Add Robometer reward model

This commit is contained in:
Khalil Meftah
2026-05-17 14:59:23 +02:00
parent 9db9c35cb4
commit f6a13b1338
19 changed files with 2701 additions and 10 deletions
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#!/usr/bin/env python
# Copyright 2026 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
"""Verify that a LeRobot-format Robometer is byte-equivalent to its upstream source.
Run this once after publishing a LeRobot-format Robometer to the Hub, before
flipping the default `RobometerConfig.pretrained_path` to it. It loads both
the upstream snapshot and the re-exported copy, compares state dicts, and
prints a clear pass/fail summary.
Example:
python scripts/verify_robometer_export.py \\
--upstream robometer/Robometer-4B \\
--lerobot lerobot/robometer-4b
python scripts/verify_robometer_export.py \\
--upstream robometer/Robometer-4B \\
--lerobot ./robometer-4b-lerobot # local folder also works
"""
from __future__ import annotations
import argparse
import sys
from lerobot.configs.rewards import RewardModelConfig
from lerobot.rewards.robometer import RobometerConfig, RobometerRewardModel
from lerobot.rewards.robometer._upstream_loader import apply_upstream_checkpoint
def _load_upstream(path: str) -> RobometerRewardModel:
# Fresh ``RobometerConfig`` (``vlm_config=None``) triggers
# ``RobometerRewardModel.__init__``'s upstream-matching path: download
# base Qwen, resize for ROBOMETER_SPECIAL_TOKENS. The subsequent
# ``apply_upstream_checkpoint`` call resizes again if the checkpoint's
# vocab differs (e.g. upstream was trained against an older Qwen).
cfg = RobometerConfig(pretrained_path=path, device="cpu")
model = RobometerRewardModel(cfg)
apply_upstream_checkpoint(model, path)
model.eval()
return model
def _load_lerobot(path: str) -> RobometerRewardModel:
cfg = RewardModelConfig.from_pretrained(path)
if not isinstance(cfg, RobometerConfig):
raise TypeError(f"Expected RobometerConfig in LeRobot export, got {type(cfg)}")
cfg.pretrained_path = path
cfg.device = "cpu"
return RobometerRewardModel.from_pretrained(path, config=cfg)
def compare_state_dicts(a: RobometerRewardModel, b: RobometerRewardModel) -> bool:
sd_a, sd_b = a.state_dict(), b.state_dict()
keys_a, keys_b = set(sd_a), set(sd_b)
missing = keys_a - keys_b
extra = keys_b - keys_a
if missing:
print(f"{len(missing)} keys missing in LeRobot-format model (sample: {list(missing)[:5]})")
if extra:
print(f"{len(extra)} extra keys in LeRobot-format model (sample: {list(extra)[:5]})")
if missing or extra:
return False
diff_summary: list[tuple[str, float]] = []
for key in sorted(keys_a):
ta, tb = sd_a[key], sd_b[key]
if ta.shape != tb.shape:
print(f"❌ shape mismatch at {key}: {tuple(ta.shape)} vs {tuple(tb.shape)}")
return False
# Compare in float to avoid bfloat16 equality quirks.
max_abs = (ta.float() - tb.float()).abs().max().item()
if max_abs > 0:
diff_summary.append((key, max_abs))
if not diff_summary:
print(f"✅ All {len(keys_a)} parameters identical")
return True
# Some keys differ; show worst offenders.
diff_summary.sort(key=lambda kv: kv[1], reverse=True)
print(f"⚠️ {len(diff_summary)} keys differ. Top 10 by max abs diff:")
for key, value in diff_summary[:10]:
print(f" {key:60s} max|Δ| = {value:.3e}")
# Tolerance: bf16 round-trips can introduce ULP-level noise but no real
# change. Allow up to 1e-3 absolute difference; anything larger is a real
# divergence.
worst = diff_summary[0][1]
if worst < 1e-3:
print(f"✅ Worst diff {worst:.3e} is within bf16 round-trip tolerance")
return True
print(f"❌ Worst diff {worst:.3e} exceeds tolerance (1e-3)")
return False
def main() -> int:
parser = argparse.ArgumentParser(
description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter
)
parser.add_argument("--upstream", required=True, help="Upstream Robometer repo id or local path.")
parser.add_argument("--lerobot", required=True, help="LeRobot-format Robometer repo id or local path.")
args = parser.parse_args()
print(f"Loading upstream: {args.upstream}")
upstream = _load_upstream(args.upstream)
print(f"Loading LeRobot-format: {args.lerobot}")
lerobot = _load_lerobot(args.lerobot)
print("\n=== Config comparison ===")
config_ok = True
for field in [
"base_model_id",
"torch_dtype",
"use_multi_image",
"use_per_frame_progress_token",
"average_temporal_patches",
"frame_pooling",
"frame_pooling_attn_temperature",
"progress_loss_type",
"progress_discrete_bins",
]:
a, b = getattr(upstream.config, field), getattr(lerobot.config, field)
field_ok = a == b
config_ok = config_ok and field_ok
ok = "" if field_ok else ""
print(f" {ok} {field}: upstream={a!r}, lerobot={b!r}")
print("\n=== State-dict comparison ===")
state_dict_ok = compare_state_dicts(upstream, lerobot)
print()
if config_ok and state_dict_ok:
print("🎉 Verification passed — safe to flip the default.")
return 0
print("⛔ Verification failed — DO NOT flip the default.")
return 1
if __name__ == "__main__":
sys.exit(main())