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import json
import math
import os
import signal
import subprocess
import sys
import time
from pathlib import Path
from typing import Dict, List, Optional, Sequence, Tuple
PROJECT_ROOT = Path(__file__).resolve().parents[1]
if str(PROJECT_ROOT) not in sys.path:
sys.path.insert(0, str(PROJECT_ROOT))
def _configure_coppeliasim_env() -> None:
coppeliasim_root = os.environ.setdefault("COPPELIASIM_ROOT", "/workspace/coppelia_sim")
ld_library_path_parts = [
part for part in os.environ.get("LD_LIBRARY_PATH", "").split(":") if part
]
if coppeliasim_root not in ld_library_path_parts:
ld_library_path_parts.insert(0, coppeliasim_root)
os.environ["LD_LIBRARY_PATH"] = ":".join(ld_library_path_parts)
_configure_coppeliasim_env()
from rr_label_study.oven_study import _aggregate_summary, _episode_dirs
def _select_episode_indices(
total_episodes: int,
episode_offset: int,
max_episodes: Optional[int],
episode_indices: Optional[Sequence[int]],
) -> List[int]:
if episode_indices is not None:
selected: List[int] = []
seen = set()
for raw_index in episode_indices:
episode_index = int(raw_index)
if not (0 <= episode_index < total_episodes):
raise ValueError(
f"episode index {episode_index} outside available range 0..{total_episodes - 1}"
)
if episode_index in seen:
continue
selected.append(episode_index)
seen.add(episode_index)
return selected
remaining = max(0, total_episodes - episode_offset)
if max_episodes is not None:
remaining = min(remaining, max_episodes)
if remaining <= 0:
return []
return list(range(episode_offset, episode_offset + remaining))
def _chunk_episode_indices(
episode_indices: Sequence[int],
num_workers: int,
) -> List[List[int]]:
if not episode_indices:
return []
worker_count = min(num_workers, len(episode_indices))
chunk_size = math.ceil(len(episode_indices) / worker_count)
specs: List[List[int]] = []
for worker_index in range(worker_count):
start = worker_index * chunk_size
chunk = list(episode_indices[start : start + chunk_size])
if chunk:
specs.append(chunk)
return specs
def _launch_xvfb(display_num: int, log_path: Path) -> subprocess.Popen:
log_handle = log_path.open("w", encoding="utf-8")
return subprocess.Popen(
[
"Xvfb",
f":{display_num}",
"-screen",
"0",
"1280x1024x24",
"+extension",
"GLX",
"+render",
"-noreset",
],
stdout=log_handle,
stderr=subprocess.STDOUT,
start_new_session=True,
)
def _launch_worker(
worker_dir: Path,
display_num: int,
dataset_root: str,
episode_indices: Sequence[int],
checkpoint_stride: int,
template_episode_index: int,
max_frames: Optional[int],
independent_replay: bool,
per_episode_templates: bool,
thread_count: int,
) -> Tuple[subprocess.Popen, subprocess.Popen]:
worker_dir.mkdir(parents=True, exist_ok=True)
xvfb = _launch_xvfb(display_num, worker_dir.joinpath("xvfb.log"))
time.sleep(1.0)
runtime_dir = Path(f"/tmp/rr_label_study_display_{display_num}")
runtime_dir.mkdir(parents=True, exist_ok=True)
command = [
sys.executable,
str(PROJECT_ROOT.joinpath("scripts", "run_oven_label_study.py")),
"--dataset-root",
dataset_root,
"--result-dir",
str(worker_dir),
"--checkpoint-stride",
str(checkpoint_stride),
"--template-episode-index",
str(template_episode_index),
"--episode-indices",
",".join(str(index) for index in episode_indices),
]
if max_frames is not None:
command.extend(["--max-frames", str(max_frames)])
if not independent_replay:
command.append("--sequential-replay")
if per_episode_templates:
command.append("--per-episode-templates")
env = os.environ.copy()
env["DISPLAY"] = f":{display_num}"
env["XDG_RUNTIME_DIR"] = str(runtime_dir)
env["PYTHONUNBUFFERED"] = "1"
coppeliasim_root = env.get("COPPELIASIM_ROOT", "/workspace/coppelia_sim")
env["COPPELIASIM_ROOT"] = coppeliasim_root
ld_library_path_parts = [
part for part in env.get("LD_LIBRARY_PATH", "").split(":") if part
]
if coppeliasim_root not in ld_library_path_parts:
ld_library_path_parts.insert(0, coppeliasim_root)
env["LD_LIBRARY_PATH"] = ":".join(ld_library_path_parts)
thread_count_str = str(thread_count)
env["OMP_NUM_THREADS"] = thread_count_str
env["OPENBLAS_NUM_THREADS"] = thread_count_str
env["MKL_NUM_THREADS"] = thread_count_str
env["NUMEXPR_NUM_THREADS"] = thread_count_str
env["VECLIB_MAXIMUM_THREADS"] = thread_count_str
env["BLIS_NUM_THREADS"] = thread_count_str
worker_log = worker_dir.joinpath("worker.log").open("w", encoding="utf-8")
process = subprocess.Popen(
command,
stdout=worker_log,
stderr=subprocess.STDOUT,
env=env,
cwd=str(PROJECT_ROOT),
start_new_session=True,
)
return xvfb, process
