Add post-training recipe for forward dynamics experiments on Droid

[WeiChengTseng]

Summary

Add a complete SFT recipe for training Cosmos3 forward dynamics on the Cosmos3-DROID dataset (LeRobot v3.0 format).

• Register action_fd_droid_posttrain experiment with mode="forward_dynamics", 10-D ee-pose action space (midtrain alias), 16-frame chunks at 480p resolution.
• Add DROIDMergedLeRobotDataset to load both success/ and failure/ splits from a single parent root, without changing the existing single-root DROIDLeRobotDataset used by the policy recipe.
• Add get_action_droid_merged_lerobot_sft_dataset() factory and wire it through ActionSFTDataset / ActionTransformPipeline.
• Ship paired TOML + launch shell (action_fd_droid_posttrain.toml, launch_sft_action_fd_droid_posttrain.sh) and reproduction docs (docs/action_fd_droid_posttrain.md).

Motivation

Cosmos3 supports forward-dynamics inference (forward_dynamics mode: predict future video from first frame + action sequence), but there was no public post-training recipe for fine-tuning on Cosmos3-DROID. This PR closes that gap and mirrors the structure of existing SFT recipes (e.g. action policy on DROID/LIBERO).

Test plan

• Config dry-run passes:

  PYTHONPATH=. python -m cosmos_framework.scripts.train \
    --sft-toml examples/toml/sft_config/action_fd_droid_posttrain.toml \
    --dryrun