Single Joint Model + Config#41
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compute_metrics previously hardcoded 4 joint names, so calling it from the single-joint training script produced meaningless per-joint keys (rmse_hip_r / rmse_knee_* were always 0 since the output has shape 1). - Add optional joint_names param to compute_metrics; defaults to the original 4-joint list so all existing callers are unaffected - Pass joint_names=[joint_name] from validate() using the joint index from the yaml config (hip_l=0, hip_r=1, knee_l=2, knee_r=3) - Derive joint_label in train() and use it for epoch and test printouts instead of printing all four hard-coded joint lines - Fix stray leading-space indent in validate()
…ce server
- SERVER: model registry for full (28-feat) and single_joint (7-feat) TCN,
selected via ?model= query param; outputs denormalized to Nm using
normalization_stats.json then scaled by pilot mass_kg
- SERVER: pilot config loaded from configs/pilots/{PILOT}.json at startup
(PILOT env var, defaults to 'default'); mass_kg=1.0 in default.json
- SERVICE: set Environment=PILOT=default in systemd unit
- EXPORT: fix export_onnx.py to read input_size/output_size from config
instead of hardcoding 28/4 — required for single-joint model export
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Created single joint TCN model. Associated YAML file should be used to specify which joint is being tested along with the features associated with that specific joint.
Related Issue: Experimentation Framework #32