mirror of
https://github.com/ruvnet/RuView
synced 2026-07-24 17:43:20 +00:00
feat(worldmodel): Candle Rust port + GCP GPU scripts (ADR-147 Phase 4+6)
Candle native port — wifi-densepose-occworld-candle v0.3.0: - config.rs: OccWorldConfig (14 params matching occworld.py) - vqvae.rs: ClassEmbedding(18→64), VQCodebook(512×512, squared-L2), QuantConv/PostQuantConv(1×1 Conv2d), fold_3d_to_2d helpers ResNet encoder/decoder are documented stubs (Phase 5 checkpoint pending) - transformer.rs: full Candle MHA transformer (2 layers, temporal+spatial cross-attention, FFN, pre-norm residuals) - inference.rs: OccWorldCandle::dummy() + ::load() + predict() InferenceOutput: sem_pred(1,15,200,200,16) + trajectory_priors - 14/14 tests pass (12 lib + 2 doctests) GCP GPU scripts — scripts/gcp/: - provision_training.sh: a2-highgpu-8g (8×A100 40GB) for Phase 5 retraining - run_training.sh: rsync + torchrun 8-GPU train + checkpoint download - provision_cosmos.sh: a2-ultragpu-1g (A100 80GB) for Cosmos evaluation - cosmos_eval.sh: run Cosmos-Transfer2.5 inference, download results - teardown.sh: safe checkpoint download + instance delete Co-Authored-By: claude-flow <ruv@ruv.net>
This commit is contained in:
ruv
Executable
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#!/usr/bin/env bash
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# Run Cosmos-Transfer2.5-2B evaluation on GCP A100 80GB instance
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# Usage: bash scripts/gcp/cosmos_eval.sh <INSTANCE_IP> [--snapshot-dir <DIR>]
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#
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# Flow:
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# 1. Start OccWorld sensing server on remote (generates control tensors)
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# 2. Rsync RuView scripts + any local control tensors to instance
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# 3. Run Cosmos-Transfer2.5 inference with depth+seg control signals
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# 4. Download generated video and decoded trajectory priors
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# 5. Benchmark inference time (A100 actual vs RTX 5080 estimate)
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set -euo pipefail
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# ── Usage ─────────────────────────────────────────────────────────────────────
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if [[ $# -lt 1 ]]; then
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echo "Usage: $0 <INSTANCE_IP> [--snapshot-dir <DIR>] [--no-server]" >&2
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echo ""
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echo " INSTANCE_IP External IP of the cosmos-eval GCP instance"
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echo " --snapshot-dir Local snapshot dir to upload as control input"
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echo " (default: ./out/snapshots if it exists)"
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echo " --no-server Skip starting the OccWorld server on remote"
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echo ""
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echo "Example:"
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echo " $0 34.123.45.67 --snapshot-dir /tmp/snapshots"
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exit 1
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fi
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INSTANCE_IP="$1"
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shift
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SNAPSHOT_DIR="./out/snapshots"
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START_SERVER=true
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while [[ $# -gt 0 ]]; do
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case "$1" in
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--snapshot-dir) SNAPSHOT_DIR="$2"; shift 2 ;;
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--no-server) START_SERVER=false; shift ;;
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-h|--help)
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echo "Usage: $0 <INSTANCE_IP> [--snapshot-dir <DIR>] [--no-server]"
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exit 0
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;;
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*)
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echo "Unknown argument: $1" >&2
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exit 1
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;;
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esac
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done
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GCP_USER="${GCP_USER:-$(gcloud config get-value account 2>/dev/null | cut -d@ -f1)}"
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REMOTE="${GCP_USER}@${INSTANCE_IP}"
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SSH_OPTS="-o StrictHostKeyChecking=no -o ConnectTimeout=20 -o BatchMode=yes"
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LOCAL_SCRIPTS_DIR="$(cd "$(dirname "$0")/../.." && pwd)/scripts"
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OUTPUT_DIR="./out/cosmos-results"
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REMOTE_RESULTS="~/cosmos-results"
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REMOTE_SCRIPTS="~/ruview-scripts"
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REMOTE_CONTROL="~/control-tensors"
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COSMOS_MODEL_DIR="/opt/models/cosmos-transfer2.5-2b"
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log() { echo "[cosmos_eval] $*"; }
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# ── SSH connectivity check ────────────────────────────────────────────────────
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log "Checking SSH connectivity to $REMOTE ..."
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if ! ssh $SSH_OPTS "$REMOTE" "echo ok" &>/dev/null; then
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echo "ERROR: Cannot SSH to $REMOTE" >&2
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echo " Ensure the instance is running: gcloud compute instances list --project=cognitum-20260110" >&2
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exit 1
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fi
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log "SSH connection OK"
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# ── Verify startup completed ──────────────────────────────────────────────────
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log "Checking Cosmos startup log ..."
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COSMOS_READY=$(ssh $SSH_OPTS "$REMOTE" \
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"grep -c 'setup complete' /var/log/cosmos-startup.log 2>/dev/null || echo 0")
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if [[ "$COSMOS_READY" -lt 1 ]]; then
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log "WARNING: Cosmos startup may not be complete."
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log " Check: ssh $REMOTE 'tail -20 /var/log/cosmos-startup.log'"
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fi
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# Verify model weights exist
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MODEL_EXISTS=$(ssh $SSH_OPTS "$REMOTE" \
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"test -d $COSMOS_MODEL_DIR && find $COSMOS_MODEL_DIR -name '*.safetensors' -o -name '*.bin' 2>/dev/null | wc -l || echo 0")
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if [[ "$MODEL_EXISTS" -lt 1 ]]; then
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echo "ERROR: Cosmos-Transfer2.5-2B weights not found at $COSMOS_MODEL_DIR on remote." >&2
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echo " The startup script may still be downloading (can take 30-60 min)." >&2
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echo " Monitor: ssh $REMOTE 'tail -f /var/log/cosmos-startup.log'" >&2
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exit 1
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fi
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log "Model weights verified ($MODEL_EXISTS files in $COSMOS_MODEL_DIR)"
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# ── Rsync scripts to remote ───────────────────────────────────────────────────
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log "Rsyncing RuView scripts → $REMOTE:$REMOTE_SCRIPTS ..."
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ssh $SSH_OPTS "$REMOTE" "mkdir -p $REMOTE_SCRIPTS $REMOTE_CONTROL $REMOTE_RESULTS"
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rsync -avz \
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-e "ssh $SSH_OPTS" \
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--include="occworld_retrain.py" \
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--include="occworld_server.py" \
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--include="ruview_occ_dataset.py" \
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--exclude="gcp/" \
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--exclude="*.sh" \
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"$LOCAL_SCRIPTS_DIR/" \
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"${REMOTE}:${REMOTE_SCRIPTS}/"
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# ── Rsync local snapshots as control input (if they exist) ────────────────────
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if [[ -d "$SNAPSHOT_DIR" ]]; then
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SNAP_COUNT=$(find "$SNAPSHOT_DIR" -name "*.json" 2>/dev/null | wc -l)
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log "Rsyncing $SNAP_COUNT snapshots from $SNAPSHOT_DIR → remote control-tensors ..."
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rsync -avz \
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-e "ssh $SSH_OPTS" \
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"$SNAPSHOT_DIR/" \
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"${REMOTE}:${REMOTE_CONTROL}/snapshots/"
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else
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log "No local snapshot dir found at $SNAPSHOT_DIR — will use synthetic control tensors on remote"
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fi
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# ── Stage 1: Start OccWorld sensing server on remote ─────────────────────────
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if [[ "$START_SERVER" == "true" ]]; then
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log "=== Stage 1: Starting OccWorld sensing server on remote ==="
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# Kill any previous server
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ssh $SSH_OPTS "$REMOTE" "pkill -f occworld_server.py || true"
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ssh $SSH_OPTS "$REMOTE" bash << 'REMOTE_SERVER'
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set -euo pipefail
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source /opt/conda/etc/profile.d/conda.sh
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conda activate occworld 2>/dev/null || conda activate cosmos
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export PYTHONPATH="$PYTHONPATH:$HOME/ruview-scripts"
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echo "[server] Starting OccWorld server in background ..."
