Comments (2)
slerman12
commented on June 20, 2024
I also get this error when I add model as an argument in that same README example:
AttributeError: 'Parameter' object has no attribute 'grad1'
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slerman12
commented on June 20, 2024
Oh I think it's because my model consists of submodules:
Model(
(torso): MLP(
(model): Sequential(
(0): Linear(in_features=5, out_features=64, bias=True)
(1): Tanh()
(2): Linear(in_features=64, out_features=64, bias=True)
(3): Tanh()
)
)
(head): DetachedScaleGaussian(
(loc_layer): Sequential(
(0): Linear(in_features=64, out_features=1, bias=True)
(1): Tanh()
)
)
)
Any idea what I can do?
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Related Issues (13)
- Replace module backward hook with tensor hook
- UserWarning: Using a non-full backward hook when the forward contains multiple autograd Nodes is deprecated and will be removed in future versions. This hook will be missing some grad_input. Please use register_full_backward_hook to get the documented behavior. HOT 3
- Imprecision?
- Extend to support Conv1d and Conv3d HOT 1
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- Autograd_Hacks for multiple GPU usage HOT 1
- ResNet support HOT 3
- Support of padding, dilation and stride in compute_grad1 function
- A One-Line Bug That Could be Easily Fixed HOT 1
- Can compute_grad1 support multiple backprops?
- RuntimeError: grad can be implicitly created only for scalar outputs HOT 1
- RuntimeError: grad can be implicitly created only for scalar outputs
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