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Bug when running nuplan_planner_tutorial.ipynb
Describe the bug
Hi, I am running the basic tutorial: nuplan_planner_tutorial.ipynb
.
When running to the cell where main_simulation(cfg, planner)
is called, I got some errors as follows.
ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (2,) + inhomogeneous part.
Rendering histograms: 0it [00:00, ?it/s]
I checked the error. It seems that when creating StateVector2D
the argument x
is in list
type instead of float
type.
It causes the error when using a list to initialize np.array
.
Setup
Ubuntu20.04, 64g ram
Steps To Reproduce
Just follow the documentation and install nuplan, and then run this .ipynb
Stack Trace
Traceback (most recent call last):
File "/home/shady/data/nuplan-devkit/nuplan/planning/simulation/runner/executor.py", line 27, in run_simulation
return sim_runner.run() # type: ignore
File "/home/shady/data/nuplan-devkit/nuplan/planning/simulation/runner/simulations_runner.py", line 134, in run
trajectories = self.planner.compute_trajectory(planner_inputs)
File "/home/shady/data/nuplan-devkit/nuplan/planning/simulation/planner/abstract_planner.py", line 124, in compute_trajectory
raise e
File "/home/shady/data/nuplan-devkit/nuplan/planning/simulation/planner/abstract_planner.py", line 121, in compute_trajectory
trajectory = self.compute_planner_trajectory(current_input)
File "/home/shady/data/nuplan-devkit/my_test/_test_script.py", line 95, in compute_planner_trajectory
state = self.motion_model.propagate_state(state, state.dynamic_car_state, self.sampling_time)
File "/home/shady/data/nuplan-devkit/nuplan/planning/simulation/controller/motion_model/kinematic_bicycle.py", line 98, in propagate_state
propagating_state = self._update_commands(state, ideal_dynamic_state, sampling_time)
File "/home/shady/data/nuplan-devkit/nuplan/planning/simulation/controller/motion_model/kinematic_bicycle.py", line 82, in _update_commands
rear_axle_acceleration_2d=StateVector2D(updated_accel, 0),
File "/home/shady/data/nuplan-devkit/nuplan/common/actor_state/state_representation.py", line 292, in __init__
self.array = np.array([self.x, self.y], dtype=np.float64)
ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (2,) + inhomogeneous part.
Rendering histograms: 0it [00:00, ?it/s]
Screenshots
Additional context
N/A
I solved the issue by integrating #214. Maybe this helps you.
@K3vwho Thank you!
BTW, I found when using +simulation=closed_loop_reactive_agents
for run_simulatioin.py
, there are similar shape related bugs in idm_agent_manager
, which causes the shapely.Polygon
construction error.
For reproducing it, run:
python run_simulation.py \
+simulation=closed_loop_nonreactive_agents \
scenario_filter.limit_total_scenarios=1 \
planner=simple_planner \
worker=sequential
Yes, I also have the same issue when using idm_planner
or +simulation=closed_loop_reactive_agents
. I didn't solve the issue yet. If you found any solution, would be nice if you can share it.
PS: I think you meant +simulation=closed_loop_reactive_agents
in your reproduction example.
I found that the construction error is caused by shapely==2.0.0, if you use an earlier version e.g. 1.8.4, it's solved. But the a new error occurs in the strtree_occupancy_map.py
. I didn't manage to solve the key error yet, do you have any suggestions?
Hi all,
We have addressed this issue in the next release. The issue comes from the update to shapely >=2.0 and some interfaces have changed. Thank you for your patience
Hi! I got the same problem when i was running "nuplan_planner_tutorial.ipynb". I have changed the shapely to 1.8.4, but didn't work.
ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (2,) + inhomogeneous part. Rendering histograms: 0it [00:00, ?it/s]
do you have any suggestions? Thanks
@HITXCI just change the branch to nuplan-devkit-v1.1 and install everything accordingly.
@K3vwho Thanks for your suggenstion! But it's still not working.