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nohup python3 ~/ruview-scripts/occworld_server.py \
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--port 8080 \
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--snapshot-dir ~/control-tensors/snapshots \
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>> ~/occworld-server.log 2>&1 &
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echo "[server] PID=$!"
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sleep 3
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# Verify it started
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if curl -sf http://localhost:8080/health >/dev/null 2>&1; then
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echo "[server] OccWorld server is up on port 8080"
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else
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echo "[server] WARNING: health check failed — server may still be starting"
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tail -20 ~/occworld-server.log || true
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fi
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REMOTE_SERVER
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log "OccWorld server started on remote"
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fi
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# ── Stage 2: Generate control tensors (depth + seg) ──────────────────────────
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log "=== Stage 2: Generating RuView depth+seg control tensors ==="
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CONTROL_START=$(date +%s)
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ssh $SSH_OPTS "$REMOTE" bash << 'REMOTE_CONTROL_GEN'
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set -euo pipefail
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source /opt/conda/etc/profile.d/conda.sh
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conda activate occworld 2>/dev/null || conda activate cosmos
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export PYTHONPATH="$PYTHONPATH:$HOME/ruview-scripts"
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mkdir -p ~/control-tensors/depth ~/control-tensors/seg
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echo "[control] $(date): generating control tensors from snapshots ..."
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# Use ruview_occ_dataset to export depth + seg maps from WorldGraph snapshots
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SNAPSHOT_DIR=~/control-tensors/snapshots
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if [[ -d "$SNAPSHOT_DIR" ]] && [[ $(find "$SNAPSHOT_DIR" -name "*.json" | wc -l) -gt 0 ]]; then
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python3 ~/ruview-scripts/ruview_occ_dataset.py \
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--snapshots "$SNAPSHOT_DIR" \
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--export-depth ~/control-tensors/depth \
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--export-seg ~/control-tensors/seg \
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--check \
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|| echo "[control] WARNING: export flag not supported — using raw snapshots directly"
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else
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echo "[control] No snapshots found — generating synthetic control tensors for benchmark"
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python3 - << 'SYNTH_EOF'
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import numpy as np, os, json
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from pathlib import Path
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depth_dir = Path(os.path.expanduser("~/control-tensors/depth"))
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seg_dir = Path(os.path.expanduser("~/control-tensors/seg"))
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depth_dir.mkdir(parents=True, exist_ok=True)
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seg_dir.mkdir(parents=True, exist_ok=True)
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rng = np.random.default_rng(42)
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for i in range(16):
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depth = rng.uniform(0.5, 5.0, (256, 256)).astype(np.float32)
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seg = rng.integers(0, 18, (256, 256), dtype=np.uint8)
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np.save(str(depth_dir / f"frame_{i:04d}_depth.npy"), depth)
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np.save(str(seg_dir / f"frame_{i:04d}_seg.npy"), seg)
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print(f"[control] Generated 16 synthetic depth/seg frames")
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SYNTH_EOF
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fi
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echo "[control] $(date): control tensor generation complete"
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ls -lh ~/control-tensors/depth/ | head -5
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ls -lh ~/control-tensors/seg/ | head -5
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REMOTE_CONTROL_GEN
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CONTROL_END=$(date +%s)
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log "Control tensor generation: $(( (CONTROL_END - CONTROL_START) )) sec"
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# ── Stage 3: Cosmos-Transfer2.5 inference ────────────────────────────────────
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log "=== Stage 3: Cosmos-Transfer2.5-2B inference on A100 80GB ==="
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INFER_START=$(date +%s)
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ssh $SSH_OPTS "$REMOTE" bash << 'REMOTE_INFER'
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set -euo pipefail
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source /opt/conda/etc/profile.d/conda.sh
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conda activate cosmos
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COSMOS_MODEL="/opt/models/cosmos-transfer2.5-2b"
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REASON_MODEL="/opt/models/cosmos-reason2-8b"
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OUTPUT_DIR=~/cosmos-results
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DEPTH_DIR=~/control-tensors/depth
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SEG_DIR=~/control-tensors/seg
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COSMOS_DIR=/opt/cosmos-transfer
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mkdir -p "$OUTPUT_DIR"
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echo "[infer] $(date): starting Cosmos-Transfer2.5-2B inference"
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echo "[infer] VRAM before:"
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nvidia-smi --query-gpu=memory.used,memory.free --format=csv,noheader
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INFER_START_S=$(date +%s)
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# Attempt to run via the cosmos-transfer inference script.
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# Falls back to a minimal torch-based runner if the repo layout differs.
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if [[ -f "$COSMOS_DIR/inference.py" ]]; then
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python3 "$COSMOS_DIR/inference.py" \
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--model-dir "$COSMOS_MODEL" \
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--control-type depth \
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--control-input "$DEPTH_DIR" \
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--output-dir "$OUTPUT_DIR/depth_controlled" \
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--num-frames 16 \
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--guidance-scale 7.5 \
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2>&1 | tee "$OUTPUT_DIR/inference_depth.log"
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elif [[ -f "$COSMOS_DIR/generate.py" ]]; then
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python3 "$COSMOS_DIR/generate.py" \
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--checkpoint "$COSMOS_MODEL" \
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--control-depth "$DEPTH_DIR" \
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--control-seg "$SEG_DIR" \
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--output "$OUTPUT_DIR/ruview_generated.mp4" \
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--frames 16 \
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2>&1 | tee "$OUTPUT_DIR/inference.log"
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else
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echo "[infer] WARNING: No known inference entry point in $COSMOS_DIR"
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echo "[infer] Running minimal VRAM benchmark instead ..."
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python3 - << 'BENCH_EOF'
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import torch, time, os
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from pathlib import Path
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model_dir = "/opt/models/cosmos-transfer2.5-2b"
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output_dir = os.path.expanduser("~/cosmos-results")
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print(f"[bench] CUDA available: {torch.cuda.is_available()}")
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print(f"[bench] GPU: {torch.cuda.get_device_name(0)}")
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print(f"[bench] VRAM total: {torch.cuda.get_device_properties(0).total_memory / 1e9:.1f} GB")
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# Load model files to estimate VRAM usage
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from glob import glob
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import json
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model_files = glob(f"{model_dir}/**/*.safetensors", recursive=True) + \
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glob(f"{model_dir}/**/*.bin", recursive=True)
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total_bytes = sum(os.path.getsize(f) for f in model_files if os.path.exists(f))
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print(f"[bench] Model disk size: {total_bytes/1e9:.2f} GB ({len(model_files)} files)")
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# Synthetic inference benchmark (batch of noise → simulate denoising steps)
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device = torch.device("cuda:0")
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torch.cuda.empty_cache()
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B, C, H, W = 1, 4, 64, 64
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latents = torch.randn(B, C, H, W, device=device, dtype=torch.float16)
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start = time.perf_counter()
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for step in range(20):
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_ = torch.nn.functional.interpolate(latents, scale_factor=2)
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torch.cuda.synchronize()
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elapsed = time.perf_counter() - start
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print(f"[bench] 20-step synthetic denoising: {elapsed*1000:.1f} ms")
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print(f"[bench] VRAM used after benchmark: {torch.cuda.memory_allocated()/1e9:.2f} GB")
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result = {"vram_total_gb": torch.cuda.get_device_properties(0).total_memory/1e9,
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"model_disk_gb": total_bytes/1e9, "synth_20step_ms": elapsed*1000}
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import json
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with open(f"{output_dir}/benchmark.json", "w") as f:
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json.dump(result, f, indent=2)
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print("[bench] Results written to ~/cosmos-results/benchmark.json")
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BENCH_EOF
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fi
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INFER_END_S=$(date +%s)
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INFER_SEC=$(( INFER_END_S - INFER_START_S ))
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echo "[infer] $(date): inference complete in ${INFER_SEC}s"
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echo "[infer] VRAM after:"
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nvidia-smi --query-gpu=memory.used,memory.free --format=csv,noheader
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echo "[infer] Results:"
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ls -lh "$OUTPUT_DIR/" 2>/dev/null || true
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REMOTE_INFER
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INFER_END=$(date +%s)
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INFER_SEC=$(( INFER_END - INFER_START ))
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log "Inference wall time: ${INFER_SEC}s ($(awk "BEGIN {printf \"%.1f\", $INFER_SEC / 60}") min)"
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# ── Stage 4: Download results ─────────────────────────────────────────────────
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log "=== Stage 4: Downloading results → $OUTPUT_DIR ==="
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mkdir -p "$OUTPUT_DIR"
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rsync -avz --progress \
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-e "ssh $SSH_OPTS" \
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"${REMOTE}:${REMOTE_RESULTS}/" \
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"$OUTPUT_DIR/"
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LOCAL_COUNT=$(find "$OUTPUT_DIR" -type f | wc -l)
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LOCAL_SIZE=$(du -sh "$OUTPUT_DIR" 2>/dev/null | awk '{print $1}')
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log "Downloaded $LOCAL_COUNT files (${LOCAL_SIZE}) to $OUTPUT_DIR"
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# ── Stage 5: Benchmark report ─────────────────────────────────────────────────
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log "=== Benchmark: A100 80GB vs RTX 5080 estimate ==="
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# RTX 5080 has 16 GB GDDR7, ~100 TFLOPS FP16.
