louiskirsch / metagenrl

MetaGenRL, a novel meta reinforcement learning algorithm. Unlike prior work, MetaGenRL can generalize to new environments that are entirely different from those used for meta-training.
66 stars 13 forks source link

ValueError: too many values to unpack #7

Open sumwailiu opened 1 year ago

sumwailiu commented 1 year ago

Traceback (most recent call last): File "/home/sumwailiu/miniconda3/envs/tf115/lib/python3.7/site-packages/ray/tune/trial_runner.py", line 515, in _process_trial result = self.trial_executor.fetch_result(trial) File "/home/sumwailiu/miniconda3/envs/tf115/lib/python3.7/site-packages/ray/tune/ray_trial_executor.py", line 351, in fetch_result result = ray.get(trial_future[0]) File "/home/sumwailiu/miniconda3/envs/tf115/lib/python3.7/site-packages/ray/worker.py", line 2121, in get raise value.as_instanceof_cause() ray.exceptions.RayTaskError(ValueError): ray_worker (pid=1296, host=bc53eb4c8015) File "/home/sumwailiu/miniconda3/envs/tf115/lib/python3.7/site-packages/ray/tune/trainable.py", line 176, in train result = self._train() File "/home/sumwailiu/MetaGenRL/ray_experiments.py", line 115, in _train interaction_lengths, shortest_episodes, rewards = zip(*ray.get(simulation_objs)) ray.exceptions.RayTaskError(ValueError): ray_worker (pid=1297, host=bc53eb4c8015) File "/home/sumwailiu/MetaGenRL/ray_workers.py", line 384, in simulate ep_len, episode_reward, taken_actions = simulate_episode() File "/home/sumwailiu/MetaGenRL/ray_workers.py", line 362, in simulate_episode newobs, r, d, = env.step(a) ValueError: too many values to unpack (expected 4)

==== Here are the versions of my installed packages. Package Version

absl-py 1.4.0 ale-py 0.8.1 astor 0.8.1 async-timeout 4.0.2 attrs 23.1.0 box2d-py 2.3.5 certifi 2023.5.7 cffi 1.15.1 charset-normalizer 3.1.0 click 8.1.3 cloudpickle 2.2.1 colorama 0.4.6 cycler 0.11.0 Cython 0.29.34 decorator 4.4.2 exceptiongroup 1.1.1 fasteners 0.18 filelock 3.12.0 fonttools 4.38.0 funcsigs 1.0.2 gast 0.2.2 glfw 2.5.9 google-pasta 0.2.0 grpcio 1.54.2 gym 0.26.2 gym-notices 0.0.8 h5py 2.10.0 idna 3.4 imageio 2.28.1 imageio-ffmpeg 0.4.8 importlib-metadata 6.6.0 importlib-resources 5.12.0 iniconfig 2.0.0 jsonschema 4.17.3 Keras-Applications 1.0.8 Keras-Preprocessing 1.1.2 kiwisolver 1.4.4 lz4 4.3.2 Markdown 3.4.3 MarkupSafe 2.1.2 matplotlib 3.5.3 moviepy 1.0.3 mujoco 2.1.2 mujoco-py 2.0.2.8 numpy 1.18.5 opencv-python 4.7.0.72 opt-einsum 3.3.0 packaging 23.1 Pillow 9.5.0 pip 23.1.2 pkgutil_resolve_name 1.3.10 pluggy 1.0.0 proglog 0.1.10 protobuf 3.14.0 psutil 5.9.5 py 1.11.0 pyarrow 0.13.0 pycparser 2.21 pygame 2.1.0 PyOpenGL 3.1.6 pyparsing 3.0.9 pyrsistent 0.19.3 pytest 7.0.1 python-dateutil 2.8.2 PyYAML 6.0 ray 0.7.6 redis 4.5.5 requests 2.30.0 scipy 1.7.1 setuptools 67.7.2 six 1.16.0 swig 4.1.1 tensorboard 1.15.0 tensorflow-estimator 1.15.1 tensorflow-gpu 1.15.5 termcolor 2.3.0 tomli 2.0.1 tqdm 4.65.0 typing_extensions 4.5.0 urllib3 2.0.2 Werkzeug 2.2.3 wheel 0.40.0 wrapt 1.15.0 zipp 3.15.0

louiskirsch commented 1 year ago

You are using a too new version of gym I believe. Try these:

absl-py==0.9.0
astor==0.8.1
atari-py==0.2.6
attrs==19.3.0
box2d-py==2.3.8
cachetools==4.0.0
certifi==2019.11.28
cffi==1.13.2
chardet==3.0.4
Click==7.0
cloudpickle==1.2.2
colorama==0.4.3
Cython==0.29.14
fasteners==0.15
filelock==3.0.12
funcsigs==1.0.2
future==0.18.2
gast==0.2.2
glfw==1.9.0
google-auth==1.10.0
google-auth-oauthlib==0.4.1
google-pasta==0.1.8
grpcio==1.26.0
gym==0.15.4
h5py==2.10.0
idna==2.8
imageio==2.6.1
importlib-metadata==1.3.0
jsonschema==3.2.0
Keras-Applications==1.0.8
Keras-Preprocessing==1.1.0
lockfile==0.12.2
Markdown==3.1.1
monotonic==1.5
more-itertools==8.0.2
mujoco-py==2.0.2.9
numpy==1.18.0
oauthlib==3.1.0
opencv-python==4.1.2.30
opt-einsum==3.1.0
packaging==19.2
Pillow==7.0.0
pluggy==0.13.1
protobuf==3.11.2
py==1.8.1
pyasn1==0.4.8
pyasn1-modules==0.2.7
pycparser==2.19
pyglet==1.3.2
pyparsing==2.4.6
pyrsistent==0.15.6
pytest==5.3.2
PyYAML==5.2
ray==0.7.6
redis==3.3.11
requests==2.22.0
requests-oauthlib==1.3.0
rsa==4.0
scipy==1.4.1
six==1.13.0
tabulate==0.8.6
tensorboard==1.14.0
tensorflow-estimator==1.14.0
tensorflow-gpu==1.14.0
termcolor==1.1.0
urllib3==1.25.7
wcwidth==0.1.8
Werkzeug==0.16.0
wrapt==1.11.2
zipp==0.6.0