Comments (7)
@zhixiongzh I am getting exactly the same problem. learn.py doesn't hover properly and just crashes. When I run singleagent.py, it gives this error:
File "C:\Users\Username\AppData\Roaming\Python\Python311\site-packages\torch\nn\modules\linear.py", line 96, in __init__
self.weight = Parameter(torch.empty((out_features, in_features), **factory_kwargs))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: empty() received an invalid combination of arguments - got (tuple, dtype=NoneType, device=NoneType), but expected one of:
* (tuple of ints size, *, tuple of names names, torch.memory_format memory_format, torch.dtype dtype, torch.layout layout, torch.device device, bool pin_memory, bool requires_grad)
* (tuple of ints size, *, torch.memory_format memory_format, Tensor out, torch.dtype dtype, torch.layout layout, torch.device device, bool pin_memory, bool requires_grad)
Any updates?
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@RibhavOjha I only run the code in learn.py
not the singleagent.py
. I also have not yet reproduced the result using the example
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@zhixiongzh are you also getting the same error as me for singleagent.py
?
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Hi @zhixiongzh and @RibhavOjha
to reproduce the work in the paper you should checkout branches master
or paper
(and I am aware that some of the 3rd party dependencies are hardly maintained/backward compatible, unfortunately).
The current main
/default branch is currently worked on to support SITL simulation and after that is done, I will re-introduce the learning examples (this time based on gymnasium
and sb3 2.0).
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I think you could get rid of this error :
File "C:\Users\Username\AppData\Roaming\Python\Python311\site-packages\torch\nn\modules\linear.py", line 96, in __init__
self.weight = Parameter(torch.empty((out_features, in_features), **factory_kwargs))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: empty() received an invalid combination of arguments - got (tuple, dtype=NoneType, device=NoneType), but expected one of:
* (tuple of ints size, *, tuple of names names, torch.memory_format memory_format, torch.dtype dtype, torch.layout layout, torch.device device, bool pin_memory, bool requires_grad)
* (tuple of ints size, *, torch.memory_format memory_format, Tensor out, torch.dtype dtype, torch.layout layout, torch.device device, bool pin_memory, bool requires_grad)
By changing the onpolicy_kwargs
in singleagent.py by this :
# onpolicy_kwargs = dict(activation_fn=torch.nn.ReLU,
# net_arch=[512, 512, dict(vf=[256, 128], pi=[256, 128])]
# ) # or None
onpolicy_kwargs = dict(activation_fn=torch.nn.ReLU,
net_arch=[512, 512, 256, 128]
) # or None
But I face the same difficulty to reproduce the results with ppo and 1D (identical input to all motors) with RPMs ("one_d_rpm")...
from gym-pybullet-drones.
Same. I continued to run the training for 1E10. It did not work.
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See #180 for the current status
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