issues.md

August 6, 2025 ยท View on GitHub

Issue with using VLABench

Issues with octo

Some experiences to create octo evaluation env:

    conda env remove -n octo
    conda create -n octo python=3.10
    conda activate octo
    pip install -e .
    pip install "jax[cuda12_pip]==0.4.20" -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html flax==0.7.5 
    pip install tensorflow==2.15.0 pip install dlimp@git+https://github.com/kvablack/dlimp@5edaa4691567873d495633f2708982b42edf1972 
    pip install distrax==0.1.5 
    pip install tensorflow_probability==0.23.0 
    pip install scipy==1.12.0 
    pip install einops==0.6.1
    pip install transformers==4.34.1 
    pip install ml_collections==0.1.0 
    pip install wandb==0.12.14 
    pip install matplotlib 
    pip install gym==0.26 
    pip install plotly==5.16.1
    pip install orbax-checkpoint==0.4.0

Note: Line 5 "cuda12_pip" may be replaced by other proper version according to your machine. Refer to jax installation.

Make sure jax version=0.4.20 and flax version=0.7.5

pip show jax flax jaxlib

Run this to verify installation successful

python -c "from octo.model.octo_model import OctoModel; model = OctoModel.load_pretrained('hf://rail-berkeley/octo-base-1.5'); print('Model loaded successfully')"

Failed to run VLABench on a headless server

To use the headless mode of MUJOCO, set the environment variable MUJOCO_GL=egl.

Please also make sure some neccessary libraries are successfully installed:

sudo apt-get install mesa-utils  
sudo apt-get install libglu1-mesa  
sudo apt-get install libgl1-mesa-dri  
sudo apt-get install libgl1-mesa-glx

Issues about rlds generation

  1. The error: got unexpected key file_format Please refer to https://github.com/kpertsch/rlds_dataset_mod/issues/3

  2. ValueError: Could not load DatasetBuilder from: xxx. Make sure the module only contains a single `DatasetBuilder'. This issue is mainly because that the rlds relative environment lacks of some dependency packages. To check these packages, you can build a new python file and load the tfds.builder from the target file.

For example, the builder file named primitive.py and the builder class is Primitive.

import tensorflow_datasets as tfds
from primitive import *

builder= Primitive()

Then the python will report the packages your environment doesn't have.

Issues about Lerobot Version.

The lerobot conversion script is accomplished by referencing the openpi implementation. The openpi codebase VLABench used is openpi. Make sure the libary datasets==3.2.0 when converting hdf5/rlds to lerobot format. Otherwise, there will be some incompatible problems.

Issues about Inverse Kinematics

When evaluating policies, you may encouter a warning like
"WARNING:absl:Failed to converge after 99 steps: err_norm=0.0868166". This is not a bug, but rather a failure of the inverse kinematics solution caused by the robotic arm exceeding its working limits due to unreasonable model outputs.