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unmannedlab / RELLIS-3D

RELLIS-3D: A Multi-modal Dataset for Off-Road Robotics
https://unmannedlab.github.io/research/RELLIS-3D
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How to load trained SalsaNext model for inference #11

Closed SvenMuc closed 3 years ago

SvenMuc commented 3 years ago

Hello, I'm currently trying to load your pretrained model for inference.

print("Initialize SalsaNext model...")
number_classes = 15      # read from yaml config file in my code
model = SalsaNext(number_classes)

print("Load model checkpoint...")
checkpoint = torch.load(FLAGS.trained_model)
model.load_state_dict(checkpoint['state_dict'], strict=True)

This gives me the following error messages. 

Initialize SalsaNext model...
Load model checkpoint...
Traceback (most recent call last):
  File "/home/i009658/workspace/AI_EnvPerception/datasets/RELLIS-3D/benchmarks/SalsaNext/train/tasks/semantic/convert_pytorch_model_to_torch_script_model.py", line 91, in <module>
    model.load_state_dict(checkpoint['state_dict'], strict=True)
  File "/home/i009658/miniconda3/envs/salsanext/lib/python3.7/site-packages/torch/nn/modules/module.py", line 777, in load_state_dict
    self.__class__.__name__, "\n\t".join(error_msgs)))
RuntimeError: Error(s) in loading state_dict for SalsaNext:
    Missing key(s) in state_dict: "downCntx.conv1.weight", "downCntx.conv1.bias", "downCntx.conv2.weight", "downCntx.conv2.bias", "downCntx.bn1.weight", "downCntx.bn1.bias", "downCntx.bn1.running_mean", "downCntx.bn1.running_var", "downCntx.conv3.weight", "downCntx.conv3.bias", "downCntx.bn2.weight", "downCntx.bn2.bias", "downCntx.bn2.running_mean", "downCntx.bn2.running_var", "downCntx2.conv1.weight", "downCntx2.conv1.bias", "downCntx2.conv2.weight", "downCntx2.conv2.bias", "downCntx2.bn1.weight", "downCntx2.bn1.bias", "downCntx2.bn1.running_mean", "downCntx2.bn1.running_var", "downCntx2.conv3.weight", "downCntx2.conv3.bias", "downCntx2.bn2.weight", "downCntx2.bn2.bias", "downCntx2.bn2.running_mean", "downCntx2.bn2.running_var", "downCntx3.conv1.weight", "downCntx3.conv1.bias", "downCntx3.conv2.weight", "downCntx3.conv2.bias", "downCntx3.bn1.weight", "downCntx3.bn1.bias", "downCntx3.bn1.running_mean", "downCntx3.bn1.running_var", "downCntx3.conv3.weight", "downCntx3.conv3.bias", "downCntx3.bn2.weight", "downCntx3.bn2.bias", "downCntx3.bn2.running_mean", "downCntx3.bn2.running_var", "resBlock1.conv1.weight", "resBlock1.conv1.bias", "resBlock1.conv2.weight", "resBlock1.conv2.bias", "resBlock1.bn1.weight", "resBlock1.bn1.bias", "resBlock1.bn1.running_mean", "resBlock1.bn1.running_var", "resBlock1.conv3.weight", "resBlock1.conv3.bias", "resBlock1.bn2.weight", "resBlock1.bn2.bias", "resBlock1.bn2.running_mean", "resBlock1.bn2.running_var", "resBlock1.conv4.weight", "resBlock1.conv4.bias", "resBlock1.bn3.weight", "resBlock1.bn3.bias", "resBlock1.bn3.running_mean