TypeError: PinholeCameraPatternCfg.__init__() got an unexpected keyword argument 'fov'

[MrigaankMouli]

I am trynig to train a GO2 using rl_mjlab as follows:
python3 scripts/train.py Mjlab-Velocity-Flat-Unitree-Go2 --env.scene.num-envs=4096

But I get the following error:

Traceback (most recent call last):
  File "/media/ok/ubuntu/Quadruped_Projects/legged_rl/mjlab_trial/unitree_rl_mjlab/scripts/train.py", line 15, in <module>
    from mjlab.tasks.registry import list_tasks, load_env_cfg, load_rl_cfg, load_runner_cls
  File "/media/ok/ubuntu/Quadruped_Projects/legged_rl/unitree_rl_mjx/mjlab/tasks/__init__.py", line 5, in <module>
    import_packages(__name__, _BLACKLIST_PKGS)
  File "/media/ok/ubuntu/Quadruped_Projects/legged_rl/unitree_rl_mjx/mjlab/utils/lab_api/tasks/importer.py", line 40, in import_packages
    for _ in _walk_packages(
             ^^^^^^^^^^^^^^^
  File "/media/ok/ubuntu/Quadruped_Projects/legged_rl/unitree_rl_mjx/mjlab/utils/lab_api/tasks/importer.py", line 89, in _walk_packages
    yield from _walk_packages(path, info.name + ".", onerror, blacklist_pkgs)
  File "/media/ok/ubuntu/Quadruped_Projects/legged_rl/unitree_rl_mjx/mjlab/utils/lab_api/tasks/importer.py", line 89, in _walk_packages
    yield from _walk_packages(path, info.name + ".", onerror, blacklist_pkgs)
  File "/media/ok/ubuntu/Quadruped_Projects/legged_rl/unitree_rl_mjx/mjlab/utils/lab_api/tasks/importer.py", line 77, in _walk_packages
    __import__(info.name)
  File "/media/ok/ubuntu/Quadruped_Projects/legged_rl/unitree_rl_mjx/mjlab/tasks/velocity/config/go2/__init__.py", line 12, in <module>
    env_cfg=unitree_go2_rough_env_cfg(),
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/media/ok/ubuntu/Quadruped_Projects/legged_rl/unitree_rl_mjx/mjlab/tasks/velocity/config/go2/env_cfgs.py", line 64, in unitree_go2_rough_env_cfg
    pattern=PinholeCameraPatternCfg(
            ^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: PinholeCameraPatternCfg.__init__() got an unexpected keyword argument 'fov'
> ```

[klavier1127]

I’m not entirely sure what is causing this issue. It might be related to an inconsistent or unclean training environment (for example, mixed versions of mjlab or dependencies).

I would recommend creating a clean environment and reinstalling the dependencies, then trying to run the training again.