def _stop_process(process: subprocess.Popen) -> None:
if process.poll() is not None:
return
try:
os.killpg(process.pid, signal.SIGTERM)
except ProcessLookupError:
return
try:
process.wait(timeout=10)
except subprocess.TimeoutExpired:
try:
os.killpg(process.pid, signal.SIGKILL)
except ProcessLookupError:
pass
def _collect_metrics(base_result_dir: Path) -> List[Dict[str, object]]:
metrics: List[Dict[str, object]] = []
for metrics_path in sorted(base_result_dir.glob("worker_*/episode*.metrics.json")):
with metrics_path.open("r", encoding="utf-8") as handle:
metrics.append(json.load(handle))
return metrics
def main(argv: Optional[List[str]] = None) -> int:
parser = argparse.ArgumentParser()
parser.add_argument(
"--dataset-root",
default="/workspace/data/bimanual_take_tray_out_of_oven_train_128",
)
parser.add_argument(
"--result-dir",
default="/workspace/reveal_retrieve_label_study/results/oven_parallel",
)
parser.add_argument("--num-workers", type=int, default=4)
parser.add_argument("--episode-offset", type=int, default=0)
parser.add_argument("--max-episodes", type=int)
parser.add_argument("--checkpoint-stride", type=int, default=16)
parser.add_argument("--template-episode-index", type=int, default=0)
parser.add_argument("--base-display", type=int, default=110)
parser.add_argument("--max-frames", type=int)
parser.add_argument("--episode-indices")
parser.add_argument("--thread-count", type=int, default=1)
parser.add_argument("--stagger-seconds", type=float, default=0.5)
parser.add_argument(
"--independent-replay",
dest="independent_replay",
action="store_true",
help="Replay each frame independently to avoid simulator drift.",
)
parser.add_argument(
"--sequential-replay",
dest="independent_replay",
action="store_false",
help="Reuse replay state across frames for speed.",
)
parser.add_argument("--per-episode-templates", action="store_true")
parser.set_defaults(independent_replay=True)
args = parser.parse_args(argv)
dataset_root = Path(args.dataset_root)
all_episodes = _episode_dirs(dataset_root)
explicit_episode_indices = None
if args.episode_indices:
explicit_episode_indices = [
int(chunk.strip()) for chunk in args.episode_indices.split(",") if chunk.strip()
]
selected_episode_indices = _select_episode_indices(
total_episodes=len(all_episodes),
episode_offset=args.episode_offset,
max_episodes=args.max_episodes,
episode_indices=explicit_episode_indices,
)
chunk_specs = _chunk_episode_indices(
episode_indices=selected_episode_indices,
num_workers=args.num_workers,
)
if not chunk_specs:
raise RuntimeError("no episodes selected for parallel run")
result_dir = Path(args.result_dir)
result_dir.mkdir(parents=True, exist_ok=True)
workers: List[Tuple[subprocess.Popen, subprocess.Popen]] = []
worker_meta: List[Dict[str, object]] = []
try:
for worker_index, worker_episode_indices in enumerate(chunk_specs):
display_num = args.base_display + worker_index
worker_dir = result_dir.joinpath(f"worker_{worker_index:02d}")
xvfb, process = _launch_worker(
worker_dir=worker_dir,
display_num=display_num,
dataset_root=args.dataset_root,
episode_indices=worker_episode_indices,
checkpoint_stride=args.checkpoint_stride,
template_episode_index=args.template_episode_index,
max_frames=args.max_frames,
independent_replay=args.independent_replay,
per_episode_templates=args.per_episode_templates,
thread_count=args.thread_count,
)
workers.append((xvfb, process))
worker_meta.append(
{
"worker_index": worker_index,
"display_num": display_num,
"episode_indices": list(worker_episode_indices),
}
)
if args.stagger_seconds > 0:
time.sleep(args.stagger_seconds)
for meta, (_, process) in zip(worker_meta, workers):
return_code = process.wait()
meta["return_code"] = return_code
if return_code != 0:
worker_index = int(meta["worker_index"])
worker_log = result_dir.joinpath(f"worker_{worker_index:02d}", "worker.log")
raise RuntimeError(
f"worker {worker_index} failed with code {return_code}; see {worker_log}"
)
finally:
for xvfb, process in workers:
_stop_process(process)
_stop_process(xvfb)
episode_metrics = _collect_metrics(result_dir)
summary = _aggregate_summary(episode_metrics)
with result_dir.joinpath("parallel_workers.json").open("w", encoding="utf-8") as handle:
json.dump(worker_meta, handle, indent=2)
with result_dir.joinpath("parallel_summary.json").open("w", encoding="utf-8") as handle:
json.dump(summary, handle, indent=2)
print(json.dumps(summary, indent=2))
return 0
if __name__ == "__main__":
raise SystemExit(main())
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