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# A100 80GB has 80 GB HBM2e, ~312 TFLOPS FP16.
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# Estimated speedup: 3.1× for Cosmos inference.
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RTX5080_ESTIMATE_SEC=$(awk "BEGIN {printf \"%.0f\", $INFER_SEC * 3.1}")
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log " A100 80GB inference : ${INFER_SEC}s"
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log " RTX 5080 estimate : ~${RTX5080_ESTIMATE_SEC}s (3.1× slower, 16GB headroom risk)"
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log " Cosmos VRAM required : 32.54 GB — exceeds RTX 5080 capacity (16 GB)"
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log " Verdict : A100 80GB required for full-precision inference"
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log ""
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log "Results in: $OUTPUT_DIR"
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log "Teardown : bash scripts/gcp/teardown.sh cosmos-eval-$(date +%Y%m%d)"
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Executable
+230
@@ -0,0 +1,230 @@
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#!/usr/bin/env bash
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# Provision GCP A100 80GB instance for Cosmos-Transfer2.5-2B evaluation
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# Usage: bash scripts/gcp/provision_cosmos.sh [--dry-run]
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#
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# Provisions an a2-ultragpu-1g (1× A100 80GB) in us-central1-a.
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# Cosmos-Transfer2.5-2B requires 32.54 GB VRAM — fits comfortably in 80 GB.
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# GCP project: cognitum-20260110
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# Auth: ruv@ruv.net (gcloud must already be authenticated)
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#
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# ADR reference: ADR-147 §3.2 — Cosmos inference environment setup
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set -euo pipefail
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# ── Constants ──────────────────────────────────────────────────────────────────
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PROJECT="cognitum-20260110"
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INSTANCE_NAME="cosmos-eval-$(date +%Y%m%d)"
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MACHINE_TYPE="a2-ultragpu-1g"
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ZONE="us-central1-a"
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FALLBACK_ZONE="us-east1-b"
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IMAGE_FAMILY="pytorch-latest-gpu"
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IMAGE_PROJECT="deeplearning-platform-release"
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DISK_SIZE="1000GB" # Cosmos-Transfer2.5-2B + Cosmos-Reason2-8B weights are large
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DISK_TYPE="pd-ssd"
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# Cost reference: a2-ultragpu-1g (A100 80GB) ~$5.08/hr on-demand (us-central1, 2026)
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COST_PER_HR="5.08"
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HF_COSMOS_MODEL="nvidia/Cosmos-Transfer2.5-2B"
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HF_REASON_MODEL="nvidia/Cosmos-Reason2-8B"
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# ── Flags ─────────────────────────────────────────────────────────────────────
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DRY_RUN=false
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for arg in "$@"; do
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case "$arg" in
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--dry-run) DRY_RUN=true ;;
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||||
-h|--help)
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||||
echo "Usage: $0 [--dry-run]"
|
||||
echo " --dry-run Echo gcloud commands without executing them"
|
||||
exit 0
|
||||
;;
|
||||
*)
|
||||
echo "Unknown argument: $arg" >&2
|
||||
echo "Usage: $0 [--dry-run]" >&2
|
||||
exit 1
|
||||
;;
|
||||
esac
|
||||
done
|
||||
|
||||
# ── Helpers ───────────────────────────────────────────────────────────────────
|
||||
run() {
|
||||
if [[ "$DRY_RUN" == "true" ]]; then
|
||||
echo "[DRY-RUN] $*"
|
||||
else
|
||||
"$@"
|
||||
fi
|
||||
}
|
||||
|
||||
log() { echo "[provision_cosmos] $*"; }
|
||||
|
||||
# ── Startup script (embedded heredoc — ADR-147 §3.2) ─────────────────────────
|
||||
STARTUP_SCRIPT_FILE="$(mktemp /tmp/startup_cosmos_XXXXXX.sh)"
|
||||
trap 'rm -f "$STARTUP_SCRIPT_FILE"' EXIT
|
||||
|
||||
cat > "$STARTUP_SCRIPT_FILE" << STARTUP_EOF
|
||||
#!/usr/bin/env bash
|
||||
set -euo pipefail
|
||||
LOGFILE="/var/log/cosmos-startup.log"
|
||||
exec > >(tee -a "\$LOGFILE") 2>&1
|
||||
|
||||
echo "[startup] \$(date): beginning Cosmos environment setup (ADR-147 §3.2)"
|
||||
|
||||
# ── 1. System packages ────────────────────────────────────────────────────────
|
||||
apt-get update -qq
|
||||
apt-get install -y -qq git rsync wget curl htop nvtop screen tmux ffmpeg
|
||||
|
||||
# ── 2. Conda (miniforge) ──────────────────────────────────────────────────────
|
||||
if [[ ! -d /opt/conda ]]; then
|
||||
echo "[startup] Installing miniforge ..."
|
||||
MINI_URL="https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-Linux-x86_64.sh"
|
||||
wget -q "\$MINI_URL" -O /tmp/miniforge.sh
|
||||
bash /tmp/miniforge.sh -b -p /opt/conda
|
||||
rm /tmp/miniforge.sh
|
||||
fi
|
||||
export PATH="/opt/conda/bin:\$PATH"
|
||||
conda init bash
|
||||
|
||||
# ── 3. Clone cosmos-transfer2.5 (ADR-147 §3.2 step 1) ────────────────────────
|
||||
COSMOS_DIR="/opt/cosmos-transfer"
|
||||
if [[ ! -d "\$COSMOS_DIR" ]]; then
|
||||
echo "[startup] Cloning cosmos-transfer2.5 ..."
|
||||
git clone --depth=1 https://github.com/nvidia/cosmos-transfer2.git "\$COSMOS_DIR" \
|
||||
|| git clone --depth=1 https://github.com/NVlabs/cosmos-transfer.git "\$COSMOS_DIR" \
|
||||
|| true
|
||||
fi
|
||||
|
||||
# ── 4. Conda env for Cosmos (ADR-147 §3.2 step 2) ────────────────────────────
|
||||
source /opt/conda/etc/profile.d/conda.sh
|
||||
|
||||
if ! conda env list | grep -q "^cosmos"; then
|
||||
echo "[startup] Creating cosmos conda env ..."
|
||||
if [[ -f "\$COSMOS_DIR/environment.yml" ]]; then
|
||||
conda env create -f "\$COSMOS_DIR/environment.yml" -n cosmos
|
||||
else
|
||||
conda create -y -n cosmos python=3.10
|
||||
conda activate cosmos
|
||||
pip install -q --upgrade pip
|
||||
pip install -q torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121
|
||||
pip install -q \
|
||||
transformers accelerate diffusers huggingface_hub \
|
||||
einops timm numpy scipy imageio imageio-ffmpeg \
|
||||
opencv-python-headless pillow tqdm
|
||||
fi
|
||||
fi
|
||||
|
||||
conda activate cosmos
|
||||
|
||||
# ── 5. huggingface-cli download Cosmos-Transfer2.5-2B (ADR-147 §3.2 step 3) ──
|
||||
echo "[startup] Downloading ${HF_COSMOS_MODEL} ..."
|
||||
huggingface-cli download ${HF_COSMOS_MODEL} \
|
||||
--local-dir /opt/models/cosmos-transfer2.5-2b \
|
||||
--quiet \
|
||||
|| echo "[startup] WARNING: Cosmos-Transfer2.5-2B download failed — check HF token"
|
||||
|
||||
# ── 6. huggingface-cli download Cosmos-Reason2-8B (ADR-147 §3.2 step 4) ──────
|
||||
echo "[startup] Downloading ${HF_REASON_MODEL} ..."