", "resBlock1.bn3.running_var", "resBlock1.conv5.weight", "resBlock1.conv5.bias", "resBlock1.bn4.weight", "resBlock1.bn4.bias", "resBlock1.bn4.running_mean", "resBlock1.bn4.running_var", "resBlock2.conv1.weight", "resBlock2.conv1.bias", "resBlock2.conv2.weight", "resBlock2.conv2.bias", "resBlock2.bn1.weight", "resBlock2.bn1.bias", "resBlock2.bn1.running_mean", "resBlock2.bn1.running_var", "resBlock2.conv3.weight", "resBlock2.conv3.bias", "resBlock2.bn2.weight", "resBlock2.bn2.bias", "resBlock2.bn2.running_mean", "resBlock2.bn2.running_var", "resBlock2.conv4.weight", "resBlock2.conv4.bias", "resBlock2.bn3.weight", "resBlock2.bn3.bias", "resBlock2.bn3.running_mean", "resBlock2.bn3.running_var", "resBlock2.conv5.weight", "resBlock2.conv5.bias", "resBlock2.bn4.weight", "resBlock2.bn4.bias", "resBlock2.bn4.running_mean", "resBlock2.bn4.running_var", "resBlock3.conv1.weight", "resBlock3.conv1.bias", "resBlock3.conv2.weight", "resBlock3.conv2.bias", "resBlock3.bn1.weight", "resBlock3.bn1.bias", "resBlock3.bn1.running_mean", "resBlock3.bn1.running_var", "resBlock3.conv3.weight", "resBlock3.conv3.bias", "resBlock3.bn2.weight", "resBlock3.bn2.bias", "resBlock3.bn2.running_mean", "resBlock3.bn2.running_var", "resBlock3.conv4.weight", "resBlock3.conv4.bias", "resBlock3.bn3.weight", "resBlock3.bn3.bias", "resBlock3.bn3.running_mean", "resBlock3.bn3.running_var", "resBlock3.conv5.weight", "resBlock3.conv5.bias", "resBlock3.bn4.weight", "resBlock3.bn4.bias", "resBlock3.bn4.running_mean", "resBlock3.bn4.running_var", "resBlock4.conv1.weight", "resBlock4.conv1.bias", "resBlock4.conv2.weight", "resBlock4.conv2.bias", "resBlock4.bn1.weight", "resBlock4.bn1.bias", "resBlock4.bn1.running_mean", "resBlock4.bn1.running_var", "resBlock4.conv3.weight", "resBlock4.conv3.bias", "resBlock4.bn2.weight", "resBlock4.bn2.bias", "resBlock4.bn2.running_mean", "resBlock4.bn2.running_var", "resBlock4.conv4.weight", "resBlock4.conv4.bias", "resBlock4.bn3.weight", "resBlock4.bn3.bias", "resBlock4.bn3.running_mean", "resBlock4.bn3.running_var", "resBlock4.conv5.weight", "resBlock4.conv5.bias", "resBlock4.bn4.weight", "resBlock4.bn4.bias", "resBlock4.bn4.running_mean", "resBlock4.bn4.running_var", "resBlock5.conv1.weight", "resBlock5.conv1.bias", "resBlock5.conv2.weight", "resBlock5.conv2.bias", "resBlock5.bn1.weight", "resBlock5.bn1.bias", "resBlock5.bn1.running_mean", "resBlock5.bn1.running_vLoad model checkpoint...
Traceback (most recent call last):
  File "/home/i009658/workspace/AI_EnvPerception/datasets/RELLIS-3D/benchmarks/SalsaNext/train/tasks/semantic/convert_pytorch_model_to_torch_script_model.py", line 91, in <module>
    model.load_state_dict(checkpoint['state_dict'], strict=True)
  File "/home/i009658/miniconda3/envs/salsanext/lib/python3.7/site-packages/torch/nn/modules/module.py", line 777, in load_state_dict
    self.__class__.__name__, "\n\t".join(error_msgs)))
RuntimeError: Error(s) in loading state_dict for SalsaNext:
    Missing key(s) in state_dict: "downCntx.conv1.weight", "downCntx.conv1.bias", "downCntx.conv2.weight", "downCntx.conv2.bias", "downCntx.bn1.weight", "downCntx.bn1.bias", "downCntx.bn1.running_mean", "downCntx.bn1.running_var", "downCntx.conv3.weight", "downCntx.conv3.bias", "downCntx.bn2.weight", "downCntx.bn2.bias", "downCntx.bn2.running_mean", "downCntx.bn2.running_var", "downCntx2.conv1.weight", "downCntx2.conv1.bias", "downCntx2.conv2.weight", "downCntx2.conv2.bias", "downCntx2.bn1.weight", "downCntx2.bn1.bias", "downCntx2.bn1.running_mean", "downCntx2.bn1.running_var", "downCntx2.conv3.weight", "downCntx2.conv3.bias", "downCntx2.bn2.weight", "downCntx2.bn2.bias", "downCntx2.bn2.running_mean", "downCntx2.bn2.running_var", "downCntx3.conv1.weight", "downCntx3.conv1.bias", "downCntx3.conv2.weight", "downCntx3.conv2.bias", "downCntx3.bn1.weight", "downCntx3.bn1.bias", "downCntx3.bn1.running_mean", "downCntx3.bn1.running_var", "downCntx3.conv3.weight", "downCntx3.conv3.bias", "downCntx3.bn2.weight", "downCntx3.bn2.bias", "downCntx3.bn2.running_mean", "downCntx3.bn2.running_var", "resBlock1.conv1.weight", "resBlock1.conv1.bias", "resBlock1.conv2.weight", "resBlock1.conv2.bias", "resBlock1.bn1.weight", "resBlock1.bn1.bias", "resBlock1.bn1.running_mean", "resBlock1.bn1.running_var", "resBlock1.conv3.weight", "resBlock1.conv3.bias", "resBlock1.bn2.weight", "resBlock1.bn2.bias", "resBlock1.bn2.running_mean", "resBlock1.bn2.running_var", "resBlock1.conv4.weight", "resBlock1.conv4.bias", "resBlock1.bn3.weight", "resBlock1.bn3.bias", "resBlock1.bn3.running_mean", "resBlock1.bn3.running_var", "resBlock1.conv5.weight", "resBlock1.conv5.bias", "resBlock1.bn4.weight", "resBlock1.bn4.bias", "resBlock1.bn4.running_mean", "resBlock1.bn4.running_var", "resBlock2.conv1.weight", "resBlock2.conv1.bias", "resBlock2.conv2.weight", "resBlock2.conv2.bias", "resBlock2.bn1.weight", "resBlock2.bn1.bias", "resBlock2.bn1.running_mean", "resBlock2.bn1.running_var", "resBlock2.conv3.weight", "resBlock2.conv3.bias", "resBlock2.bn2.weight", "resBlock2.bn2.bias", "resBlock2.bn2.running_mean", "resBlock2.bn2.running_var", "resBlock2.conv4.weight", "resBlock2.conv4.bias", "resBlock2.bn3.weight", "resBlock2.bn3.bias", "resBlock2.bn3.running_mean", "resBlock2.bn3.running_var", "resBlock2.conv5.weight", "resBlock2.conv5.bias", "resBlock2.bn4.weight", "resBlock2.bn4.bias", "resBlock2.bn4.running_mean", "resBlock2.bn4.running_var", "resBlock3.conv1.weight", "resBlock3.conv1.bias", "resBlock3.conv2.weight", "resBlock3.conv2.bias", "resBlock3.bn1.weight", "resBlock3.bn1.bias", "resBlock3.bn1.running_mean", "resBlock3.bn1.running_var", "resBlock3.conv3.weight", "resBlock3.conv3.bias", "resBlock3.bn2.weight", "resBlock3.bn2.bias", "resBlock3.bn2.running_mean", "resBlock3.bn2.running_var", "resBlock3.conv4.weight", "resBlock3.conv4.bias", "resBlock3.bn3.weight", "resBlock3.bn3.bias", "resBlock3.bn3.running_mean", "resBlock3.bn3.running_var", "resBlock3.conv5.weight", "resBlock3.conv5.bias", "resBlock3.bn4.weight", "resBlock3.bn4.bias", "resBlock3.bn4.running_mean", "resBlock3.bn4.running_var", "resBlock4.conv1.weight", "resBlock4.conv1.bias", "resBlock4.conv2.weight", "resBlock4.conv2.bias", "resBlock4.bn1.weight", "resBlock4.bn1.bias", "resBlock4.bn1.running_mean", "resBlock4.bn1.running_var", "resBlock4.conv3.weight", "resBlock4.conv3.bias", "resBlock4.bn2.weight", "resBlock4.bn2.bias", "resBlock4.bn2.running_mean", "resBlock4.bn2.running_var", "resBlock4.conv4.weight", "resBlock4.conv4.bias", "resBlock4.bn3.weight", "resBlock4.bn3.bias", "resBlock4.bn3.running_mean", "resBlock4.bn3.running_var", "resBlock4.conv5.weight", "resBlock4.conv5.bias", "resBlock4.bn4.weight", "resBlock4.bn4.bias", "resBlock4.bn4.running_mean", "resBlock4.bn4.running_var", "resBlock5.conv1.weight", "resBlock5.conv1.bias", "resBlock5.conv2.weight", "resBlock5.conv2.bias", "resBlock5.bn1.weight", "resBlock5.bn1.bias", "resBlock5.bn1.running_mean", "resBlock5.bn1.running_var", "resBlock5.conv3.weight", "resBlock5.conv3.bias", "resBlock5.bn2.weight", "resBlock5.bn2.bias", "resBlock5.bn2.running_mean", "resBlock5.bn2.running_var", "resBlock5.conv4.weight", "resBlock5.conv4.bias", "resBlock5.bn3.weight", "resBlock5.bn3.bias", "resBlock5.bn3.running_mean", "resBlock5.bn3.running_var", "resBlock5.conv5.weight", "resBlock5.conv5.bias", "resBlock5.bn4.weight", "resBlock5.bn4.bias", "resBlock5.bn4.running_mean", "resBlock5.bn4.running_var", "upBlock1.conv1.weight", "upBlock1.conv1.bias", "upBlock1.bn1.weight", "upBlock1.bn1.bias", "upBlock1.bn1.running_mean", "upBlock1.bn1.running_var", "upBlock1.conv2.weight", "upBlock1.conv2.bias", "upBlock1.bn2.weight", "upBlock1.bn2.bias", "upBlock1.bn2.running_mean", "upBlock1.bn2.running_var", "upBlock1.conv3.weight", "upBlock1.conv3.bias", "upBlock1.bn3.weight", "upBlock1.bn3.bias", "upBlock1.bn3.running_mean", "upBlock1.bn3.running_var", "upBlock1.conv4.weight", "upBlock1.conv4.bias", "upBlock1.bn4.weight", "upBlock1.bn4.bias", "upBlock1.bn4.running_mean", "upBlock1.bn4.running_var", "upBlock2.conv1.weight", "upBlock2.conv1.bias", "upBlock2.bn1.weight", "upBlock2.bn1.bias", "upBlock2.bn1.running_mean", "upBlock2.bn1.running_var", "upBlock2.conv2.weight", "upBlock2.conv2.bias", "upBlock2.bn2.weight", "upBlock2.bn2.bias", "upBlock2.bn2.running_mean", "upBlock2.bn2.running_var", "upBlock2.conv3.weight", "upBlock2.conv3.bias", "upBlock2.bn3.weight", "upBlock2.bn3.bias", "upBlock2.bn3.running_mean", "upBlock2.bn3.running_var", "upBlock2.conv4.weight", "upBlock2.conv4.bias", "upBlock2.bn4.weight", "upBlock2.bn4.bias", "upBlock2.bn4.running_mean", "upBlock2.bn4.running_var", "upBlock3.conv1.weight", "upBlock3.conv1.bias", "upBlock3.bn1.weight", "upBlock3.bn1.bias", "upBlock3.bn1.running_mean", "upBlock3.bn1.running_var", "upBlock3.conv2.weight