Load checkpoint and train

I need to train a model that was saved in .params. I used this post but it works for inference and doesn’t train.

My code looks like:

sym, arg_params, aux_params = mx.model.load_checkpoint(
    prefix, 0)
# Dropping the loss from model
new_sym = sym.get_children()[0]
net = gluon.nn.SymbolBlock(outputs=new_sym, inputs=mx.sym.var("data"))
net.initialize(mx.init.Normal(0.002), ctx=ctx)

Then I define loss, optimizer etc. Everything works but the model weights won’t change.

Also when I replaced my model by a single conv layer, it works. So I guess something freezes my weights in the way I load my net.

Can you provide a small reproducible example?

There is also a tutorial on how to load and save a model with MXNet https://mxnet.incubator.apache.org/versions/master/tutorials/gluon/save_load_params.html