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After running the a1_jump-virtual train, I tried to play the result. However, I got a error saying that operands could not be broadcast together with shapes (593,464,2) (592,464,2) . The details are as follows:
.../parkour/legged_gym$ python legged_gym/scripts/play.py --task a1_jump --load_run Nov26_17-29-57_Skills_jump_virtual_fromNov24_09-41-36
Importing module 'gym_38' (/home/pdj/parkour_env/isaacgym/python/isaacgym/_bindings/linux-x86_64/gym_38.so)
Setting GYM_USD_PLUG_INFO_PATH to /home/pdj/parkour_env/isaacgym/python/isaacgym/_bindings/linux-x86_64/usd/plugInfo.json
PyTorch version 1.10.0+cu113
Device count 1
/home/pdj/parkour_env/isaacgym/python/isaacgym/_bindings/src/gymtorch
Using /home/pdj/.cache/torch_extensions/py38_cu113 as PyTorch extensions root...
Emitting ninja build file /home/pdj/.cache/torch_extensions/py38_cu113/gymtorch/build.ninja...
Building extension module gymtorch...
Allowing ninja to set a default number of workers... (overridable by setting the environment variable MAX_JOBS=N)
ninja: no work to do.
Loading extension module gymtorch...
Setting seed: 1
Using LeggedRobotField.__init__, num_obs and num_privileged_obs will be computed instead of assigned.
Not connected to PVD
+++ Using GPU PhysX
Physics Engine: PhysX
Physics Device: cuda:0
GPU Pipeline: enabled
Traceback (most recent call last):
File "legged_gym/scripts/play.py", line 341, in <module>
play(args)
File "/home/pdj/anaconda3/envs/parkour_env38/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 28, in decorate_context
return func(*args, **kwargs)
File "legged_gym/scripts/play.py", line 165, in play
env, _ = task_registry.make_env(name=args.task, args=args, env_cfg=env_cfg)
File "/home/pdj/parkour_env/parkour/legged_gym/legged_gym/utils/task_registry.py", line 116, in make_env
env = task_class( cfg=env_cfg,
File "/home/pdj/parkour_env/parkour/legged_gym/legged_gym/envs/base/legged_robot_field.py", line 20, in __init__
super().__init__(cfg, sim_params, physics_engine, sim_device, headless)
File "/home/pdj/parkour_env/parkour/legged_gym/legged_gym/envs/base/legged_robot.py", line 72, in __init__
super().__init__(self.cfg, sim_params, physics_engine, sim_device, headless)
File "/home/pdj/parkour_env/parkour/legged_gym/legged_gym/envs/base/base_task.py", line 84, in __init__
self.create_sim()
File "/home/pdj/parkour_env/parkour/legged_gym/legged_gym/envs/base/legged_robot.py", line 265, in create_sim
self._create_terrain()
File "/home/pdj/parkour_env/parkour/legged_gym/legged_gym/envs/base/legged_robot_field.py", line 651, in _create_terrain
self.terrain.add_terrain_to_sim(self.gym, self.sim, self.device)
File "/home/pdj/parkour_env/parkour/legged_gym/legged_gym/utils/terrain/barrier_track.py", line 600, in add_terrain_to_sim
self.build_heightfield_raw()
File "/home/pdj/parkour_env/parkour/legged_gym/legged_gym/utils/terrain/barrier_track.py", line 444, in build_heightfield_raw
heightfield_noise = TerrainPerlin.generate_fractal_noise_2d(
File "/home/pdj/parkour_env/parkour/legged_gym/legged_gym/utils/terrain/perlin.py", line 68, in generate_fractal_noise_2d
noise += amplitude * TerrainPerlin.generate_perlin_noise_2d((xSamples, ySamples), (xScale, yScale)) * zScale
File "/home/pdj/parkour_env/parkour/legged_gym/legged_gym/utils/terrain/perlin.py", line 49, in generate_perlin_noise_2d
n00 = np.sum(grid * g00, 2)
ValueError: operands could not be broadcast together with shapes (593,464,2) (592,464,2)
I also tried other skills like leap, crawl, tilt. The same problem happened with crawl while leap and tilt went well.
What should I do to fix it? Thanks!
The text was updated successfully, but these errors were encountered:
After running the
a1_jump-virtual
train, I tried to play the result. However, I got a error saying thatoperands could not be broadcast together with shapes (593,464,2) (592,464,2)
. The details are as follows:I also tried other skills like
leap, crawl, tilt
. The same problem happened withcrawl
whileleap
andtilt
went well.What should I do to fix it? Thanks!
The text was updated successfully, but these errors were encountered: