Closed asaran closed 4 years ago
v1.4 models are for data-efficient Rainbow, so you will need to run with --architecture data-efficient --hidden-size 256
, but v1.3 models should work with the default hyperparameters. Could you please confirm?
Thanks for your reply. v1.4 models work as expected with the additional arguments, however v1.3 models still complain with default hyperparameters:
Traceback (most recent call last):
File "main.py", line 82, in
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]).