Installation#

System Requirements#

  • OS: Linux x86_64 (required by the locked ManiSkill / SAPIEN stack; see pyproject.toml).

  • Python: >=3.9, <3.12.

  • CUDA driver: 11.8 or 12.x (driver must match your PyTorch CUDA build; uv sync --frozen picks the correct PyTorch wheel automatically).

  • OpenGL / Vulkan: SAPIEN uses the system GPU graphics stack for rendering; ensure your driver provides Vulkan loader libraries.

  • Disk: ~5 GB for the environment and SAPIEN assets; additional space for datasets (see Datasets).

Verify Installation#

Run the snippet below to confirm the package imports cleanly and the canonical VLA wrapper path can be created:

uv run python -c "
import gymnasium as gym
import mikasa_robo_suite.vla.memory_envs
from mikasa_robo_suite.vla.utils.apply_wrappers import apply_mikasa_vla_wrappers

env = gym.make('RememberColor3-VLA-v0', num_envs=1, obs_mode='rgb',
               control_mode='pd_ee_delta_pose', render_mode='all',
               sim_backend='gpu')
env = apply_mikasa_vla_wrappers(env, include_overlays=False)
obs, info = env.reset(seed=0)
print('OK')
env.close()
"

Expected output includes: OK

Legacy RL Version#

The default repository is moving to the VLA benchmark. The pip command below installs only the original RL benchmark release from PyPI; it does not include the VLA environments or this documentation. Use the mikasa-robo-rl branch or:

pip install mikasa-robo-suite==0.0.5

Note

If you run into errors during setup, check the FAQ and Troubleshooting page for common installation problems (uv environment conflicts, CUDA mismatches, missing submodules).