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Description
Hi team,
First of all, thank you for sharing this great work.
I'm currently trying to run inference using the imdy_pretrain.pt checkpoint provided in the repository. I followed the expected procedure by initializing the model from models/IDFD_mkr.py and loading the config file from config/IDFD_mkr.yml.
However, I encountered several issues during the process:
1. Missing Config Keys
The config file is missing several required keys under the transformer section, such as:
dimnum_headnum_layersnorm
I was able to resolve this by adding them manually based on how they're used in the model definition, but I am not sure if the values I used match the training configuration.
2. Shape Mismatch when Loading Weights
When calling:
model.load_state_dict(ckpt['model_state'])I got the following error:
RuntimeError: Error(s) in loading state_dict for mkrIDFD:
size mismatch for ID_inProj.weight: copying a param with shape torch.Size([64, 36]) from checkpoint, the shape in current model is torch.Size([64, 72]).
size mismatch for ID_outProj.weight: copying a param with shape torch.Size([332, 64]) from checkpoint, the shape in current model is torch.Size([236, 64]).
size mismatch for ID_outProj.bias: copying a param with shape torch.Size([332]) from checkpoint, the shape in current model is torch.Size([236]).
size mismatch for FD_inProj.mkr_pre.weight: copying a param with shape torch.Size([64, 9]) from checkpoint, the shape in current model is torch.Size([64, 18]).
This suggests that either:
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The model structure changed since the checkpoint was created, or
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The config I used does not match the one used during training.
Could you please share the exact config file (YAML or other format) used to train the imdy_pretrain.pt checkpoint?
Additionally, a minimal working inference script or example input/output would be extremely helpful to ensure proper usage of the model and checkpoint.
Thanks again for your contribution to the community, and I appreciate your help!