error with animal model

[kcamnairb]

Hi,

I'm trying out both models from mirDNN with fungi. I was able to run the animal model successfully but the plant model gives this error:
python3 ~/bin/mirDNN/mirdnn_eval.py -i test.fold -o plant.csv -m ~/bin/mirDNN/models/plants.pmt -s 160 -d "cpu" Traceback (most recent call last): File "/home/brian/bin/mirDNN/mirdnn_eval.py", line 32, in <module> main(sys.argv[1:]) File "/home/brian/bin/mirDNN/mirdnn_eval.py", line 16, in main model.load(pp.model_file) File "/home/brian/bin/mirDNN/src/model.py", line 75, in load self.load_state_dict(tr.load(model_file, map_location=lambda storage, loc: storage)) File "/home/brian/mambaforge/envs/mirdnn_env/lib/python3.11/site-packages/torch/nn/modules/module.py", line 2041, in load_state_dict raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format( RuntimeError: Error(s) in loading state_dict for mirDNN: Missing key(s) in state_dict: "conv_layers.18.weight", "conv_layers.18.bias", "conv_layers.18.running_mean", "conv_layers.18.running_var". Unexpected key(s) in state_dict: "conv_layers.19.layers.1.weight", "conv_layers.19.layers.1.bias", "conv_layers.19.layers.1.running_mean", "conv_layers.19.layers.1.running_var", "conv_layers.19.layers.1.num_batches_tracked", "conv_layers.19.layers.2.weight", "conv_layers.19.layers.2.bias", "conv_layers.19.layers.4.weight", "conv_layers.19.layers.4.bias", "conv_layers.19.layers.4.running_mean", "conv_layers.19.layers.4.running_var", "conv_layers.19.layers.4.num_batches_tracked", "conv_layers.19.layers.5.weight", "conv_layers.19.layers.5.bias", "conv_layers.22.weight", "conv_layers.22.bias", "conv_layers.22.running_mean", "conv_layers.22.running_var", "conv_layers.22.num_batches_tracked", "conv_layers.17.layers.1.weight", "conv_layers.17.layers.1.bias", "conv_layers.17.layers.1.running_mean", "conv_layers.17.layers.1.running_var", "conv_layers.17.layers.1.num_batches_tracked", "conv_layers.17.layers.2.weight", "conv_layers.17.layers.2.bias", "conv_layers.17.layers.4.weight", "conv_layers.17.layers.4.bias", "conv_layers.17.layers.4.running_mean", "conv_layers.17.layers.4.running_var", "conv_layers.17.layers.4.num_batches_tracked", "conv_layers.17.layers.5.weight", "conv_layers.17.layers.5.bias", "conv_layers.18.layers.1.weight", "conv_layers.18.layers.1.bias", "conv_layers.18.layers.1.running_mean", "conv_layers.18.layers.1.running_var", "conv_layers.18.layers.1.num_batches_tracked", "conv_layers.18.layers.2.weight", "conv_layers.18.layers.2.bias", "conv_layers.18.layers.4.weight", "conv_layers.18.layers.4.bias", "conv_layers.18.layers.4.running_mean", "conv_layers.18.layers.4.running_var", "conv_layers.18.layers.4.num_batches_tracked", "conv_layers.18.layers.5.weight", "conv_layers.18.layers.5.bias".