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raise RuntimeError("Mismatch in shape: grad_output[" RuntimeError: Mismatch in shape: grad_output[0] has a shape of torch.Size([1]) and output[0] has a shape of torch.Size([]).
#73
Open
xxz-wow opened this issue
Aug 9, 2022
· 5 comments
deer
how to solve it?in the rl.py
autograd.backward(
[critic_loss] + losses,
[torch.ones(1).to(critic_loss.device)]*(1+len(losses)),
)
raise that problem
The text was updated successfully, but these errors were encountered:
deer how to solve it?in the rl.py autograd.backward( [critic_loss] + losses, [torch.ones(1).to(critic_loss.device)]*(1+len(losses)), ) raise that problem
---- Replied Message ----
| From | ***@***.***> |
| Date | 01/14/2023 20:45 |
| To | ***@***.***> |
| Cc | ***@***.***>***@***.***> |
| Subject | Re: [ChenRocks/fast_abs_rl] raise RuntimeError("Mismatch in shape: grad_output[" RuntimeError: Mismatch in shape: grad_output[0] has a shape of torch.Size([1]) and output[0] has a shape of torch.Size([]). (Issue #73) |
deer how to solve it?in the rl.py autograd.backward( [critic_loss] + losses, [torch.ones(1).to(critic_loss.device)]*(1+len(losses)), ) raise that problem
have you solve the problem ?
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deer how to solve it?in the rl.py autograd.backward( [critic_loss] + losses, [torch.ones(1).to(critic_loss.device)]*(1+len(losses)), ) raise that problem
deer
how to solve it?in the rl.py
autograd.backward(
[critic_loss] + losses,
[torch.ones(1).to(critic_loss.device)]*(1+len(losses)),
)
raise that problem
The text was updated successfully, but these errors were encountered: