# Training-Time RTC

Training-Time RTC teaches the model to handle inference delay during training.
It feeds the **ground-truth action prefix** to the model and trains only on the remaining postfix actions.
This keeps chunk transitions smooth without doing any inference-time inpainting.

Based on: [Training-Time Action Conditioning for Efficient Real-Time Chunking](https://arxiv.org/abs/2512.05964).

LeRobot supports this for `pi0`, `pi05` and `smolvla` without changing model parameters.

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## How It Works

At training time:

- Sample a delay `d` per batch element.
- Keep the first `d` action steps as **ground truth** (no noise).
- Add noise only to the postfix actions.
- Set the flow-matching timestep to **1.0** for prefix tokens and normal timesteps for postfix tokens.
- Mask the loss to only train on the postfix.

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## Quick Start (CLI)

```bash
lerobot-train \
  --policy.type=pi0 \
  --dataset.repo_id=your/dataset \
  --policy.rtc_training_config.enabled=true \
  --policy.rtc_training_config.min_delay=0 \
  --policy.rtc_training_config.max_delay=6 \
  --policy.rtc_training_config.delay_distribution=UNIFORM
```

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## Key Parameters

`RTCTrainingConfig` is available on the policy config (`pi0`, `pi05`, `smolvla`, `xvla`):

- **`enabled`**: Toggle training-time RTC.
- **`min_delay` / `max_delay`**: Delay range (inclusive).
- **`delay_distribution`**:
  - `UNIFORM`: uniform in `[min_delay, max_delay]`
  - `EXP`: exponentially decayed distribution over delays
- **`exp_decay`**: Exponential decay factor for `EXP` sampling.

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## Notes and Recommendations

- Start with `min_delay=0` and `max_delay` around your expected worst-case inference delay.
- Use `EXP` if you want more supervision on smaller delays.

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## Related Docs

- [Real-Time Chunking (Inference-Time RTC)](./rtc)
- [Pi0](./pi0), [Pi0.5](./pi05), [SmolVLA](./smolvla)