", "upBlock3.conv2.bias", "upBlock3.bn2.weight", "upBlock3.bn2.bias", "upBlock3.bn2.running_mean", "upBlock3.bn2.running_var", "upBlock3.conv3.weight", "upBlock3.conv3.bias", "upBlock3.bn3.weight", "upBlock3.bn3.bias", "upBlock3.bn3.running_mean", "upBlock3.bn3.running_var", "upBlock3.conv4.weight", "upBlock3.conv4.bias", "upBlock3.bn4.weight", "upBlock3.bn4.bias", "upBlock3.bn4.running_mean", "upBlock3.bn4.running_var", "upBlock4.conv1.weight", "upBlock4.conv1.bias", "upBlock4.bn1.weight", "upBlock4.bn1.bias", "upBlock4.bn1.running_mean", "upBlock4.bn1.running_var", "upBlock4.conv2.weight", "upBlock4.conv2.bias", "upBlock4.bn2.weight", "upBlock4.bn2.bias", "upBlock4.bn2.running_mean", "upBlock4.bn2.running_var", "upBlock4.conv3.weight", "upBlock4.conv3.bias", "upBlock4.bn3.weight", "upBlock4.bn3.bias", "upBlock4.bn3.running_mean", "upBlock4.bn3.running_var", "upBlock4.conv4.weight", "upBlock4.conv4.bias", "upBlock4.bn4.weight", "upBlock4.bn4.bias", "upBlock4.bn4.running_mean", "upBlock4.bn4.running_var", "logits.weight", "logits.bias". 
    Unexpected key(s) in state_dict: "module.downCntx.conv1.weight", "module.downCntx.conv1.bias", "module.downCntx.conv2.weight", "module.downCntx.conv2.bias", "module.downCntx.bn1.weight", "module.downCntx.bn1.bias", "module.downCntx.bn1.running_mean", "module.downCntx.bn1.running_var", "module.downCntx.bn1.num_batches_tracked", "module.downCntx.conv3.weight", "module.downCntx.conv3.bias", "module.downCntx.bn2.weight", "module.downCntx.bn2.bias", "module.downCntx.bn2.running_mean", "module.downCntx.bn2.running_var", "module.downCntx.bn2.num_batches_tracked", "module.downCntx2.conv1.weight", "module.downCntx2.conv1.bias", "module.downCntx2.conv2.weight", "module.downCntx2.conv2.bias", "module.downCntx2.bn1.weight", "module.downCntx2.bn1.bias", "module.downCntx2.bn1.running_mean", "module.downCntx2.bn1.running_var", "module.downCntx2.bn1.num_batches_tracked", "module.downCntx2.conv3.weight", "module.downCntx2.conv3.bias", "module.downCntx2.bn2.weight", "module.downCntx2.bn2.bias", "module.downCntx2.bn2.running_mean", "module.downCntx2.bn2.running_var", "module.downCntx2.bn2.num_batches_tracked", "module.downCntx3.conv1.weight", "module.downCntx3.conv1.bias", "module.downCntx3.conv2.weight", "module.downCntx3.conv2.bias", "module.downCntx3.bn1.weight", "module.downCntx3.bn1.bias", "module.downCntx3.bn1.running_mean", "module.downCntx3.bn1.running_var", "module.downCntx3.bn1.num_batches_tracked", "module.downCntx3.conv3.weight", "module.downCntx3.conv3.bias", "module.downCntx3.bn2.weight", "module.downCntx3.bn2.bias", "module.downCntx3.bn2.running_mean", "module.downCntx3.bn2.running_var", "module.downCntx3.bn2.num_batches_tracked", "module.resBlock1.conv1.weight", "module.resBlock1.conv1.bias", "module.resBlock1.conv2.weight", "module.resBlock1.conv2.bias", "module.resBlock1.bn1.weight", "module.resBlock1.bn1.bias", "module.resBlock1.bn