| """Render the final five-task, four-method frozen-100-seed comparison table.""" |
| from __future__ import annotations |
|
|
| import argparse |
| import hashlib |
| import json |
| from pathlib import Path |
|
|
| import matplotlib.pyplot as plt |
|
|
|
|
| TASKS = [ |
| ("LiftBarrier", 2, "lift_barrier"), |
| ("CameraAlignment", 3, "camera_alignment"), |
| ("ThreeRobotsStackCube", 3, "three_robots_stack_cube"), |
| ("LongPipelineDelivery", 4, "long_pipeline_delivery"), |
| ("TakePhoto", 4, "take_photo"), |
| ] |
| METHODS = [ |
| ("冻结 DINOv3-ACT", "frozen_dinov3_act_all5_80k"), |
| ("Stereo-ACT-cross_relbias", "stereo_cross_relbias_all5_80k"), |
| ("Stereo-FFN-MoE", "stereo_ffn_moe_all5_80k"), |
| ("Local-ARCA", "local_arca_all5_80k"), |
| ] |
|
|
|
|
| def read_result(root: Path, method: str, task: str, seed_root: Path): |
| |
| |
| |
| path = root / method / "formal_heldout_100" / f"eval_{task}.json" |
| if not path.is_file(): |
| return None |
| raw = json.loads(path.read_text(encoding="utf-8")) |
| if raw.get("episodes") != 100: |
| raise ValueError(f"not formal 100-seed output: {path}") |
| expected = hashlib.sha256((seed_root / f"{task}.json").read_bytes()).hexdigest() |
| protocol = raw.get("seed_protocol", {}) |
| if protocol.get("sha256") != expected or protocol.get("training_seed_overlap") != 0: |
| raise ValueError(f"seed audit failed: {path}") |
| return int(raw["successes"]), int(raw["episodes"]) |
|
|
|
|
| def main() -> None: |
| parser = argparse.ArgumentParser() |
| parser.add_argument("--root", default="/workspace/RoboFactory/runs/strict640x480_v2/results") |
| parser.add_argument("--output", default="/workspace/RoboFactory/runs/strict640x480_v2/final_report") |
| args = parser.parse_args(); root, out = Path(args.root), Path(args.output); out.mkdir(parents=True, exist_ok=True) |
| seed_root = root.parent / "heldout_seeds" |
| values = [[read_result(root, method_dir, task_id, seed_root) for _, _, task_id in TASKS] for _, method_dir in METHODS] |
| lines = ["| Training corpus | Test task (robots) | " + " | ".join(name for name, _ in METHODS) + " |", |
| "|---|---|" + "---|" * len(METHODS)] |
| table = [] |
| for task_index, (task_name, robots, _) in enumerate(TASKS): |
| row = [column[task_index] for column in values] |
| best = max((item[0] / item[1] for item in row if item), default=None) |
| cells = [] |
| for item in row: |
| if not item: cells.append("—"); continue |
| text = f"{item[0]}/{item[1]} ({100 * item[0] / item[1]:.1f}%)" |
| cells.append(f"**{text}**" if item[0] / item[1] == best else text) |
| lines.append("| All-5 strict640x480-v2 | " + f"{task_name} ({robots}) | " + " | ".join(cells) + " |") |
| table.append(cells) |
| (out / "performance_table.md").write_text("\n".join(lines) + "\n", encoding="utf-8") |
| (out / "formal_seed_audit.json").write_text(json.dumps({ |
| "status": "PASS", "episodes_per_cell": 100, |
| "tasks": [task_id for _, _, task_id in TASKS], |
| "methods": [method_id for _, method_id in METHODS], |
| "condition": "each result uses the matching frozen manifest with zero training-seed overlap", |
| }, indent=2) + "\n", encoding="utf-8") |
| fig, axis = plt.subplots(figsize=(16, 4.8)); axis.axis("off") |
| rendered = axis.table(cellText=table, colLabels=[name for name, _ in METHODS], |
| rowLabels=[f"{name} ({robots})" for name, robots, _ in TASKS], |
| cellLoc="center", loc="center") |
| rendered.auto_set_font_size(False); rendered.set_fontsize(10); rendered.scale(1, 2.0) |
| axis.set_title("RoboFactory — strict wrist-only RGB-D, All-5, frozen unseen 100-seed evaluation", pad=20, fontsize=14, weight="bold") |
| fig.tight_layout(); fig.savefig(out / "performance_table.png", dpi=220, bbox_inches="tight") |
| print(out / "performance_table.png") |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|