GPUs parameter doesn't seem to be working

When I try to run a basic MLCube passing the --gpus parameter, I get an error mlcube.errors.ConfigurationError: Unknown keys: ['--gpus']. Namespace = runner.

I've tried different ways of passing the parameter and value: --gpus="all", --gpus=all, --gpus all, --gpus=1, --gpus="1" just in case that would affect, but I get the same error regardless.

I also tried specifying the accelerator_count to different values but nothing changed.

Full traceback:

HelloWorld/data_preparator/mlcube % mlcube run --task=prepare --gpus="all" -Pdocker.build_strategy=always
Traceback (most recent call last):
  File "/Users/alejandroaristizabal/opt/anaconda3/envs/medperf/bin/mlcube", line 8, in <module>
    sys.exit(cli())
  File "/Users/alejandroaristizabal/opt/anaconda3/envs/medperf/lib/python3.9/site-packages/click/core.py", line 1130, in __call__
    return self.main(*args, **kwargs)
  File "/Users/alejandroaristizabal/opt/anaconda3/envs/medperf/lib/python3.9/site-packages/click/core.py", line 1055, in main
    rv = self.invoke(ctx)
  File "/Users/alejandroaristizabal/opt/anaconda3/envs/medperf/lib/python3.9/site-packages/click/core.py", line 1657, in invoke
    return _process_result(sub_ctx.command.invoke(sub_ctx))
  File "/Users/alejandroaristizabal/opt/anaconda3/envs/medperf/lib/python3.9/site-packages/click/core.py", line 1404, in invoke
    return ctx.invoke(self.callback, **ctx.params)
  File "/Users/alejandroaristizabal/opt/anaconda3/envs/medperf/lib/python3.9/site-packages/click/core.py", line 760, in invoke
    return __callback(*args, **kwargs)
  File "/Users/alejandroaristizabal/opt/anaconda3/envs/medperf/lib/python3.9/site-packages/click/decorators.py", line 26, in new_func
    return f(get_current_context(), *args, **kwargs)
  File "/Users/alejandroaristizabal/opt/anaconda3/envs/medperf/lib/python3.9/site-packages/mlcube/__main__.py", line 272, in run
    runner_cls, mlcube_config = parse_cli_args(
  File "/Users/alejandroaristizabal/opt/anaconda3/envs/medperf/lib/python3.9/site-packages/mlcube/cli.py", line 60, in parse_cli_args
    mlcube_config = MLCubeConfig.create_mlcube_config(
  File "/Users/alejandroaristizabal/opt/anaconda3/envs/medperf/lib/python3.9/site-packages/mlcube/config.py", line 158, in create_mlcube_config
    runner_cls.CONFIG.validate(mlcube_config)
  File "/Users/alejandroaristizabal/opt/anaconda3/envs/medperf/lib/python3.9/site-packages/mlcube_docker/docker_run.py", line 100, in validate
    _ = validator.check_unknown_keys(Config.DEFAULT.keys())\
  File "/Users/alejandroaristizabal/opt/anaconda3/envs/medperf/lib/python3.9/site-packages/mlcube/validate.py", line 78, in check_unknown_keys
    raise ConfigurationError(f"Unknown keys: {unknown_keys}.{self._namespace_msg()}")
mlcube.errors.ConfigurationError: Unknown keys: ['--gpus']. Namespace = runner.

Reproduce the command from the report, then start in mlcube/cli.py at parse_cli_args and follow configuration creation into mlcube_docker/docker_run.py, where validation rejects the key. Done means the documented --gpus usage is accepted without the Unknown keys error and GPU configuration reaches the runner as intended.