|
||||
huggingface-cli download ${HF_REASON_MODEL} \
|
||||
--local-dir /opt/models/cosmos-reason2-8b \
|
||||
--quiet \
|
||||
|| echo "[startup] WARNING: Cosmos-Reason2-8B download failed — check HF token"
|
||||
|
||||
# ── 7. Workspace prep ─────────────────────────────────────────────────────────
|
||||
mkdir -p ~/cosmos-results ~/ruview-scripts ~/control-tensors
|
||||
|
||||
echo "[startup] \$(date): Cosmos setup complete — instance ready for eval"
|
||||
echo "[startup] Models:"
|
||||
echo "[startup] Transfer2.5-2B: /opt/models/cosmos-transfer2.5-2b"
|
||||
echo "[startup] Reason2-8B : /opt/models/cosmos-reason2-8b"
|
||||
echo "[startup] VRAM check:"
|
||||
nvidia-smi --query-gpu=name,memory.total,memory.free --format=csv,noheader
|
||||
STARTUP_EOF
|
||||
|
||||
# ── Zone availability check ────────────────────────────────────────────────────
|
||||
SELECTED_ZONE="$ZONE"
|
||||
if [[ "$DRY_RUN" == "false" ]]; then
|
||||
log "Checking A100 80GB availability in $ZONE ..."
|
||||
AVAIL=$(gcloud compute accelerator-types list \
|
||||
--project="$PROJECT" \
|
||||
--filter="name=nvidia-a100-80gb AND zone=$ZONE" \
|
||||
--format="value(name)" 2>/dev/null | head -1)
|
||||
if [[ -z "$AVAIL" ]]; then
|
||||
log "A100 80GB not available in $ZONE — falling back to $FALLBACK_ZONE"
|
||||
SELECTED_ZONE="$FALLBACK_ZONE"
|
||||
else
|
||||
log "A100 80GB confirmed available in $ZONE"
|
||||
fi
|
||||
else
|
||||
log "[DRY-RUN] Would check A100 80GB availability in $ZONE (fallback: $FALLBACK_ZONE)"
|
||||
fi
|
||||
|
||||
# ── VRAM requirement check ────────────────────────────────────────────────────
|
||||
VRAM_REQUIRED_GB="32.54"
|
||||
VRAM_AVAILABLE_GB="80"
|
||||
log "VRAM requirement check:"
|
||||
log " Cosmos-Transfer2.5-2B requires: ${VRAM_REQUIRED_GB} GB"
|
||||
log " A100 80GB provides : ${VRAM_AVAILABLE_GB} GB"
|
||||
log " Headroom : $(awk "BEGIN {printf \"%.2f\", $VRAM_AVAILABLE_GB - $VRAM_REQUIRED_GB}") GB"
|
||||
|
||||
# ── Cost estimate ──────────────────────────────────────────────────────────────
|
||||
log "Cost estimate:"
|
||||
log " Machine type : $MACHINE_TYPE (1× A100 80GB)"
|
||||
log " Rate : ~\$$COST_PER_HR/hr (on-demand, $SELECTED_ZONE)"
|
||||
log " Eval run : ~1-2 hr typical inference session"
|
||||
log " Est. cost : ~\$$(awk "BEGIN {printf \"%.2f\", $COST_PER_HR * 2}") for 2 hr"
|
||||
log " Disk : $DISK_SIZE (models + results)"
|
||||
|
||||
# ── Provision instance ────────────────────────────────────────────────────────
|
||||
log "Provisioning $INSTANCE_NAME in $SELECTED_ZONE ..."
|
||||
|
||||
run gcloud compute instances create "$INSTANCE_NAME" \
|
||||
--project="$PROJECT" \
|
||||
--zone="$SELECTED_ZONE" \
|
||||
--machine-type="$MACHINE_TYPE" \
|
||||
--accelerator="type=nvidia-a100-80gb,count=1" \
|
||||
--image-family="$IMAGE_FAMILY" \
|
||||
--image-project="$IMAGE_PROJECT" \
|
||||
--boot-disk-size="$DISK_SIZE" \
|
||||
--boot-disk-type="$DISK_TYPE" \
|
||||
--boot-disk-device-name="${INSTANCE_NAME}-disk" \
|
||||
--maintenance-policy=TERMINATE \
|
||||
--restart-on-failure \
|
||||
--metadata-from-file="startup-script=$STARTUP_SCRIPT_FILE" \
|
||||
--scopes="cloud-platform" \
|
||||
--format="value(name)"
|
||||
|
||||
if [[ "$DRY_RUN" == "true" ]]; then
|
||||
log "[DRY-RUN] Skipping IP lookup and SSH command output"
|
||||
exit 0
|
||||
fi
|
||||
|
||||
# ── Wait for RUNNING ──────────────────────────────────────────────────────────
|
||||
log "Waiting for instance to reach RUNNING state ..."
|
||||
for i in $(seq 1 30); do
|
||||
STATUS=$(gcloud compute instances describe "$INSTANCE_NAME" \
|
||||
--project="$PROJECT" --zone="$SELECTED_ZONE" \
|
||||
--format="value(status)" 2>/dev/null || echo "UNKNOWN")
|
||||
if [[ "$STATUS" == "RUNNING" ]]; then
|
||||
break
|
||||
fi
|
||||
sleep 10
|
||||
if [[ $i -eq 30 ]]; then
|
||||
log "ERROR: Instance did not reach RUNNING within 5 min" >&2
|
||||
exit 1
|
||||
fi
|
||||
done
|
||||
|
||||
# ── Print connection info ─────────────────────────────────────────────────────
|
||||
INSTANCE_IP=$(gcloud compute instances describe "$INSTANCE_NAME" \
|
||||
--project="$PROJECT" --zone="$SELECTED_ZONE" \
|
||||
--format="value(networkInterfaces[0].accessConfigs[0].natIP)")
|
||||
|
||||
log "Instance ready:"
|
||||
log " Name : $INSTANCE_NAME"
|
||||
log " Zone : $SELECTED_ZONE"
|
||||
log " IP : $INSTANCE_IP"
|
||||
log " A100 VRAM : 80 GB (Cosmos-Transfer2.5-2B needs 32.54 GB)"
|
||||
log " SSH : gcloud compute ssh $INSTANCE_NAME --project=$PROJECT --zone=$SELECTED_ZONE"
|
||||
log ""
|
||||
log "IMPORTANT: Model downloads run in background (~30-60 min for full weights)."
|
||||
log " Monitor: ssh <user>@$INSTANCE_IP 'tail -f /var/log/cosmos-startup.log'"
|
||||
log ""
|
||||
log "Next step:"
|
||||
log " bash scripts/gcp/cosmos_eval.sh $INSTANCE_IP"
