How severe does this issue affect your experience of using Ray?
- High: It blocks me to complete my task.
I have used Ray 2.0.0 to train a simple FCNet of 2 layers (256, 256) and store the result in a checkpoint. Later, I read in the checkpoint using
algo = ppo.PPO(config = config, env = env) algo.restore(path_to_checkpoint)
This works great to do inferences, although the network’s performance is so-so. However, if I train a model with 3 layers, e.g. [300, 128, 64], then the training works well, but restoring the checkpoint for inference results in the following error message:
ValueError: loaded state dict contains a parameter group that doesn't match the size of optimizer's group.
I feel like there’s a config item that I should be setting for the optimizer, or something, but don’t find any guidance in the Ray docs. I would be grateful to anyone who can provide some guidance.