# Logging stats side channels in custom Unity Environment using ML-Agents Academy.Instance.StatsRecorder

**URL:** <https://discuss.ray.io/t/logging-stats-side-channels-in-custom-unity-environment-using-ml-agents-academy-instance-statsrecorder/12437>\
**Category:** RLlib\
**Created:** [October 12, 2023, 8:11pm UTC](https://discuss.ray.io/t/logging-stats-side-channels-in-custom-unity-environment-using-ml-agents-academy-instance-statsrecorder/12437 "2023-10-12T20:11:58Z")\
**Posts on this page:** 2\
**Page:** 1

<div class="post-metadata">

**Author:** ![Philipp\_D\_Siedler](https://sea2.discourse-cdn.com/flex020/user_avatar/discuss.ray.io/philipp_d_siedler/32/2779_2.png) [@Philipp\_D\_Siedler](https://discuss.ray.io/u/Philipp_D_Siedler)\
**Post date:** [October 12, 2023, 8:11pm UTC](https://discuss.ray.io/t/logging-stats-side-channels-in-custom-unity-environment-using-ml-agents-academy-instance-statsrecorder/12437/1 "2023-10-12T20:11:58Z")

</div>

**How severe does this issue affect your experience of using Ray?**

- High: It blocks me to complete my task.

Heya, I have a custom environment built in Unity. In Unity, I use ML-Agents, which also provides an `Academy.Instance.StatsRecorder` to track custom data in the environment. This is how I was hoping this would work:

```python
    from mlagents_envs.side_channel.environment_parameters_channel import EnvironmentParametersChannel
    from mlagents_envs.side_channel.stats_side_channel import StatsSideChannel
    
    env_setup_channel = EnvironmentParametersChannel()
    env_setup_channel .set_float_parameter("training", 1)

    # This is what I'm interested in:
    stats_channel = StatsSideChannel()

    tune.register_env(
        "unity3d",
        lambda c: CustomEnv(
            file_name=FILE_NAME,
            no_graphics=True,
            episode_horizon=EPISODE_HORIZON,
            side_channel=[env_setup_channel, stats_channel],
        ),
    )

```

The `env_setup_channel` is passing parameters to the Unity environment, which works well when I use RLLibs `tune.Tuner` to run training:

```python
    results = tune.Tuner(
        "PPO",
        param_space=config.to_dict(),
        run_config=air.RunConfig(
            stop=stop,
            verbose=2,
            checkpoint_config=air.CheckpointConfig(
                checkpoint_frequency=5,
                checkpoint_at_end=True,
            ),
        ),
    ).fit()

```

However I was expecting for the stats that I’m adding to my `Academy.Instance.StatsRecorder` in the Unity environment, would show up when I open the training results in tensorboard. (this is the behaviour in Unitys ML-Agents)

Am I missing something? Maybe [sven1977](https://discuss.ray.io/u/sven1977) has an idea? Thank you!

---

<div class="post-metadata">

**Author:** ![Philipp\_D\_Siedler](https://sea2.discourse-cdn.com/flex020/user_avatar/discuss.ray.io/philipp_d_siedler/32/2779_2.png) [@Philipp\_D\_Siedler](https://discuss.ray.io/u/Philipp_D_Siedler)\
**Post date:** [October 19, 2023, 10:31am UTC](https://discuss.ray.io/t/logging-stats-side-channels-in-custom-unity-environment-using-ml-agents-academy-instance-statsrecorder/12437/2 "2023-10-19T10:31:08Z")

</div>

I just found out how to do it:

1. Create a custom callback:

```auto
from ray.rllib.algorithms.callbacks import DefaultCallbacks

class CustomMetricsCallback(DefaultCallbacks):
    def on_episode_end(self, worker, base_env, policies, episode, **kwargs):
        unity_env = base_env.get_sub_environments()[0]
        stats_side_channel = unity_env.stats_channel.stats

        for key, metric in stats_side_channel.items():
            episode.custom_metrics[key] = sum([value[0] for value in metric]) / len(
                metric
            )

```

1. Then add it to the config:

```auto
config = (
    PPOConfig()
    ...
    .callbacks(CustomMetricsCallback)
)

```