BraxAutoResetWrapper discards terminal observation, breaking correct value bootstrapping on truncation

# `BraxAutoResetWrapper` discards terminal observation, breaking correct value bootstrapping on truncation

Hello everyone, I have searched through the existing and closed issues but I have found nothing regarding incorrect value bootstrapping on truncation, so here it is:

## Summary

`BraxAutoResetWrapper` (in `mujoco_playground/_src/wrapper.py`) overwrites `state.obs` with the reset observation on `done`, without preserving the pre-reset observation anywhere in `state.info`. While this is perfect for automated-reset in vectorized environments, this makes it impossible for downstream RL algorithms to implement correct value bootstrapping on truncation.

## Why this matters for RL

Every actor-critic method needs to distinguish termination from truncation when computing TD targets / GAE:

- **Termination** (e.g. agent fell): the MDP ends. Target is `r_t` (no bootstrap).
- **Truncation** (e.g. time limit hit, task still alive): the episode is artificially cut. Target is `r_t + γ·V(s_{t+1})`, where `s_{t+1}` is the observation the agent *would have seen next* had the episode continued.

`wrap_for_brax_training` already exposes the termination/truncation distinction correctly via `state.info['truncation']` (set by brax's `EpisodeWrapper`). But to actually compute the truncation bootstrap `V(s_{t+1})`, the learner needs access to `s_{t+1}` — the terminal observation of the truncated trajectory. After `BraxAutoResetWrapper.step`, that observation is gone: `state.obs` has been replaced by the reset state, and `info` only holds reset-related bookkeeping (`_first_data`, `_first_obs`, `_rng`, `_done_count`).

In practice this means every PPO/SAC implementation built on Playground is silently bootstrapping on `V(s_reset)` instead of `V(s_{t+1})` at every truncation. The bias is small on short-horizon tasks with low γ but grows with episode length and γ, and is particularly pathological on locomotion tasks where `s_reset` is an upright pose very different from the late-episode state.

The same flaw exists in `brax.envs.wrappers.training.AutoResetWrapper`. Gymnasium solved this years ago by putting the terminal observation in `info["final_observation"]` on truncation, which is the convention most SB3/CleanRL/RLlib code expects.

## Proposed fix

In `BraxAutoResetWrapper.step`, before the `where_done` mask replaces `obs` and `data`, stash the pre-reset observation in info:

```python
# inside BraxAutoResetWrapper.step, after self.env.step(...) returns
next_info = state.info
next_info[f"{self._info_key}_final_obs"] = state.obs
# ...rest unchanged
```

This is does not break anything, and enables correct truncation handling for any downstream learner that reads it.

## Reproduction

```python
import jax, jax.numpy as jnp
from mujoco_playground import registry, wrapper

env = wrapper.wrap_for_brax_training(registry.load("HopperHop"), episode_length=10)
state = jax.jit(env.reset)(jax.random.split(jax.random.PRNGKey(0), 2))
for t in range(10):
state = jax.jit(env.step)(state, jnp.zeros((2, env.action_size)))
print("done:", state.done, "truncation:", state.info["truncation"])
print("obs (overwritten by reset):", state.obs[0, :3])
# no info key holds the pre-reset observation
print("info keys:", [k for k in state.info if "obs" in k.lower()])
```

Expected: some `info['...final_obs...']` key carrying the real terminal observation.
Actual: no such key exists.

Maybe I am missing something, please tell me if that's the case :)

Otherwise, I can take care of the pull-request if needed.

Yann