Reprocess 4,976 DROID Episodes Across 5 Machines
Quick Start
Run this command on each of the 5 machines:
cd /root/workspace/code/wmrl/Dual-Dynamics-Models/DROID-main
bash scripts/reprocess_all_5machines.sh <MACHINE_ID>
Where <MACHINE_ID> is:
- Machine 1:
0 - Machine 2:
1 - Machine 3:
2 - Machine 4:
3 - Machine 5:
4
Episode Distribution
Each machine processes a subset of the 4,976 episodes:
| Machine | Episodes | Count |
|---|---|---|
| 0 | 0 → 995 | 995 |
| 1 | 995 → 1990 | 995 |
| 2 | 1990 → 2985 | 995 |
| 3 | 2985 → 3980 | 995 |
| 4 | 3980 → 4976 | 996 |
Each machine distributes its episodes across 8 GPUs (~124 episodes per GPU).
Monitoring Progress
Check logs
# Watch GPU 0 log in real-time
tail -f /mnt/kevin/data/droid_processed_1000pts/reprocessing_logs/m0_gpu0.log
# Check all GPU logs on machine 0
ls -lh /mnt/kevin/data/droid_processed_1000pts/reprocessing_logs/m0_*.log
Check completion
# Count completed GPUs on machine 0
grep 'Complete:' /mnt/kevin/data/droid_processed_1000pts/reprocessing_logs/m0_*.log | wc -l
# Should output: 8 (when all GPUs done)
# Check success/error counts
grep -h 'Success:' /mnt/kevin/data/droid_processed_1000pts/reprocessing_logs/m0_*.log
Monitor GPU usage
watch -n 1 nvidia-smi
# Should see all 8 GPUs at 70-90% utilization
Verify Results
After all machines complete, verify track counts:
cd /root/workspace/code/wmrl/Dual-Dynamics-Models/DROID-main
/mnt/kevin/envs/miniconda3/envs/atm_ati_vdm_droid/bin/python -c "
import numpy as np
from pathlib import Path
import random
data_dir = Path('/mnt/kevin/data/droid_processed_1000pts/data')
npz_files = sorted(data_dir.glob('episode_*.npz'))
# Sample 50 random episodes
samples = random.sample(npz_files, 50)
correct = 0
wrong = 0
for npz_path in samples:
data = np.load(npz_path, allow_pickle=True)
wrist_count = data['tracks_wrist'].shape[1]
if wrist_count == 1105:
correct += 1
else:
wrong += 1
print(f'{npz_path.name}: wrist={wrist_count}')
print(f'\nResults from 50 random samples:')
print(f' Correct (1105): {correct}')
print(f' Wrong: {wrong}')
"
Expected output: All 50 samples should have 1105 wrist points.
Troubleshooting
Stop all reprocessing
pkill -f 'python.*episode'
Restart a specific machine
# Stop
pkill -f 'python.*episode'
# Wait a few seconds
sleep 5
# Restart
bash scripts/reprocess_all_5machines.sh <MACHINE_ID>
Check for stuck processes
ps aux | grep python | grep episode
Estimated Time
- Per episode: ~30-60 seconds (depending on length)
- Per GPU: ~124 episodes × 45 sec avg = ~93 minutes
- Total time: ~1.5-2 hours (all machines in parallel)
What Gets Updated
Each .npz file will be updated with:
- ✓
tracks_wrist: 1112 → 1105 points (7 mesh + 98 grid + 1000 random) - ✓
tracks_exterior: Already correct (1105 points) - ✓
mesh_vertices_2d_wrist_fixed: Already exists - ✓ All other fields: Unchanged
Features
- ✅ GPU distribution: All 40 GPUs (5 machines × 8 GPUs) utilized
- ✅ OOM handling: Automatic retry with batching (batch_size=600)
- ✅ Correct track counts: 1105 points for both views
- ✅ Progress tracking: Individual log files per GPU
- ✅ Resumable: Skips already-processed episodes (checks track count)