I also have the same problem.
In nengo_dl, there is no problem, but the question is how to do it in nengo core?
In nengo Core, if you want to do off-line learning, you use nengo.solver to solve the decoder.
conn = nengo.Connection(input_neuron,
Here eval_points is your training data, function is you label. then you can solve the connection weights(decoder).
My question is, can we here first load the pre-trained weights, then the nengo solver solve the optimization problem.