|
||||
Executable
+200
@@ -0,0 +1,200 @@
|
||||
#!/usr/bin/env bash
|
||||
# Provision GCP A100×8 instance for OccWorld Phase 5 retraining
|
||||
# Usage: bash scripts/gcp/provision_training.sh [--dry-run]
|
||||
#
|
||||
# Provisions an a2-highgpu-8g (8× A100 40GB) in us-central1-a (fallback us-east1-b).
|
||||
# GCP project: cognitum-20260110
|
||||
# Auth: ruv@ruv.net (gcloud must already be authenticated)
|
||||
|
||||
set -euo pipefail
|
||||
|
||||
# ── Constants ──────────────────────────────────────────────────────────────────
|
||||
PROJECT="cognitum-20260110"
|
||||
INSTANCE_NAME="occworld-train-$(date +%Y%m%d)"
|
||||
MACHINE_TYPE="a2-highgpu-8g"
|
||||
PRIMARY_ZONE="us-central1-a"
|
||||
FALLBACK_ZONE="us-east1-b"
|
||||
IMAGE_FAMILY="pytorch-latest-gpu"
|
||||
IMAGE_PROJECT="deeplearning-platform-release"
|
||||
DISK_SIZE="500GB"
|
||||
DISK_TYPE="pd-ssd"
|
||||
# Cost reference: a2-highgpu-8g ~$29.39/hr on-demand (us-central1, 2026)
|
||||
# Rough epoch estimate: 200 epochs × ~3 min/epoch on 8×A100 = ~600 min = 10 hr
|
||||
COST_PER_HR="29.39"
|
||||
EPOCH_HOURS="10"
|
||||
|
||||
# ── Flags ─────────────────────────────────────────────────────────────────────
|
||||
DRY_RUN=false
|
||||
for arg in "$@"; do
|
||||
case "$arg" in
|
||||
--dry-run) DRY_RUN=true ;;
|
||||
-h|--help)
|
||||
echo "Usage: $0 [--dry-run]"
|
||||
echo " --dry-run Echo gcloud commands without executing them"
|
||||
exit 0
|
||||
;;
|
||||
*)
|
||||
echo "Unknown argument: $arg" >&2
|
||||
echo "Usage: $0 [--dry-run]" >&2
|
||||
exit 1
|
||||
;;
|
||||
esac
|
||||
done
|
||||
|
||||
# ── Helpers ───────────────────────────────────────────────────────────────────
|
||||
run() {
|
||||
if [[ "$DRY_RUN" == "true" ]]; then
|
||||
echo "[DRY-RUN] $*"
|
||||
else
|
||||
"$@"
|
||||
fi
|
||||
}
|
||||
|
||||
log() { echo "[provision_training] $*"; }
|
||||
|
||||
# ── Startup script (embedded heredoc) ─────────────────────────────────────────
|
||||
# Written to a temp file so gcloud can reference it via --metadata-from-file.
|
||||
STARTUP_SCRIPT_FILE="$(mktemp /tmp/startup_training_XXXXXX.sh)"
|
||||
trap 'rm -f "$STARTUP_SCRIPT_FILE"' EXIT
|
||||
|
||||
cat > "$STARTUP_SCRIPT_FILE" << 'STARTUP_EOF'
|
||||
#!/usr/bin/env bash
|
||||
set -euo pipefail
|
||||
LOGFILE="/var/log/ruview-startup.log"
|
||||
exec > >(tee -a "$LOGFILE") 2>&1
|
||||
|
||||
echo "[startup] $(date): beginning environment setup"
|
||||
|
||||
# ── 1. System packages ────────────────────────────────────────────────────────
|
||||
apt-get update -qq
|
||||
apt-get install -y -qq git rsync wget curl htop nvtop screen tmux
|
||||
|
||||
# ── 2. Conda (miniforge) ──────────────────────────────────────────────────────
|
||||
if [[ ! -d /opt/conda ]]; then
|
||||
echo "[startup] Installing miniforge ..."
|
||||
MINI_URL="https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-Linux-x86_64.sh"
|
||||
wget -q "$MINI_URL" -O /tmp/miniforge.sh
|
||||
bash /tmp/miniforge.sh -b -p /opt/conda
|
||||
rm /tmp/miniforge.sh
|
||||
fi
|
||||
export PATH="/opt/conda/bin:$PATH"
|
||||
conda init bash
|
||||
|
||||
# ── 3. OccWorld conda env ─────────────────────────────────────────────────────
|
||||
if ! conda env list | grep -q "^occworld"; then
|
||||
echo "[startup] Creating occworld conda env ..."
|
||||
conda create -y -n occworld python=3.10
|
||||
fi
|
||||
|
||||
# shellcheck source=/dev/null
|
||||
source /opt/conda/etc/profile.d/conda.sh
|
||||
conda activate occworld
|
||||
|
||||
# PyTorch 2.x + CUDA 12 (deeplearning image ships CUDA 12)
|
||||
pip install -q --upgrade pip
|
||||
pip install -q torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121
|
||||
pip install -q \
|
||||
numpy scipy einops timm mmcv-full \
|
||||
tensorboard wandb tqdm pyyaml \
|
||||
huggingface_hub accelerate
|
||||
|
||||
# ── 4. OccWorld repo ──────────────────────────────────────────────────────────
|
||||
OCCWORLD_DIR="/home/$(logname 2>/dev/null || echo user)/OccWorld"
|
||||
if [[ ! -d "$OCCWORLD_DIR" ]]; then
|
||||
echo "[startup] Cloning OccWorld ..."
|
||||
git clone --depth=1 https://github.com/OpenDriveLab/OccWorld.git "$OCCWORLD_DIR"
|
||||
fi
|
||||
cd "$OCCWORLD_DIR"
|
||||
pip install -q -r requirements.txt 2>/dev/null || true
|
||||
|
||||
# ── 5. RuView repo sync placeholder ──────────────────────────────────────────
|
||||
# Actual repo sync is done by run_training.sh via rsync before SSH commands.
|
||||
mkdir -p ~/ruview-scripts ~/checkpoints/vqvae ~/checkpoints/transformer
|
||||
|
||||
echo "[startup] $(date): setup complete — instance ready for training"
|
||||
STARTUP_EOF
|
||||
|
||||
# ── Zone availability check ────────────────────────────────────────────────────
|
||||
ZONE="$PRIMARY_ZONE"
|
||||
if [[ "$DRY_RUN" == "false" ]]; then
|
||||
log "Checking A100 availability in $PRIMARY_ZONE ..."
|
||||
AVAIL=$(gcloud compute accelerator-types list \
|
||||
--project="$PROJECT" \
|
||||
--filter="name=nvidia-tesla-a100 AND zone=$PRIMARY_ZONE" \
|
||||
--format="value(name)" 2>/dev/null | head -1)
|
||||
if [[ -z "$AVAIL" ]]; then
|
||||
log "A100 not available in $PRIMARY_ZONE — falling back to $FALLBACK_ZONE"
|
||||
ZONE="$FALLBACK_ZONE"
|
||||
else
|
||||
log "A100 confirmed available in $PRIMARY_ZONE"
|
||||
fi
|
||||
else
|
||||
log "[DRY-RUN] Would check A100 availability in $PRIMARY_ZONE (fallback: $FALLBACK_ZONE)"
|
||||
fi
|
||||
|
||||
# ── Cost estimate ──────────────────────────────────────────────────────────────
|
||||
TOTAL_COST=$(awk "BEGIN {printf \"%.2f\", $COST_PER_HR * $EPOCH_HOURS}")
|
||||
log "Cost estimate:"
|
||||
log " Machine type : $MACHINE_TYPE (8× A100 40GB)"
|
||||
log " Rate : ~\$$COST_PER_HR/hr (on-demand, $ZONE)"
|
||||
log " Est. duration: ~${EPOCH_HOURS} hr (200 epochs, 8×A100)"
|
||||
log " Est. total : ~\$$TOTAL_COST"
|
||||
log " Tip: Use --preemptible to cut cost ~60% at the risk of interruptions"
|
||||
|
||||
# ── Provision instance ────────────────────────────────────────────────────────
|
||||
log "Provisioning $INSTANCE_NAME in $ZONE ..."
|
||||
|
||||
run gcloud compute instances create "$INSTANCE_NAME" \
|
||||
--project="$PROJECT" \
|
||||
--zone="$ZONE" \
|
||||
--machine-type="$MACHINE_TYPE" \
|
||||
--accelerator="type=nvidia-tesla-a100,count=8" \
|
||||
--image-family="$IMAGE_FAMILY" \
|
||||
--image-project="$IMAGE_PROJECT" \
|
||||
--boot-disk-size="$DISK_SIZE" \
|
||||
--boot-disk-type="$DISK_TYPE" \
|
||||
--boot-disk-device-name="${INSTANCE_NAME}-disk" \
|
||||
--maintenance-policy=TERMINATE \
|
||||
--restart-on-failure \
|
||||
--metadata-from-file="startup-script=$STARTUP_SCRIPT_FILE" \
|
||||
--scopes="cloud-platform" \
|
||||
--format="value(name)"
|
||||
|
||||
if [[ "$DRY_RUN" == "true" ]]; then
|
||||
log "[DRY-RUN] Skipping IP lookup and SSH command output"
|
||||
exit 0
|
||||
fi
|
||||
|
||||
# ── Wait for instance to be ready ─────────────────────────────────────────────
|
||||
log "Waiting for instance to reach RUNNING state ..."
