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9398fb9 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 | #!/usr/bin/env python3
"""Legacy timing harness (evaluate2 removed). Use scripts/evaluate.py directly.
This script is deprecated and may be removed. Run evaluate.py with --policy-gpu / --render-gpu.
"""
from __future__ import annotations
import argparse
import json
import os
import subprocess
import sys
from pathlib import Path
OPENPI_ROOT = Path(__file__).resolve().parents[1]
EVAL_SCRIPT = OPENPI_ROOT / "scripts" / "evaluate.py"
def _parse_args() -> argparse.Namespace:
p = argparse.ArgumentParser(description="Benchmark evaluate2 end-to-end timing")
p.add_argument("--python", default=sys.executable)
p.add_argument("--suite", default="libero_10_task")
p.add_argument("--task-index", type=int, default=4)
p.add_argument("--rollouts-per-task", type=int, default=1)
p.add_argument("--max-control-steps", type=int, default=120)
p.add_argument("--config-name", default="pi05_libero_stage2p5_joint")
p.add_argument(
"--checkpoint-dir",
default="/scratch1/home/zhicao/openpi/checkpoints/pi05_libero_stage2p5_joint/pi05_final/29999",
)
p.add_argument("--out-dir", default=str(OPENPI_ROOT / "results" / "timing_benchmark"))
p.add_argument("--run-name", default="timing_probe")
p.add_argument(
"--compare-modes",
action="store_true",
help="Run full / light / no-video / no-original presets and print table",
)
p.add_argument("--extra-args", nargs=argparse.REMAINDER, help="Passed through to evaluate2")
return p.parse_args()
def _run_evaluate2(
*,
python: str,
label: str,
suite: str,
task_index: int,
rollouts: int,
max_steps: int,
config_name: str,
checkpoint: str,
out_dir: str,
run_name: str,
mode_flags: list[str],
extra: list[str] | None,
) -> dict:
run_slug = f"{run_name}_{label}"
cmd = [
python,
str(EVAL_SCRIPT),
"--profile-timing",
"--suites",
suite,
"--task-index",
str(task_index),
"--rollouts-per-task",
str(rollouts),
"--max-control-steps",
str(max_steps),
"--config-name",
config_name,
"--checkpoint-dir",
checkpoint,
"--out-dir",
out_dir,
"--run-name",
run_slug,
*mode_flags,
]
if extra:
cmd.extend(extra)
print(f"\n>>> [{label}] {' '.join(cmd)}", flush=True)
proc = subprocess.run(cmd, cwd=str(OPENPI_ROOT), env=os.environ.copy(), check=False)
if proc.returncode != 0:
raise RuntimeError(f"evaluate2 failed for mode={label} (exit {proc.returncode})")
timing_path = Path(out_dir) / f"{run_slug}_timing_profile.json"
if not timing_path.exists():
raise FileNotFoundError(f"Missing timing JSON: {timing_path}")
data = json.loads(timing_path.read_text(encoding="utf-8"))
row = data.get(suite, data)
row["label"] = label
row["timing_json"] = str(timing_path)
return row
def _extrapolate_hours(row: dict) -> float:
s_per = float(row.get("s_per_rollout", 0))
n_tasks = int(row.get("task_ids", 1))
rollouts = int(row.get("rollouts_per_task", 1))
max_steps = int(row.get("max_control_steps", 0))
measured = int(row.get("control_steps", 0))
policy_load = float(row.get("policy_load_s", 0))
total_rollouts = n_tasks * rollouts
if max_steps <= 0 or measured <= 0:
return (s_per * total_rollouts + policy_load) / 3600.0
scale = float(max_steps) / float(measured)
return (s_per * scale * total_rollouts + policy_load) / 3600.0
def _print_row(row: dict) -> None:
label = row.get("label", "?")
print(f"\n--- {label} ---")
phases = [
("policy_load", "policy_load_s"),
("env_build", "env_build_s"),
("rollout_reset", "rollout_reset_s"),
("wait_env_step", "wait_env_step_s"),
("prepare_raw", "prepare_raw_s"),
("policy_infer", "policy_infer_s"),
("render_overlay", "render_overlay_s"),
("render_original", "render_original_s"),
("control_env_step", "control_env_step_s"),
("video_overlay_encode", "video_overlay_encode_s"),
("video_original_encode", "video_original_encode_s"),
("hdf5_write", "hdf5_write_s"),
]
total = float(row.get("rollout_wall_s", 0))
for name, key in phases:
v = float(row.get(key, 0))
if v <= 0:
continue
pct = 100.0 * v / total if total > 0 else 0
print(f" {name:22} {v:8.2f}s ({pct:5.1f}% of rollout wall)")
print(f" {'TOTAL rollout':22} {total:8.2f}s ({row.get('rollouts', '?')} rollouts)")
if "ms_per_control_step" in row:
print(f" ms/control_step: {row['ms_per_control_step']}")
if "s_per_policy_infer" in row:
print(f" s/policy_infer: {row['s_per_policy_infer']}")
est_h = _extrapolate_hours(row)
n_tasks = row.get("task_ids", "?")
rpt = row.get("rollouts_per_task", "?")
print(
f" Extrapolate suite: {n_tasks} tasks × {rpt} rollouts "
f"≈ {est_h:.2f} h (light_eval={row.get('light_eval')}, "
f"orig_video={row.get('save_original_rollout_video')})"
)
print(f" JSON: {row.get('timing_json', '')}")
def _print_compare_table(rows: list[dict]) -> None:
print("\n" + "=" * 88)
print("MODE COMPARISON (one task, limited max_control_steps)")
print("=" * 88)
headers = ["label", "s/rollout", "ms/step", "s/infer", "est_suite_h", "light", "orig_vid"]
print(" | ".join(f"{h:>12}" for h in headers))
print("-" * 88)
for r in rows:
print(
" | ".join(
f"{str(r.get(h, '')):>12}"
for h in [
"label",
"s_per_rollout",
"ms_per_control_step",
"s_per_policy_infer",
f"{_extrapolate_hours(r):.2f}",
"light_eval",
"save_original_rollout_video",
]
)
)
print("=" * 88)
if len(rows) >= 2:
base = float(rows[0].get("s_per_rollout", 0))
fast = min(float(r.get("s_per_rollout", 0)) for r in rows[1:])
if base > 0 and fast > 0:
print(f"Fastest vs baseline rollout: {base / fast:.2f}x speedup")
def main() -> None:
args = _parse_args()
extra = list(args.extra_args or [])
presets: list[tuple[str, list[str]]]
if args.compare_modes:
presets = [
("full_default", []),
("no_original_video", ["--no-save-original-rollout-video"]),
("light_eval", ["--light-eval"]),
]
else:
presets = [("probe", [])]
rows: list[dict] = []
for label, flags in presets:
rows.append(
_run_evaluate2(
python=args.python,
label=label,
suite=args.suite,
task_index=args.task_index,
rollouts=args.rollouts_per_task,
max_steps=args.max_control_steps,
config_name=args.config_name,
checkpoint=args.checkpoint_dir,
out_dir=args.out_dir,
run_name=args.run_name,
mode_flags=flags,
extra=extra,
)
)
_print_row(rows[-1])
if len(rows) > 1:
_print_compare_table(rows)
if __name__ == "__main__":
main()
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