validate.py causes segmentation fault about ngsim_env HOT 4 OPEN

@raunakbh92
Not sure what the reason for the segfault might be.
Any changes that need to be made in the gaussian_latent_var_gru_policy.py ?

UPDATE:

File "/home/asyin/R/rllab/hgail/hgail/policies/gaussian_latent_var_gru_policy.py", line 193, in get_action
return actions[0], {k: v[0] for k, v in agent_infos.items()}
KeyError: 0

AGENT_INFO
[('mean', array([[ 0.01187703, -0.02830665]], dtype=float32)), ('prev_action', array([[ 0., 0.]])), ('latent_info', {'latent': array([[1, 0, 0, 0]])}), ('log_std', array([[-0.67997968, -0.72506523]], dtype=float32)), ('latent', array([[1, 0, 0, 0]]))]

I fixed the inital KeyError:0 by changing the way the dictionary was created by removing the latent_info key.

However,
I still am getting this error,

signal (11): Segmentation fault
in expression starting at no file:0

Similar to the one mentioned in https://github.com/sisl/ngsim_env/blob/c34f2c4bd6bf2e089b69bddefb4283ef6829c042/docs/usingTrainedPolicy.md

But deleting PyCall cache from ~/.julia/complied/v1.1 didnt work. Should try reverting to 0.6 (if so how?) or are there any other solutions ?

Thanks

from ngsim_env.

@raks097 Hi man, have you solved this issue? So currently, you are only able to run training a policy?

from ngsim_env.

agent_infos: {'mean': array([[-0.36561757, -0.4166246 ]], dtype=float32), 'log_std': array([[0.01288844, 0.06403346]], dtype=float32), 'prev_action': array([[0., 0.]]), 'latent': array([[0, 1, 0, 0]]), 'latent_info': {'latent': array([[0, 1, 0, 0]])}}

change 'latent_info': {'latent': array([[0, 1, 0, 0]])} ---> 'latent_info': array([[0, 1, 0, 0]])

from ngsim_env.

python validate.py --n_proc 4 --exp_dir ../../data/experiments/NGSIM-gail/ --params_filename itr_1000.npz --random_seed 42

For example, if I have selected n_proc equal to 4 here, I met some errors that only some of the pid worked, one of them (say 2) might fail.
pid: 0 or 1 or 3 traj: 515 / 516 pid equal to 2 never showed again.

from ngsim_env.