ColinSkywalker/Pi0-Tube-GT

GeoPi0-new

PyTorch pi0 policy fine-tuned on the local UR5 real-robot LeRobot-format dataset with the GT stage-2 foreground cross-view distillation setup:

• dataset: ur5_lab_test_tube_camera_shifts
• training config name: pi0_ur5_real_robot_pytorch_cross_attn_fg_distill_gt_stage2_hard
• experiment name: pi0_ur5_real_robot_cross_attn_fg_distill_gt_hard_stage2_a100_2gpu_b16
• source Slurm job: 9555584
• base camera view: observation.images.context_left_rgb
• wrist camera view: observation.images.wrist_right_rgb
• base model init: /scratch/yz11445/pi0_base
• stage-1 init weights: /scratch/yz11445/tmp/openpi_cam/checkpoints/pi0_ur5_real_robot_pytorch_cross_attn_fg_distill_gt_stage1_hard/pi0_ur5_real_robot_cross_attn_fg_distill_gt_hard_stage1_a100_2gpu_b16/5000
• currently included checkpoint steps: 20000, 25000, 30000

This run completed through 30000 steps.

Included Files

• config.json: base Pi0 model config copied from the initialization checkpoint
• model_architecture_config.json: fine-tuned architecture settings used by this run
• training_config_summary.json: training/data/run summary for this release
• assets/ur5_lab_test_tube_camera_shifts/norm_stats.json: normalization statistics
• checkpoints/<step>/: checkpoint snapshots with model.safetensors, metadata.pt, optimizer.pt, and copied assets

Inference

Serve one of the included checkpoints with:

uv run scripts/serve_policy.py policy:checkpoint \
  --policy.config=pi0_ur5_real_robot_pytorch_cross_attn_fg_distill_gt_stage2_hard \
  --policy.dir=/path/to/GeoPi0-new/checkpoints/30000

Replace 30000 with one of 20000, 25000, or 30000.

Notes

• The policy loader uses the code-defined training config pi0_ur5_real_robot_pytorch_cross_attn_fg_distill_gt_stage2_hard from src/openpi/training/config.py.
• This GT stage-2 variant uses PRoPE ray encoding, foreground cross-view fusion, and hard-confidence auxiliary point supervision from the grid-224 GT target cache.
• Normalization stats are loaded from assets/ur5_lab_test_tube_camera_shifts/norm_stats.json inside each checkpoint directory.
• Tokenizer assets are not bundled in this release directory. In this codebase, the Pi0 tokenizer is loaded at runtime from external sources referenced in src/openpi/models/tokenizer.py.