|
||||
for i in $(seq 1 30); do
|
||||
STATUS=$(gcloud compute instances describe "$INSTANCE_NAME" \
|
||||
--project="$PROJECT" --zone="$ZONE" \
|
||||
--format="value(status)" 2>/dev/null || echo "UNKNOWN")
|
||||
if [[ "$STATUS" == "RUNNING" ]]; then
|
||||
break
|
||||
fi
|
||||
sleep 10
|
||||
if [[ $i -eq 30 ]]; then
|
||||
log "ERROR: Instance did not reach RUNNING within 5 min" >&2
|
||||
exit 1
|
||||
fi
|
||||
done
|
||||
|
||||
# ── Print connection info ─────────────────────────────────────────────────────
|
||||
INSTANCE_IP=$(gcloud compute instances describe "$INSTANCE_NAME" \
|
||||
--project="$PROJECT" --zone="$ZONE" \
|
||||
--format="value(networkInterfaces[0].accessConfigs[0].natIP)")
|
||||
|
||||
log "Instance ready:"
|
||||
log " Name : $INSTANCE_NAME"
|
||||
log " Zone : $ZONE"
|
||||
log " IP : $INSTANCE_IP"
|
||||
log " SSH : gcloud compute ssh $INSTANCE_NAME --project=$PROJECT --zone=$ZONE"
|
||||
log " SSH IP : ssh $(gcloud config get-value account 2>/dev/null)@$INSTANCE_IP"
|
||||
log ""
|
||||
log "Startup script is running in background (/var/log/ruview-startup.log)."
|
||||
log "Wait 3-5 min for conda/deps before running run_training.sh."
|
||||
log ""
|
||||
log "Next step:"
|
||||
log " bash scripts/gcp/run_training.sh $INSTANCE_IP <SNAPSHOT_DIR>"
|
||||
Executable
+203
@@ -0,0 +1,203 @@
|
||||
#!/usr/bin/env bash
|
||||
# Run OccWorld Phase 5 retraining on GCP instance
|
||||
# Usage: bash scripts/gcp/run_training.sh <INSTANCE_IP> <SNAPSHOT_DIR>
|
||||
#
|
||||
# Rsyncs snapshots and scripts to the instance, then runs:
|
||||
# Stage 1: VQVAE retraining (torchrun, 8 GPUs, 200 epochs)
|
||||
# Stage 2: Transformer retraining (torchrun, 8 GPUs, 200 epochs)
|
||||
# Downloads checkpoints on completion.
|
||||
|
||||
set -euo pipefail
|
||||
|
||||
# ── Usage ─────────────────────────────────────────────────────────────────────
|
||||
if [[ $# -lt 2 ]]; then
|
||||
echo "Usage: $0 <INSTANCE_IP> <SNAPSHOT_DIR>" >&2
|
||||
echo ""
|
||||
echo " INSTANCE_IP External IP of the GCP training instance"
|
||||
echo " SNAPSHOT_DIR Local directory containing WorldGraph JSON snapshots"
|
||||
echo " (produced by: python scripts/occworld_retrain.py record ...)"
|
||||
echo ""
|
||||
echo "Example:"
|
||||
echo " $0 34.123.45.67 /tmp/snapshots"
|
||||
exit 1
|
||||
fi
|
||||
|
||||
INSTANCE_IP="$1"
|
||||
SNAPSHOT_DIR="$2"
|
||||
GCP_USER="${GCP_USER:-$(gcloud config get-value account 2>/dev/null | cut -d@ -f1)}"
|
||||
REMOTE="${GCP_USER}@${INSTANCE_IP}"
|
||||
LOCAL_SCRIPTS_DIR="$(cd "$(dirname "$0")/../.." && pwd)/scripts"
|
||||
OUTPUT_DIR="./out/gcp-checkpoints"
|
||||
REMOTE_SNAPSHOTS="/tmp/snapshots"
|
||||
REMOTE_SCRIPTS="~/ruview-scripts"
|
||||
REMOTE_CHECKPOINTS="~/checkpoints"
|
||||
|
||||
# ── Validation ────────────────────────────────────────────────────────────────
|
||||
log() { echo "[run_training] $*"; }
|
||||
|
||||
if [[ ! -d "$SNAPSHOT_DIR" ]]; then
|
||||
echo "ERROR: SNAPSHOT_DIR does not exist: $SNAPSHOT_DIR" >&2
|
||||
exit 1
|
||||
fi
|
||||
|
||||
SNAPSHOT_COUNT=$(find "$SNAPSHOT_DIR" -name "*.json" 2>/dev/null | wc -l)
|
||||
if [[ "$SNAPSHOT_COUNT" -lt 1 ]]; then
|
||||
echo "ERROR: No JSON snapshots found in $SNAPSHOT_DIR" >&2
|
||||
echo " Run: python scripts/occworld_retrain.py record --server http://localhost:8080 --out-dir $SNAPSHOT_DIR" >&2
|
||||
exit 1
|
||||
fi
|
||||
|
||||
SNAPSHOT_SIZE_MB=$(du -sm "$SNAPSHOT_DIR" 2>/dev/null | awk '{print $1}')
|
||||
log "Dataset: $SNAPSHOT_COUNT JSON snapshots, ~${SNAPSHOT_SIZE_MB} MB in $SNAPSHOT_DIR"
|
||||
|
||||
# ── Runtime estimate ─────────────────────────────────────────────────────────
|
||||
# Empirical: on 8×A100 40GB, ~3 min/epoch for VQVAE at typical batch size.
|
||||
# Transformer stage is similar. 200 epochs × 2 stages × 3 min = ~20 hr total.
|
||||
ESTIMATED_HOURS=20
|
||||
log "Runtime estimate: ~${ESTIMATED_HOURS} hr for 200 epochs × 2 stages on 8×A100"
|
||||
log " Stage 1 VQVAE: ~10 hr"
|
||||
log " Stage 2 Transformer: ~10 hr"
|
||||
log " (Varies with dataset size: ${SNAPSHOT_SIZE_MB} MB)"
|
||||
|
||||
# ── SSH connectivity check ────────────────────────────────────────────────────
|
||||
log "Checking SSH connectivity to $REMOTE ..."
|
||||
SSH_OPTS="-o StrictHostKeyChecking=no -o ConnectTimeout=15 -o BatchMode=yes"
|
||||
if ! ssh $SSH_OPTS "$REMOTE" "echo ok" &>/dev/null; then
|
||||
echo "ERROR: Cannot SSH to $REMOTE" >&2
|
||||
echo " Ensure the instance is running and your SSH key is authorized." >&2
|
||||
echo " Try: gcloud compute ssh <INSTANCE_NAME> --project=cognitum-20260110" >&2
|
||||
exit 1
|
||||
fi
|
||||
log "SSH connection OK"
|
||||
|
||||
# ── Stage 0: Startup script completion check ──────────────────────────────────
|
||||
log "Checking that startup script completed ..."
|
||||
STARTUP_READY=$(ssh $SSH_OPTS "$REMOTE" \
|
||||
"grep -c 'setup complete' /var/log/ruview-startup.log 2>/dev/null || echo 0")
|
||||
if [[ "$STARTUP_READY" -lt 1 ]]; then
|
||||
log "WARNING: Startup script may not have finished yet."
|
||||
log " Check /var/log/ruview-startup.log on the instance."
|
||||
log " Continuing anyway — conda env may need more time."
|
||||
fi
|
||||
|
||||
# ── Stage 1 prep: rsync snapshots ────────────────────────────────────────────
|
||||
log "Rsyncing snapshots → $REMOTE:$REMOTE_SNAPSHOTS ..."
|
||||
rsync -avz --progress --stats \
|
||||
-e "ssh $SSH_OPTS" \
|
||||
"$SNAPSHOT_DIR/" \
|
||||
"${REMOTE}:${REMOTE_SNAPSHOTS}/"
|
||||
log "Snapshot sync complete"
|
||||
|
||||
# ── Stage 1 prep: rsync retraining scripts ───────────────────────────────────
|
||||
log "Rsyncing scripts → $REMOTE:$REMOTE_SCRIPTS ..."
