Hi,
If I train a model with one GPU (without nn.DataParallel), the parameter names in saved models are something like:
features.0.weight
If the model was initialized with nn.DataParallel, the saved parameter names have a prefix:
model.features.0.weight
While doing inference I only use one GPU so the model failed to load the latter model file because the parameter names are not matching. I am wondering why parameter names are prepend the prefix? Can I trim the prefix and still use the model?
Thanks.
Ming