1.running_mean", "module.resBlock1.bn1.running_var", "module.resBlock1.bn1.num_batches_tracked", "module.resBlock1.conv3.weight", "module.resBlock1.conv3.bias", "module.resBlock1.bn2.weight", "module.resBlock1.bn2.bias", "module.resBlock1.bn2.running_mean", "module.resBlock1.bn2.running_var", "module.resBlock1.bn2.num_batches_tracked", "module.resBlock1.conv4.weight", "module.resBlock1.conv4.bias", "module.resBlock1.bn3.weight", "module.resBlock1.bn3.bias", "module.resBlock1.bn3.running_mean", "module.resBlock1.bn3.running_var", "module.resBlock1.bn3.num_batches_tracked", "module.resBlock1.conv5.weight", "module.resBlock1.conv5.bias", "module.resBlock1.bn4.weight", "module.resBlock1.bn4.bias", "module.resBlock1.bn4.running_mean", "module.resBlock1.bn4.running_var", "module.resBlock1.bn4.num_batches_tracked", "module.resBlock2.conv1.weight", "module.resBlock2.conv1.bias", "module.resBlock2.conv2.weight", "module.resBlock2.conv2.bias", "module.resBlock2.bn1.weight", "module.resBlock2.bn1.bias", "module.resBlock2.bn1.running_mean", "module.resBlock2.bn1.running_var", "module.resBlock2.bn1.num_batches_tracked", "module.resBlock2.conv3.weight", "module.resBlock2.conv3.bias", "module.resBlock2.bn2.weight", "module.resBlock2.bn2.bias", "module.resBlock2.bn2.running_mean", "module.resBlock2.bn2.running_var", "module.resBlock2.bn2.num_batches_tracked", "module.resBlock2.conv4.weight", "module.resBlock2.conv4.bias", "module.resBlock2.bn3.weight", "module.resBlock2.bn3.bias", "module.resBlock2.bn3.running_mean", "module.resBlock2.bn3.running_var", "module.resBlock2.bn3.num_batches_tracked", "module.resBlock2.conv5.weight", "module.resBlock2.conv5.bias", "module.resBlock2.bn4.weight", "module.resBlock2.bn4.bias", "module.resBlock2.bn4.running_mean", "module.resBlock2.bn4.running_var", "module.resBlock2.bn4.num_batches_tracked", "module.resBlock3.conv1.weight", "module.resBlock3.conv1.bias", "module.resBlock3.conv2.weight", "module.resBlock3.conv2.bias", "module.resBlock3.bn1.weight", "module.resBlock3.bn1.bias", "module.resBlock3.bn1.running_mean", "module.resBlock3.bn1.running_var", "module.resBlock3.bn1.num_batches_tracked", "module.resBlock3.conv3.weight", "module.resBlock3.conv3.bias", "module.resBlock3.bn2.weight", "module.resBlock3.bn2.bias", "module.resBlock3.bn2.running_mean", "module.resBlock3.bn2.running_var", "module.resBlock3.bn2.num_batches_tracked", "module.resBlock3.conv4.weight", "module.resBlock3.conv4.bias", "module.resBlock3.bn3.weight", "module.resBlock3.bn3.bias", "module.resBlock3.bn3.running_mean", "module.resBlock3.bn3.running_var", "module.resBlock3.bn3.num_batches_tracked", "module.resBlock3.conv5.weight", "module.resBlock3.conv5.bias", "module.resBlock3.bn4.weight", "module.resBlock3.bn4.bias", "module.resBlock3.bn4.running_mean", "module.resBlock3.bn4.running_var", "module.resBlock3.bn4.num_batches_tracked", "module.resBlock4.conv1.weight", "module.resBlock4.conv1.bias", "module.resBlock4.conv2.weight", "module.resBlock4.conv2.bias", "module.resBlock4.bn1.weight", "module.resBlock4.bn1.bias", "module.resBlock4.bn1.running_mean", "module.resBlock4.bn1.running_var", "module.resBlock4.bn1.num_batches_tracked", "module.resBlock4.conv3.weight", "module.resBlock4.conv3.bias", "module.resBlock4.bn2.weight", "module.resBlock4.bn2.bias", "module.resBlock4.bn2.running_mean", "module.resBlock4.bn2.running_var", "module.resBlock4.bn2.num_batches_tracked", "module.resBlock4.conv4.weight", "module.resBlock4.conv4.bias", "module.resBlock4.bn3.weight", "module.resBlock4.bn3.bias", "module.resBlock4.bn3.running_mean", "module.resBlock4.bn3.running_var", "module.resBlock4.bn3.num_batches_tracked", "module.resBlock4.conv5.weight", "module.resBlock4.conv5.bias", "module.resBlock4.bn4.weight", "module.resBlock4.bn4.bias", "module.resBlock4.bn4.running_mean", "module.resBlock4.bn4.running_var", "module.resBlock4.bn4.num_batches_tracked", "module.resBlock5.conv1.weight", "module.resBlock5.conv1.bias", "module.resBlock5.conv2.weight", "module.resBlock5.conv2.bias", "module.resBlock5.bn1.weight", "module.resBlock5.bn1.bias", "module.resBlock5.bn1.running_mean", "module.resBlock5.bn1.running_var", "module.resBlock5.bn1.num_batches_tracked", "module.resBlock5.conv3.weight", "module.resBlock5.conv3.bias", "module.resBlock5.bn2.weight", "module.resBlock5.bn2.bias", "module.resBlock5.bn2.running_mean", "module.resBlock5.bn2.running_var", "module.resBlock5.bn2.num_batches_tracked", "module.resBlock5.conv4.weight", "module.resBlock5.conv4.bias", "module.resBlock5.bn3.weight", "module.resBlock5.bn3.bias", "module.resBlock5.bn3.running_mean", "module.resBlock5.bn3.running_var", "module.resBlock5.bn3.num_batches_tracked", "module.resBlock5.conv5.weight", "module.resBlock5.conv5.bias", "module.resBlock5.bn4.weight", "module.resBlock5.bn4.bias", "module.resBlock5.bn4.running_mean", "module.resBlock5.bn4.running_var", "module.resBlock5.bn4.num_batches_tracked", "module.upBlock1.conv1.weight", "module.upBlock1.conv1.bias", "module.upBlock1.bn1.weight", "module.upBlock1.bn1.bias", "module.upBlock1.bn1.running_mean", 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Process finished with exit code 1ar", "resBlock5.conv3.weight", "resBlock5.conv3.bias", "resBlock5.bn2.weight", "resBlock5.bn2.bias", "resBlock5.bn2.running_mean", "resBlock5.bn2.running_var", "resBlock5.conv4.weight", "resBlock5.conv4.bias", "resBlock5.bn3.weight", "resBlock5.bn3.bias", "resBlock5.bn3.running_mean", "resBlock5.bn3.running_var", "resBlock5.conv5.weight", "resBlock5.conv5.bias", "resBlock5.bn4.weight", "resBlock5.bn4.bias", "resBlock5.bn4.running_mean", "resBlock5.bn4.running_var", "upBlock1.conv1.weight", "upBlock1.conv1.bias", "upBlock1.bn1.weight", "upBlock1.bn1.bias", "upBlock1.bn1.running_mean", "upBlock1.bn1.running_var", "upBlock1.conv2.weight", "upBlock1.conv2.bias", "