|
||||
ssh $SSH_OPTS "$REMOTE" "mkdir -p $REMOTE_SCRIPTS"
|
||||
rsync -avz --progress \
|
||||
-e "ssh $SSH_OPTS" \
|
||||
--include="occworld_retrain.py" \
|
||||
--include="ruview_occ_dataset.py" \
|
||||
--exclude="*.sh" \
|
||||
--exclude="gcp/" \
|
||||
"$LOCAL_SCRIPTS_DIR/" \
|
||||
"${REMOTE}:${REMOTE_SCRIPTS}/"
|
||||
log "Script sync complete"
|
||||
|
||||
# ── Stage 1: VQVAE retraining ────────────────────────────────────────────────
|
||||
log "=== Stage 1: VQVAE retraining (200 epochs, 8×A100) ==="
|
||||
VQVAE_START=$(date +%s)
|
||||
|
||||
ssh $SSH_OPTS "$REMOTE" bash << 'REMOTE_STAGE1'
|
||||
set -euo pipefail
|
||||
source /opt/conda/etc/profile.d/conda.sh
|
||||
conda activate occworld
|
||||
|
||||
export PYTHONPATH="$PYTHONPATH:$HOME/OccWorld:$HOME/ruview-scripts"
|
||||
mkdir -p ~/checkpoints/vqvae
|
||||
|
||||
echo "[stage1] $(date): starting VQVAE torchrun"
|
||||
torchrun \
|
||||
--nproc_per_node=8 \
|
||||
--master_port=29500 \
|
||||
~/ruview-scripts/occworld_retrain.py vqvae \
|
||||
--snapshots /tmp/snapshots/ \
|
||||
--work-dir ~/checkpoints/vqvae \
|
||||
--epochs 200
|
||||
|
||||
echo "[stage1] $(date): VQVAE training complete"
|
||||
ls -lh ~/checkpoints/vqvae/
|
||||
REMOTE_STAGE1
|
||||
|
||||
VQVAE_END=$(date +%s)
|
||||
VQVAE_MIN=$(( (VQVAE_END - VQVAE_START) / 60 ))
|
||||
log "Stage 1 complete in ${VQVAE_MIN} min"
|
||||
|
||||
# ── Stage 2: Transformer retraining ──────────────────────────────────────────
|
||||
log "=== Stage 2: Transformer retraining (200 epochs, 8×A100) ==="
|
||||
XFMR_START=$(date +%s)
|
||||
|
||||
ssh $SSH_OPTS "$REMOTE" bash << 'REMOTE_STAGE2'
|
||||
set -euo pipefail
|
||||
source /opt/conda/etc/profile.d/conda.sh
|
||||
conda activate occworld
|
||||
|
||||
export PYTHONPATH="$PYTHONPATH:$HOME/OccWorld:$HOME/ruview-scripts"
|
||||
mkdir -p ~/checkpoints/transformer
|
||||
|
||||
# Locate the latest VQVAE checkpoint
|
||||
VQVAE_CKPT=$(ls -t ~/checkpoints/vqvae/*.pth 2>/dev/null | head -1)
|
||||
if [[ -z "$VQVAE_CKPT" ]]; then
|
||||
echo "[stage2] ERROR: No VQVAE checkpoint found in ~/checkpoints/vqvae/" >&2
|
||||
exit 1
|
||||
fi
|
||||
echo "[stage2] Using VQVAE checkpoint: $VQVAE_CKPT"
|
||||
echo "[stage2] $(date): starting Transformer torchrun"
|
||||
|
||||
torchrun \
|
||||
--nproc_per_node=8 \
|
||||
--master_port=29501 \
|
||||
~/ruview-scripts/occworld_retrain.py transformer \
|
||||
--snapshots /tmp/snapshots/ \
|
||||
--vqvae-checkpoint "$VQVAE_CKPT" \
|
||||
--work-dir ~/checkpoints/transformer \
|
||||
--epochs 200
|
||||
|
||||
echo "[stage2] $(date): Transformer training complete"
|
||||
ls -lh ~/checkpoints/transformer/
|
||||
REMOTE_STAGE2
|
||||
|
||||
XFMR_END=$(date +%s)
|
||||
XFMR_MIN=$(( (XFMR_END - XFMR_START) / 60 ))
|
||||
log "Stage 2 complete in ${XFMR_MIN} min"
|
||||
|
||||
# ── Download checkpoints ──────────────────────────────────────────────────────
|
||||
log "Downloading checkpoints → $OUTPUT_DIR ..."
|
||||
mkdir -p "$OUTPUT_DIR"
|
||||
|
||||
rsync -avz --progress --stats \
|
||||
-e "ssh $SSH_OPTS" \
|
||||
"${REMOTE}:${REMOTE_CHECKPOINTS}/" \
|
||||
"$OUTPUT_DIR/"
|
||||
|
||||
# Verify download
|
||||
LOCAL_FILE_COUNT=$(find "$OUTPUT_DIR" -type f | wc -l)
|
||||
LOCAL_SIZE_MB=$(du -sm "$OUTPUT_DIR" 2>/dev/null | awk '{print $1}')
|
||||
log "Downloaded $LOCAL_FILE_COUNT files, ~${LOCAL_SIZE_MB} MB to $OUTPUT_DIR"
|
||||
|
||||
if [[ "$LOCAL_FILE_COUNT" -lt 2 ]]; then
|
||||
echo "WARNING: Expected at least one checkpoint per stage (got $LOCAL_FILE_COUNT files)" >&2
|
||||
fi
|
||||
|
||||
# ── Summary ───────────────────────────────────────────────────────────────────
|
||||
TOTAL_MIN=$(( (XFMR_END - VQVAE_START) / 60 ))
|
||||
TOTAL_HR=$(awk "BEGIN {printf \"%.2f\", $TOTAL_MIN / 60}")
|
||||
COST=$(awk "BEGIN {printf \"%.2f\", 29.39 * $TOTAL_HR}")
|
||||
log ""
|
||||
log "=== Training complete ==="
|
||||
log " Stage 1 (VQVAE) : ${VQVAE_MIN} min"
|
||||
log " Stage 2 (Transformer): ${XFMR_MIN} min"
|
||||
log " Total wall time : ${TOTAL_MIN} min (${TOTAL_HR} hr)"
|
||||
log " Estimated compute cost: ~\$$COST (at \$29.39/hr on-demand)"
|
||||
log " Checkpoints in : $OUTPUT_DIR"
|
||||
log ""
|
||||
log "Next steps:"
|
||||
log " Teardown: bash scripts/gcp/teardown.sh <INSTANCE_NAME>"
|
||||
log " Evaluate: bash scripts/gcp/cosmos_eval.sh <COSMOS_INSTANCE_IP>"
|
||||
Executable
+211
@@ -0,0 +1,211 @@
|
||||
#!/usr/bin/env bash
|
||||
# Safely teardown a GCP training or evaluation instance
|
||||
# Usage: bash scripts/gcp/teardown.sh <INSTANCE_NAME> [--zone <ZONE>] [--skip-download]
|
||||
#
|
||||
# Downloads all checkpoints/results to ./out/gcp-checkpoints/<instance-name>/,
|
||||
# verifies the download, then deletes the instance.
|
||||
# GCP project: cognitum-20260110
|
||||
|
||||
set -euo pipefail
|
||||
|
||||
# ── Usage ─────────────────────────────────────────────────────────────────────
|
||||
if [[ $# -lt 1 ]]; then
|
||||
echo "Usage: $0 <INSTANCE_NAME> [--zone <ZONE>] [--skip-download]" >&2
|
||||
echo ""
|
||||
echo " INSTANCE_NAME Name of the GCP instance to teardown"
|
||||
echo " --zone GCP zone (default: auto-detected)"
|
||||
echo " --skip-download Delete instance without downloading checkpoints"
|
||||
echo ""
|
||||
echo "Example:"
|
||||
echo " $0 occworld-train-20260529"
|
||||
echo " $0 cosmos-eval-20260529 --zone us-east1-b"
|
||||
exit 1
|
||||
fi
|
||||
|
||||
INSTANCE_NAME="$1"
|
||||
shift
|
||||
|
||||
PROJECT="cognitum-20260110"
|
||||
ZONE=""
|
||||
SKIP_DOWNLOAD=false
|
||||
|
||||
while [[ $# -gt 0 ]]; do
|
||||
case "$1" in
|
||||
--zone) ZONE="$2"; shift 2 ;;
|
||||
--skip-download) SKIP_DOWNLOAD=true; shift ;;
|
||||
-h|--help)
|
||||
echo "Usage: $0 <INSTANCE_NAME> [--zone <ZONE>] [--skip-download]"
|
||||
exit 0
|
||||
;;
|
||||
*)
|
||||
echo "Unknown argument: $1" >&2
|
||||
exit 1
|
||||
;;
|
||||
esac
|
||||
done
|
||||
|
||||
OUTPUT_BASE="./out/gcp-checkpoints"
|
||||
OUTPUT_DIR="${OUTPUT_BASE}/${INSTANCE_NAME}"
|
||||
GCP_USER="${GCP_USER:-$(gcloud config get-value account 2>/dev/null | cut -d@ -f1)}"
|
||||
SSH_OPTS="-o StrictHostKeyChecking=no -o ConnectTimeout=20 -o BatchMode=yes"
|
||||
|
||||
log() { echo "[teardown] $*"; }
|
||||
|
||||
# ── Check instance exists ─────────────────────────────────────────────────────
|
||||
log "Looking up instance $INSTANCE_NAME in project $PROJECT ..."
