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GPSDynamicsModel — graph-based (GNN + Transformer) dynamics model for
variable-vertex cloth meshes, two-gripper, trained with rectified flow
matching instead of DDPM. Given the 3 previous mesh frames and a per-hand 3D
gripper action, predicts the next 5 mesh frames.dexgarmentlab_dual_gps2048_clean.h5, Cloth-splatters/dexgarmentlab-dual-meshes-clean)FlowMatch_DynamicsGPS, logit-normal t, shift 1.0)model/ is checkpoint-best)demos2h_dyn_gps_flow_2026-08-21_17-27-35_776087 (full config in config.yml)history_noise_std 1e-4. Validation plateaued at step 175k — the last 25k
steps gained nothing, so this horizon was long enough (unlike the DDPM arm).cross_attn_mode: sequential here, versus parallel for the DDPM sibling.
That is carried over from the flow recipe it inherits and is the setting this
checkpoint's numbers belong to; parallel vs sequential has never been A/B'd
within the dynamics family, so treat the choice as inherited rather than
validated.max_grippers: 2. The action is one token stream per hand, with a learned
gripper-ID embedding and per-gripper grasped-flag node channels. A trajectory
that moves only one hand parks the other and flags it in the recording's
hand_active attribute; the loader masks that slot out of both gripper_mask
and the translation-centering centroid, so it behaves exactly like a padded
slot.gripper_pos / actuated_vertices fields, but on a two-handed
trajectory those are a lossy back-compat projection — the legacy point is a
virtual gripper between the hands, ~14 cm from the vertices it nominally
drives (the real per-hand positions sit 3-4 cm away), and the legacy mask
covers only ~85 of the ~153 vertices the two hands actually hold. Use
gripper_pos_2h / actuated_vertices_2h, as ClothDynamicsVariableDataset
and ClothDynamicsGraphDataset now do.scripts/benchmark_dynamics_accuracy.py, validation split (24 held-out
garments — the split is by garment, baked into the dataset file, so no
trajectory of a validation cloth is ever seen in training), 50 denoising
steps, one trajectory per cloth for the rollout:| model | one-shot (5 frames) | rollout mean | rollout end |
|---|---|---|---|
-dynamics-gps (DDPM) | 1.25 cm | 1.86 cm | 3.00 cm |
-dynamics-gps-flow | 1.24 cm | 1.84 cm | 3.10 cm |
-dynamics-gns | 0.52 cm | 3.75 cm | 5.72 cm |