Error in train.py

[zqs010908]

Thank you for providing the code.
I am trying to use train.by to train my model，but I encountered the following issue while using train.py

Traceback (most recent call last):
File "/home/iiau-vln/ws_zqs/nomad/visualnav-transformer/train/train.py", line 402, in
main(config)
File "/home/iiau-vln/ws_zqs/nomad/visualnav-transformer/train/train.py", line 326, in main
train_eval_loop_nomad(
File "/home/iiau-vln/ws_zqs/nomad/visualnav-transformer/train/vint_train/training/train_eval_loop.py", line 196, in train_eval_loop_nomad
ema_model = EMAModel(model=model,power=0.75)
TypeError: init() missing 1 required positional argument: 'parameters'

Traceback (most recent call last):
File "/home/iiau-vln/ws_zqs/nomad/visualnav-transformer/train/train.py", line 402, in
main(config)
File "/home/iiau-vln/ws_zqs/nomad/visualnav-transformer/train/train.py", line 326, in main
train_eval_loop_nomad(
File "/home/iiau-vln/ws_zqs/nomad/visualnav-transformer/train/vint_train/training/train_eval_loop.py", line 203, in train_eval_loop_nomad
train_nomad(
File "/home/iiau-vln/ws_zqs/nomad/visualnav-transformer/train/vint_train/training/train_utils.py", line 661, in train_nomad
loss.backward()
File "/home/iiau-vln/miniconda3/envs/nomad/lib/python3.8/site-packages/torch/_tensor.py", line 522, in backward
torch.autograd.backward(
File "/home/iiau-vln/miniconda3/envs/nomad/lib/python3.8/site-packages/torch/autograd/init.py", line 266, in backward
Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
RuntimeError: element 0 of tensors does not require grad and does not have a grad_fn

[zolmaeng]

Try using EMAModel(model.parameters(), power=0.75) instead of EMAModel(model, power=0.75).

[robodhruv]

Thanks @zolmaeng! Does that fix the problem, @zqs010908 ?
We also welcome PRs with reproducible bug reports :)

This seems like an issue for other users too, tracking it at #30

[zqs010908]

I have already used EMAModel(model.parameters(), power=0.75)，but a new problem has arisen

/home/iiau-vln/miniconda3/envs/nomad/lib/python3.8/site-packages/diffusers/training_utils.py:361: FutureWarning: Passing a torch.nn.Module to ExponentialMovingAverage.step is deprecated. Please pass the parameters of the module instead.
deprecate(
Traceback (most recent call last):
File "/home/iiau-vln/ws_zqs/nomad/ori_nomad/visualnav-transformer/train/train.py", line 402, in
main(config)
File "/home/iiau-vln/ws_zqs/nomad/ori_nomad/visualnav-transformer/train/train.py", line 326, in main
train_eval_loop_nomad(
File "/home/iiau-vln/ws_zqs/nomad/ori_nomad/visualnav-transformer/train/vint_train/training/train_eval_loop.py", line 203, in train_eval_loop_nomad
train_nomad(
File "/home/iiau-vln/ws_zqs/nomad/ori_nomad/visualnav-transformer/train/vint_train/training/train_utils.py", line 676, in train_nomad
ema_model.averaged_model,
AttributeError: 'EMAModel' object has no attribute 'averaged_model'

I found that the EMAModel class in diffusers.training_utils indeed does not have the averaged_model object. I see that the EMAModel in diffusion_policy has the averaged_model object, as referenced in line 31 of ema_model.py. I'm not sure if this method is correct.

[zqs010908]

And after I used the EMAModel in diffusion_policy, I found that it solved the previous problem, but now a new issue has arisen. I am using the config from nomad and training with the SACSoN/HuRoN dataset. Have you encountered this issue before?
Traceback (most recent call last):
File "/home/iiau-vln/ws_zqs/nomad/visualnav-transformer/train/train.py", line 402, in
main(config)
File "/home/iiau-vln/ws_zqs/nomad/visualnav-transformer/train/train.py", line 326, in main
train_eval_loop_nomad(
File "/home/iiau-vln/ws_zqs/nomad/visualnav-transformer/train/vint_train/training/train_eval_loop.py", line 203, in train_eval_loop_nomad
train_nomad(
File "/home/iiau-vln/ws_zqs/nomad/visualnav-transformer/train/vint_train/training/train_utils.py", line 860, in train_nomad
loss.backward()
File "/home/iiau-vln/miniconda3/envs/nomad/lib/python3.8/site-packages/torch/_tensor.py", line 522, in backward
torch.autograd.backward(
File "/home/iiau-vln/miniconda3/envs/nomad/lib/python3.8/site-packages/torch/autograd/init.py", line 266, in backward
Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
RuntimeError: element 0 of tensors does not require grad and does not have a grad_fn

[keshav0306]

Change line 31 of the file ema_model.py in diffusion_policy/diffusion_policy/model/diffusion/ from
self.averaged_model = model to self.averaged_model = copy.deepcopy(model)