---
license: apache-2.0
task_categories:
- text-to-video
pretty_name: One-Forcing Data
size_categories:
- 1K<n<10K
---

# One-Forcing Data

Compact clean-latent LMDB shards for One-Forcing training.

The original ODE trajectory rows had shape `[num_denoising_steps, num_frames, channels, height, width]`.
This release keeps only the clean latent used by training, so each row is stored as
`[num_frames, channels, height, width]`.

## Layout

```text
ODE6KCausal_chunkwise_0/data.mdb
ODE6KCausal_chunkwise_0/lock.mdb
...
ODE6KCausal_chunkwise_14/data.mdb
ODE6KCausal_chunkwise_14/lock.mdb
```

Each shard uses the same LMDB key layout as the training code:

- `latents_shape`: stored shape for the shard, e.g. `434 21 16 60 104`
- `latents_source_shape`: original full trajectory shape, e.g. `434 6 21 16 60 104`
- `latents_clean_only`: `1`
- `latents_{i}_data`: float16 clean latent row
- `prompts_{i}_data`: UTF-8 prompt string
- `prompts_shape`: number of prompts in the shard

## Usage

Point One-Forcing training at the downloaded dataset directory:

```bash
torchrun --nproc_per_node=8 train.py \
  --config_path chunkwise_config.yaml \
  --data_path /path/to/One-Forcing-Data \
  --disable-wandb \
  --no_visualize
```

The expected `data_prefix` is `ODE6KCausal_chunkwise`.