer.encoder.layers.5.self_attn.in_proj_weight", "transformer.encoder.layers.5.self_attn.in_proj_bias", "transformer.encoder.layers.5.self_attn.out_proj.weight", "transformer.encoder.layers.5.self_attn.out_proj.bias", "transformer.encoder.layers.5.linear1.weight", "transformer.encoder.layers.5.linear1.bias", "transformer.encoder.layers.5.linear2.weight", "transformer.encoder.layers.5.linear2.bias", "transformer.encoder.layers.5.norm1.weight", "transformer.encoder.layers.5.norm1.bias", "transformer.encoder.layers.5.norm2.weight", "transformer.encoder.layers.5.norm2.bias", "transformer.decoder.layers.3.self_attn.in_proj_weight", "transformer.decoder.layers.3.self_attn.in_proj_bias", "transformer.decoder.layers.3.self_attn.out_proj.weight", "transformer.decoder.layers.3.self_attn.out_proj.bias", "transformer.decoder.layers.3.multihead_attn.in_proj_weight", "transformer.decoder.layers.3.multihead_attn.in_proj_bias", "transformer.decoder.layers.3.multihead_attn.out_proj.weight", "transformer.decoder.layers.3.multihead_attn.out_proj.bias", "transformer.decoder.layers.3.linear1.weight", "transformer.decoder.layers.3.linear1.bias", "transformer.decoder.layers.3.linear2.weight", "transformer.decoder.layers.3.linear2.bias", "transformer.decoder.layers.3.norm1.weight", "transformer.decoder.layers.3.norm1.bias", "transformer.decoder.layers.3.norm2.weight", "transformer.decoder.layers.3.norm2.bias", "transformer.decoder.layers.3.norm3.weight", "transformer.decoder.layers.3.norm3.bias", "transformer.decoder.layers.4.self_attn.in_proj_weight", "transformer.decoder.layers.4.self_attn.in_proj_bias", "transformer.decoder.layers.4.self_attn.out_proj.weight", "transformer.decoder.layers.4.self_attn.out_proj.bias", "transformer.decoder.layers.4.multihead_attn.in_proj_weight", "transformer.decoder.layers.4.multihead_attn.in_proj_bias", "transformer.decoder.layers.4.multihead_attn.out_proj.weight", "transformer.decoder.layers.4.multihead_attn.out_proj.bias", "transformer.decoder.layers.4.linear1.weight", "transformer.decoder.layers.4.linear1.bias", "transformer.decoder.layers.4.linear2.weight", "transformer.decoder.layers.4.linear2.bias", "transformer.decoder.layers.4.norm1.weight", "transformer.decoder.layers.4.norm1.bias", "transformer.decoder.layers.4.norm2.weight", "transformer.decoder.layers.4.norm2.bias", "transformer.decoder.layers.4.norm3.weight", "transformer.decoder.layers.4.norm3.bias", "transformer.decoder.layers.5.self_attn.in_proj_weight", "transformer.decoder.layers.5.self_attn.in_proj_bias", "transformer.decoder.layers.5.self_attn.out_proj.weight", "transformer.decoder.layers.5.self_attn.out_proj.bias", "transformer.decoder.layers.5.multihead_attn.in_proj_weight", "transformer.decoder.layers.5.multihead_attn.in_proj_bias", "transformer.decoder.layers.5.multihead_attn.out_proj.weight", "transformer.decoder.layers.5.multihead_attn.out_proj.bias", "transformer.decoder.layers.5.linear1.weight", "transformer.decoder.layers.5.linear1.bias", "transformer.decoder.layers.5.linear2.weight", "transformer.decoder.layers.5.linear2.bias", "transformer.decoder.layers.5.norm1.weight", "transformer.decoder.layers.5.norm1.bias", "transformer.decoder.layers.5.norm2.weight", "transformer.decoder.layers.5.norm2.bias", "transformer.decoder.layers.5.norm3.weight", "transformer.decoder.layers.5.norm3.bias".

I have used default DeformConv2d from the torchvision in segmentation.py at the time of training

from torchvision.ops import DeformConv2d as DeformConv

[Epiphqny]

@OmkarThawakar You have missed --masks

[OmkarThawakar]

Thanks @Epiphqny , It's resolved now.