Segmentation fault (core dumped)

[sondv2]

environment:
Ubuntu 18.04
GPU 1 card 1080ti
When i run python network.py and got error:

Traceback (most recent call last):
File "network.py", line 62, in
int8_calibrator=int8_calibrator
File "/home/xxx/anaconda3/envs/tensorrtserver/lib/python3.6/site-packages/trtis-0.1.0-py3.6.egg/trtis/trt_backend/torch2trt.py", line 126, in torch2trt
File "/home/xxx/anaconda3/envs/tensorrtserver/lib/python3.6/site-packages/trtis-0.1.0-py3.6.egg/trtis/onnx_backend/torch2onnx.py", line 147, in torch2onnx
File "/home/xxx/anaconda3/envs/tensorrtserver/lib/python3.6/site-packages/torch/nn/modules/module.py", line 839, in load_state_dict
self.class.name, "\n\t".join(error_msgs)))
RuntimeError: Error(s) in loading state_dict for WrapperModel:
Missing key(s) in state_dict: "model.dla_up.ida_0.proj_1.0.weight", "model.dla_up.ida_0.proj_1.1.weight", "model.dla_up.ida_0.proj_1.1.bias", "model.dla_up.ida_0.proj_1.1.running_mean", "model.dla_up.ida_0.proj_1.1.running_var", "model.dla_up.ida_0.up_1.weight", "model.dla_up.ida_0.node_1.0.weight", "model.dla_up.ida_0.node_1.1.weight", "model.dla_up.ida_0.node_1.1.bias", "model.dla_up.ida_0.node_1.1.running_mean", "model.dla_up.ida_0.node_1.1.running_var", "model.dla_up.ida_1.proj_1.0.weight", "model.dla_up.ida_1.proj_1.1.weight", "model.dla_up.ida_1.proj_1.1.bias", "model.dla_up.ida_1.proj_1.1.running_mean", "model.dla_up.ida_1.proj_1.1.running_var", "model.dla_up.ida_1.up_1.weight", "model.dla_up.ida_1.proj_2.0.weight", "model.dla_up.ida_1.proj_2.1.weight", "model.dla_up.ida_1.proj_2.1.bias", "model.dla_up.ida_1.proj_2.1.running_mean", "model.dla_up.ida_1.proj_2.1.running_var", "model.dla_up.ida_1.up_2.weight", "model.dla_up.ida_1.node_1.0.weight", "model.dla_up.ida_1.node_1.1.weight", "model.dla_up.ida_1.node_1.1.bias", "model.dla_up.ida_1.node_1.1.running_mean", "model.dla_up.ida_1.node_1.1.running_var", "model.dla_up.ida_1.node_2.0.weight", "model.dla_up.ida_1.node_2.1.weight", "model.dla_up.ida_1.node_2.1.bias", "model.dla_up.ida_1.node_2.1.running_mean", "model.dla_up.ida_1.node_2.1.running_var", "model.dla_up.ida_2.proj_1.0.weight", "model.dla_up.ida_2.proj_1.1.weight", "model.dla_up.ida_2.proj_1.1.bias", "model.dla_up.ida_2.proj_1.1.running_mean", "model.dla_up.ida_2.proj_1.1.running_var", "model.dla_up.ida_2.up_1.weight", "model.dla_up.ida_2.proj_2.0.weight", "model.dla_up.ida_2.proj_2.1.weight", "model.dla_up.ida_2.proj_2.1.bias", "model.dla_up.ida_2.proj_2.1.running_mean", "model.dla_up.ida_2.proj_2.1.running_var", "model.dla_up.ida_2.up_2.weight", "model.dla_up.ida_2.proj_3.0.weight", "model.dla_up.ida_2.proj_3.1.weight", "model.dla_up.ida_2.proj_3.1.bias", "model.dla_up.ida_2.proj_3.1.running_mean", "model.dla_up.ida_2.proj_3.1.running_var", "model.dla_up.ida_2.up_3.weight", "model.dla_up.ida_2.node_1.0.weight", "model.dla_up.ida_2.node_1.1.weight", "model.dla_up.ida_2.node_1.1.bias", "model.dla_up.ida_2.node_1.1.running_mean", "model.dla_up.ida_2.node_1.1.running_var", "model.dla_up.ida_2.node_2.0.weight", "model.dla_up.ida_2.node_2.1.weight", "model.dla_up.ida_2.node_2.1.bias", "model.dla_up.ida_2.node_2.1.running_mean", "model.dla_up.ida_2.node_2.1.running_var", "model.dla_up.ida_2.node_3.0.weight", "model.dla_up.ida_2.node_3.1.weight", "model.dla_up.ida_2.node_3.1.bias", "model.dla_up.ida_2.node_3.1.running_mean", "model.dla_up.ida_2.node_3.1.running_var", "model.hm.0.weight", "model.hm.0.bias", "model.hm.2.weight", "model.hm.2.bias", "model.wh.0.weight", "model.wh.0.bias", "model.wh.2.weight", "model.wh.2.bias", "model.reg.0.weight", "model.reg.0.bias", "model.reg.2.weight", "model.reg.2.bias".

[layerism]

I think you have to modify a little bit in the torch2onnx.py to match the name in your pth file. The file is in backend/onnx_backend/torch2onnx.py. I didn't carefully handle the name in dla34, many authors will change the layer or re-define the module, it is painful to get each name of layer match.