colab-gpu

SKILL.md

Colab GPU Integration

Quick Reference

# First time setup
./scripts/colab_sync.sh init

# Every iteration cycle
./scripts/colab_sync.sh push      # Push src/ to Drive
# → User runs Colab notebook (Run All)
./scripts/colab_sync.sh watch     # Auto-poll until complete
./scripts/colab_sync.sh pull      # Pull results/ back

# Check status manually
./scripts/colab_sync.sh status

How It Works

Local (Claude Code)              Google Drive              Colab (GPU)
─────────────────              ────────────              ───────────
src/ ──push──────────→ research-fleet/src/ ──mount──→ /content/workspace/src/
                                                      GPU Training
results/ ←──pull───── research-fleet/results/ ←──sync── writes results + _colab_complete.json

Completion Detection

The Colab notebook writes _colab_complete.json when finished:

{
  "iteration": 1,
  "status": "complete",
  "gpu": "Tesla T4",
  "files_synced": 5
}

colab_sync.sh watch polls for this file every 30 seconds.

Troubleshooting

Symptom Cause Fix
push fails Drive not mounted/configured Run rclone config or install Google Drive Desktop
status never completes Colab disconnected Reconnect Colab, re-run cells
Results missing Train.py errored Check Colab output cells for Python errors
Wrong iteration State file stale Check orchestrator_state.json iteration number

Local GPU Fallback

If GPU is available locally, skip Colab entirely:

cd workspace/src && python train.py

The rest of the pipeline doesn't care where results came from.

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