upBlock1.bn2.weight", "upBlock1.bn2.bias", "upBlock1.bn2.running_mean", "upBlock1.bn2.running_var", "upBlock1.conv3.weight", "upBlock1.conv3.bias", "upBlock1.bn3.weight", "upBlock1.bn3.bias", "upBlock1.bn3.running_mean", "upBlock1.bn3.running_var", "upBlock1.conv4.weight", "upBlock1.conv4.bias", "upBlock1.bn4.weight", "upBlock1.bn4.bias", "upBlock1.bn4.running_mean", "upBlock1.bn4.running_var", "upBlock2.conv1.weight", "upBlock2.conv1.bias", "upBlock2.bn1.weight", "upBlock2.bn1.bias", "upBlock2.bn1.running_mean", "upBlock2.bn1.running_var", "upBlock2.conv2.weight", "upBlock2.conv2.bias", "upBlock2.bn2.weight", "upBlock2.bn2.bias", "upBlock2.bn2.running_mean", "upBlock2.bn2.running_var", "upBlock2.conv3.weight", "upBlock2.conv3.bias", "upBlock2.bn3.weight", "upBlock2.bn3.bias", "upBlock2.bn3.running_mean", "upBlock2.bn3.running_var", "upBlock2.conv4.weight", "upBlock2.conv4.bias", "upBlock2.bn4.weight", "upBlock2.bn4.bias", "upBlock2.bn4.running_mean", "upBlock2.bn4.running_var", "upBlock3.conv1.weight", "upBlock3.conv1.bias", "upBlock3.bn1.weight", "upBlock3.bn1.bias", "upBlock3.bn1.running_mean", "upBlock3.bn1.running_var", "upBlock3.conv2.weight", "upBlock3.conv2.bias", "upBlock3.bn2.weight", "upBlock3.bn2.bias", "upBlock3.bn2.running_mean", "upBlock3.bn2.running_var", "upBlock3.conv3.weight", "upBlock3.conv3.bias", "upBlock3.bn3.weight", "upBlock3.bn3.bias", "upBlock3.bn3.running_mean", "upBlock3.bn3.running_var", "upBlock3.conv4.weight", "upBlock3.conv4.bias", "upBlock3.bn4.weight", "upBlock3.bn4.bias", "upBlock3.bn4.running_mean", "upBlock3.bn4.running_var", "upBlock4.conv1.weight", "upBlock4.conv1.bias", "upBlock4.bn1.weight", "upBlock4.bn1.bias", "upBlock4.bn1.running_mean", "upBlock4.bn1.running_var", "upBlock4.conv2.weight", "upBlock4.conv2.bias", "upBlock4.bn2.weight", "upBlock4.bn2.bias", "upBlock4.bn2.running_mean", "upBlock4.bn2.running_var", "upBlock4.conv3.weight", "upBlock4.conv3.bias", "upBlock4.bn3.weight", "upBlock4.bn3.bias", "upBlock4.bn3.running_mean", "upBlock4.bn3.running_var", "upBlock4.conv4.weight", "upBlock4.conv4.bias", "upBlock4.bn4.weight", "upBlock4.bn4.bias", "upBlock4.bn4.running_mean", "upBlock4.bn4.running_var", "logits.weight", "logits.bias". 
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Process finished with exit code 1

Did you save all required parameters during training? Or is there something wrong with my code? Thanks for some feedback.

Sven

SvenMuc commented 3 years ago

Short update. In the meanwhile I also tried the code from the trainer.py script. I got the same errors.

model = SalsaNext(self.parser.get_n_classes())
...
torch.nn.Module.dump_patches = True
w_dict = torch.load(FLAGS.trained_model, map_location=lambda storage, loc: storage)
maskjp commented 3 years ago

@SvenMuc ,

Did you try this script?

SvenMuc commented 3 years ago

I solved it. I had some conflicts with the installed cuda and pytorch libraries.