| # GeoPi0-new |
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| PyTorch `pi0` policy fine-tuned on the local UR5 real-robot LeRobot-format dataset with the GT stage-2 foreground cross-view distillation setup: |
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| - 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` |
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| This run completed through `30000` steps. |
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| ## Included Files |
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| - `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 |
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| ## Inference |
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| Serve one of the included checkpoints with: |
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| ```bash |
| 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 |
| ``` |
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| Replace `30000` with one of `20000`, `25000`, or `30000`. |
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| ## Notes |
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| - 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`. |
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