Are the pretrained model files correct/linked to the correct commit? Tried running the evaluation with pretrained models of v1.3 and v1.4 but receiving a runtime error "Error(s) in loading state_dict for DQN"
Traceback (most recent call last):
File "main.py", line 82, in
dqn = Agent(args, env)
File "/home/akanksha/Documents/Rainbow/agent.py", line 24, in init
self.online_net.load_state_dict(torch.load(args.model, map_location='cpu'))
File "/home/akanksha/anaconda3/envs/rainbow/lib/python3.7/site-packages/torch/nn/modules/module.py", line 845, in load_state_dict
self.class.name, "\n\t".join(error_msgs)))
RuntimeError: Error(s) in loading state_dict for DQN:
Missing key(s) in state_dict: "convs.4.weight", "convs.4.bias".
size mismatch for convs.0.weight: copying a param with shape torch.Size([32, 4, 5, 5]) from checkpoint, the shape in current model is torch.Size([32, 4, 8, 8]).
size mismatch for convs.2.weight: copying a param with shape torch.Size([64, 32, 5, 5]) from checkpoint, the shape in current model is torch.Size([64, 32, 4, 4]).
size mismatch for fc_h_v.weight_mu: copying a param with shape torch.Size([256, 576]) from checkpoint, the shape in current model is torch.Size([512, 3136]).
size mismatch for fc_h_v.weight_sigma: copying a param with shape torch.Size([256, 576]) from checkpoint, the shape in current model is torch.Size([512, 3136]).
size mismatch for fc_h_v.bias_mu: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for fc_h_v.bias_sigma: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for fc_h_v.weight_epsilon: copying a param with shape torch.Size([256, 576]) from checkpoint, the shape in current model is torch.Size([512, 3136]).
size mismatch for fc_h_v.bias_epsilon: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for fc_h_a.weight_mu: copying a param with shape torch.Size([256, 576]) from checkpoint, the shape in current model is torch.Size([512, 3136]).
size mismatch for fc_h_a.weight_sigma: copying a param with shape torch.Size([256, 576]) from checkpoint, the shape in current model is torch.Size([512, 3136]).
size mismatch for fc_h_a.bias_mu: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for fc_h_a.bias_sigma: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for fc_h_a.weight_epsilon: copying a param with shape torch.Size([256, 576]) from checkpoint, the shape in current model is torch.Size([512, 3136]).
size mismatch for fc_h_a.bias_epsilon: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for fc_z_v.weight_mu: copying a param with shape torch.Size([51, 256]) from checkpoint, the shape in current model is torch.Size([51, 512]).
size mismatch for fc_z_v.weight_sigma: copying a param with shape torch.Size([51, 256]) from checkpoint, the shape in current model is torch.Size([51, 512]).
size mismatch for fc_z_v.weight_epsilon: copying a param with shape torch.Size([51, 256]) from checkpoint, the shape in current model is torch.Size([51, 512]).
size mismatch for fc_z_a.weight_mu: copying a param with shape torch.Size([918, 256]) from checkpoint, the shape in current model is torch.Size([306, 512]).
size mismatch for fc_z_a.weight_sigma: copying a param with shape torch.Size([918, 256]) from checkpoint, the shape in current model is torch.Size([306, 512]).
size mismatch for fc_z_a.bias_mu: copying a param with shape torch.Size([918]) from checkpoint, the shape in current model is torch.Size([306]).
size mismatch for fc_z_a.bias_sigma: copying a param with shape torch.Size([918]) from checkpoint, the shape in current model is torch.Size([306]).
size mismatch for fc_z_a.weight_epsilon: copying a param with shape torch.Size([918, 256]) from checkpoint, the shape in current model is torch.Size([306, 512]).
size mismatch for fc_z_a.bias_epsilon: copying a param with shape torch.Size([918]) from checkpoint, the shape in current model is torch.Size([306]).