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Hi,
I really like this feature in skrl which enables simultaneous deploying of agents (https://skrl.readthedocs.io/en/latest/intro/examples.html). However, it would be great if skrl for example can also load the .pth file trained with Isaac Gym Library(https://github.com/NVIDIA-Omniverse/IsaacGymEnvs) for benchmark purposes. Currently, one gets the following errors:
File "ppo_ant.py", line 135, in <module> models_ppo["policy"].load("./ant_best.pth") File "/home/user/skrl/skrl/models/torch/base.py", line 302, in load self.load_state_dict(torch.load(path)) File "/home/user/.local/lib/python3.6/site-packages/torch/nn/modules/module.py", line 1483, in load_state_dict self.__class__.__name__, "\n\t".join(error_msgs))) RuntimeError: Error(s) in loading state_dict for Policy: Missing key(s) in state_dict: "log_std_parameter", "net.0.weight", "net.0.bias", "net.2.weight", "net.2.bias", "net.4.weight", "net.4.bias", "net.6.weight", "net.6.bias". Unexpected key(s) in state_dict: "running_mean_std", "reward_mean_std", "model", "epoch", "optimizer", "frame", "last_mean_rewards", "env_state".
The text was updated successfully, but these errors were encountered:
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Hi,
I really like this feature in skrl which enables simultaneous deploying of agents (https://skrl.readthedocs.io/en/latest/intro/examples.html). However, it would be great if skrl for example can also load the .pth file trained with Isaac Gym Library(https://github.com/NVIDIA-Omniverse/IsaacGymEnvs) for benchmark purposes. Currently, one gets the following errors:
The text was updated successfully, but these errors were encountered: