Segmentation fault (core dumped) while running in docker container

(mimex) root@a7fb20a782e2:/docker_local_test/mimex-pixmc# python tools/train.py task=FrankaReachSparsePixels expl_cfg=expl_l5 expl_cfg.k_expl=0.5
Importing module ‘gym_37’ (/docker_local_test/mimex-pixmc/IsaacGym_Preview_4_Package/isaacgym/python/isaacgym/_bindings/linux-x86_64/gym_37.so)
Setting GYM_USD_PLUG_INFO_PATH to /docker_local_test/mimex-pixmc/IsaacGym_Preview_4_Package/isaacgym/python/isaacgym/_bindings/linux-x86_64/usd/plugInfo.json
PyTorch version 1.13.1+cu117
Device count 1
/docker_local_test/mimex-pixmc/IsaacGym_Preview_4_Package/isaacgym/python/isaacgym/_bindings/src/gymtorch
Using /root/.cache/torch_extensions/py37_cu117 as PyTorch extensions root…
Emitting ninja build file /root/.cache/torch_extensions/py37_cu117/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…
tools/train.py:67: UserWarning:
The version_base parameter is not specified.
Please specify a compatability version level, or None.
Will assume defaults for version 1.1
@hydra.main(config_name=“config”, config_path=“…/configs”)
/opt/anaconda/envs/mimex/lib/python3.7/site-packages/hydra/_internal/defaults_list.py:251: UserWarning: In ‘config’: Defaults list is missing _self_. See Changes to default composition order | Hydra for more information
warnings.warn(msg, UserWarning)
/opt/anaconda/envs/mimex/lib/python3.7/site-packages/hydra/_internal/defaults_list.py:415: UserWarning: In config: Invalid overriding of hydra/job_logging:
Default list overrides requires ‘override’ keyword.
See Defaults List Overrides | Hydra for more information.

deprecation_warning(msg)
/opt/anaconda/envs/mimex/lib/python3.7/site-packages/hydra/_internal/hydra.py:127: UserWarning: Future Hydra versions will no longer change working directory at job runtime by default.
See Changes to job's runtime working directory | Hydra for more information.
configure_logging=with_log_configuration,
LOGDIR ===> /docker_local_test/mimex-pixmc/exp/FrankaReachSparse_2024-03-19_02:25:07_l5_k0.5_mr0.7_s0
task:
name: FrankaReach
env:
numEnvs: 512
envSpacing: 1.5
episodeLength: 200
goal_pos_init: [0.55, 0.0, 0.7]
goal_pos_delta: [0.2, 0.3, 0.2]
obs_type: pixels
im_size: 224
cam:
crop: center
w: 298
h: 224
fov: 120
ss: 2
loc_p: [0.04, 0.0, 0.045]
loc_r: [180, -90.0, 0.0]
dofVelocityScale: 0.1
actionScale: 7.5
goalDistRewardScale: 0.0
goalBonusRewardScale: 0.4
actionPenaltyScale: 0.01
asset:
assetRoot: assets
assetFileNameFranka: urdf/franka_description/robots/franka_panda.urdf
sim:
substeps: 1
physx:
num_threads: 4
solver_type: 1
num_position_iterations: 12
num_velocity_iterations: 1
contact_offset: 0.005
rest_offset: 0.0
bounce_threshold_velocity: 0.2
max_depenetration_velocity: 1000.0
default_buffer_size_multiplier: 5.0
always_use_articulations: False
task:
randomize: False
train:
seed: 0
torch_deterministic: False
clip_observations: 5.0
clip_actions: 1.0
encoder:
model_type: maevit-s16
pretrain_dir: /docker_local_test/mimex-pixmc/tmp/pretrained
pretrain_type: hoi
freeze: True
emb_dim: 128
policy:
pi_hid_sizes: [256, 128, 64]
vf_hid_sizes: [256, 128, 64]
learn:
agent_name: franka_ppo
test: False
resume: 0
save_interval: 50
print_log: True
max_iterations: 500
cliprange: 0.1
ent_coef: 0
nsteps: 32
noptepochs: 10
nminibatches: 4
max_grad_norm: 1
optim_stepsize: 0.001
schedule: cos
gamma: 0.99
lam: 0.95
init_noise_std: 1.0
log_interval: 1
expl_cfg:
baseline: none
input_type: obs_feat
expl_seq_len: 5
k_expl: 0.5
anneal_k: False
mask_ratio: 0.7
mask_all: False
n_mask: 1
norm_loss: False
use_cls: True
use_actor_feat: False
bert_lr: 0.0001
embed_dim: 128
decoder_embed_dim: 64
decoder_num_heads: 2
decoder_depth: 1
use_my_ratio: False
physics_engine: physx
pipeline: gpu
sim_device: cuda:0
rl_device: cuda:0
graphics_device_id: 0
num_gpus: 1
test: False
resume: 0
logdir: /docker_local_test/mimex-pixmc/exp/FrankaReachSparse_2024-03-19_02:25:07_l5_k0.5_mr0.7_s0
cptdir:
headless: True
exp_name: exp
exp: t
wandb_mode: disabled
save_latest_video: False
action_noise_cfg:
type: learned
schedule: linear(1.0,0.1,16000)
Wrote config to: /docker_local_test/mimex-pixmc/exp/FrankaReachSparse_2024-03-19_02:25:07_l5_k0.5_mr0.7_s0/config.yaml
Setting seed: 0
Setting sim options
Not connected to PVD
+++ Using GPU PhysX
Physics Engine: PhysX
Physics Device: cuda:0
GPU Pipeline: enabled
Segmentation fault (core dumped)

I am unable to run the Issac Gym library inside the Docker container and also reported an error after installing Vulkan:
[Error] [card. gmm. plugin] Failed to create Nvf device in createNvfGraphics Please make sure Vulkan is correctly installed

Has anyone successfully run issacgym in Docker? My experience shows that issaggym cannot run in Docker containers
My Docker environment and host are both Ubuntu 18.04. The CUDA version of the host is 12.1, the NVIDIA driver version is 530.41.03, and the NVIDIA GeForce RTX 3090