DiMorph Body-Field Encoder
Runtime checkpoint for the DiMorph cross-morphology body functional-field encoder used by T1, K1, Unitree H1 and Unitree G1 policies.
The public artifact is a sanitized inference checkpoint. Training-only optimizer/pretrainer state, source file lists, cached human roles, normalization statistics and raw/converted motion data are not included. The runtime keys required by research/dimarl/dimarl/model.py are preserved.
Architecture
- encoder type:
body_functional_field_v1 - spectral coordinate width: 32
- hidden width: 128
- role width: 64
- attention heads: 4
- encoder layers: 2
- source morphology joint count: 23 (Booster T1)
Download
hf download tsingzeyong/dimarl-body-field-encoder \
encoder_best_runtime.pt \
--local-dir /root/gpufree-data/DI-MARL/body_field/public
Use it during training with:
export DIMARL_PRETRAINED_ENCODER=/root/gpufree-data/DI-MARL/body_field/public/encoder_best_runtime.pt
The full code and experiment record are available at hashlure/di-marl, commit 3446d70bdf1e2cd051e60288f39e068ad3d973ce.
Validation status
The GitHub snapshot passed 99 CPU static tests, Python AST checks and shell syntax checks. The post-fix four-robot GPU training sequence has not yet been rerun, so this repository does not claim final locomotion performance.
Terms
The encoder was trained for non-commercial scientific research using AMASS/CMU-derived supervision. Use is limited by the applicable source-dataset terms, including the AMASS license. No AMASS/CMU frames are distributed here.
- Downloads last month
- -