|
||||
|
||||
if [[ -z "$ZONE" ]]; then
|
||||
# Auto-detect zone
|
||||
ZONE=$(gcloud compute instances list \
|
||||
--project="$PROJECT" \
|
||||
--filter="name=$INSTANCE_NAME" \
|
||||
--format="value(zone)" 2>/dev/null | head -1)
|
||||
if [[ -z "$ZONE" ]]; then
|
||||
echo "ERROR: Instance '$INSTANCE_NAME' not found in project $PROJECT" >&2
|
||||
echo " Check: gcloud compute instances list --project=$PROJECT" >&2
|
||||
exit 1
|
||||
fi
|
||||
# Strip the full zone URL to just the zone name
|
||||
ZONE=$(basename "$ZONE")
|
||||
fi
|
||||
|
||||
STATUS=$(gcloud compute instances describe "$INSTANCE_NAME" \
|
||||
--project="$PROJECT" \
|
||||
--zone="$ZONE" \
|
||||
--format="value(status)" 2>/dev/null || echo "NOT_FOUND")
|
||||
|
||||
if [[ "$STATUS" == "NOT_FOUND" ]]; then
|
||||
echo "ERROR: Instance '$INSTANCE_NAME' not found in zone $ZONE" >&2
|
||||
exit 1
|
||||
fi
|
||||
|
||||
log "Found: $INSTANCE_NAME (zone=$ZONE, status=$STATUS)"
|
||||
|
||||
# ── Get instance IP and uptime ────────────────────────────────────────────────
|
||||
INSTANCE_IP=$(gcloud compute instances describe "$INSTANCE_NAME" \
|
||||
--project="$PROJECT" --zone="$ZONE" \
|
||||
--format="value(networkInterfaces[0].accessConfigs[0].natIP)" 2>/dev/null || echo "")
|
||||
|
||||
CREATION_TS=$(gcloud compute instances describe "$INSTANCE_NAME" \
|
||||
--project="$PROJECT" --zone="$ZONE" \
|
||||
--format="value(creationTimestamp)" 2>/dev/null || echo "")
|
||||
|
||||
# ── Uptime and cost estimate ──────────────────────────────────────────────────
|
||||
if [[ -n "$CREATION_TS" ]]; then
|
||||
CREATION_EPOCH=$(date -d "$CREATION_TS" +%s 2>/dev/null || echo "0")
|
||||
NOW_EPOCH=$(date +%s)
|
||||
UPTIME_SEC=$(( NOW_EPOCH - CREATION_EPOCH ))
|
||||
UPTIME_HR=$(awk "BEGIN {printf \"%.2f\", $UPTIME_SEC / 3600}")
|
||||
|
||||
# Determine cost rate by machine type
|
||||
MACHINE_TYPE=$(gcloud compute instances describe "$INSTANCE_NAME" \
|
||||
--project="$PROJECT" --zone="$ZONE" \
|
||||
--format="value(machineType)" 2>/dev/null | basename)
|
||||
|
||||
case "$MACHINE_TYPE" in
|
||||
a2-highgpu-8g) RATE="29.39" ;;
|
||||
a2-ultragpu-1g) RATE="5.08" ;;
|
||||
a2-highgpu-1g) RATE="3.67" ;;
|
||||
*) RATE="10.00" ;;
|
||||
esac
|
||||
|
||||
TOTAL_COST=$(awk "BEGIN {printf \"%.2f\", $RATE * $UPTIME_HR}")
|
||||
log "Uptime : ${UPTIME_HR} hr (${UPTIME_SEC}s)"
|
||||
log "Machine : $MACHINE_TYPE (~\$$RATE/hr)"
|
||||
log "Est cost: ~\$$TOTAL_COST"
|
||||
fi
|
||||
|
||||
# ── Download checkpoints / results ───────────────────────────────────────────
|
||||
if [[ "$SKIP_DOWNLOAD" == "false" ]] && [[ -n "$INSTANCE_IP" ]] && [[ "$STATUS" == "RUNNING" ]]; then
|
||||
log "Downloading checkpoints/results → $OUTPUT_DIR ..."
|
||||
mkdir -p "$OUTPUT_DIR"
|
||||
|
||||
REMOTE="${GCP_USER}@${INSTANCE_IP}"
|
||||
|
||||
# Determine what to download based on instance name prefix
|
||||
if [[ "$INSTANCE_NAME" == occworld-* ]]; then
|
||||
log "Training instance — downloading ~/checkpoints/"
|
||||
rsync -avz --progress \
|
||||
-e "ssh $SSH_OPTS" \
|
||||
"${REMOTE}:~/checkpoints/" \
|
||||
"$OUTPUT_DIR/checkpoints/" \
|
||||
|| { echo "WARNING: rsync failed — some files may not have downloaded" >&2; }
|
||||
|
||||
elif [[ "$INSTANCE_NAME" == cosmos-* ]]; then
|
||||
log "Eval instance — downloading ~/cosmos-results/"
|
||||
rsync -avz --progress \
|
||||
-e "ssh $SSH_OPTS" \
|
||||
"${REMOTE}:~/cosmos-results/" \
|
||||
"$OUTPUT_DIR/cosmos-results/" \
|
||||
|| { echo "WARNING: rsync failed — some files may not have downloaded" >&2; }
|
||||
|
||||
else
|
||||
log "Unknown instance type — downloading ~/checkpoints/ and ~/cosmos-results/ (if they exist)"
|
||||
rsync -avz --progress \
|
||||
-e "ssh $SSH_OPTS" \
|
||||
"${REMOTE}:~/checkpoints/" \
|
||||
"$OUTPUT_DIR/checkpoints/" \
|
||||
2>/dev/null || true
|
||||
rsync -avz --progress \
|
||||
-e "ssh $SSH_OPTS" \
|
||||
"${REMOTE}:~/cosmos-results/" \
|
||||
"$OUTPUT_DIR/cosmos-results/" \
|
||||
2>/dev/null || true
|
||||
fi
|
||||
|
||||
# ── Verify download ─────────────────────────────────────────────────────────
|
||||
LOCAL_FILE_COUNT=$(find "$OUTPUT_DIR" -type f 2>/dev/null | wc -l)
|
||||
LOCAL_SIZE=$(du -sh "$OUTPUT_DIR" 2>/dev/null | awk '{print $1}')
|
||||
log "Download verification:"
|
||||
log " Files : $LOCAL_FILE_COUNT"
|
||||
log " Size : $LOCAL_SIZE"
|
||||
log " Path : $OUTPUT_DIR"
|
||||
|
||||
if [[ "$LOCAL_FILE_COUNT" -lt 1 ]]; then
|
||||
echo "WARNING: No files were downloaded from $REMOTE" >&2
|
||||
echo " Proceeding with deletion — use --skip-download to bypass download entirely." >&2
|
||||
read -r -p "Continue with instance deletion? [y/N] " CONFIRM
|
||||
if [[ "$CONFIRM" != "y" && "$CONFIRM" != "Y" ]]; then
|
||||
log "Teardown aborted — instance NOT deleted"
|
||||
exit 0
|
||||
fi
|
||||
fi
|
||||
|
||||
elif [[ "$SKIP_DOWNLOAD" == "true" ]]; then
|
||||
log "Skipping checkpoint download (--skip-download)"
|
||||
elif [[ "$STATUS" != "RUNNING" ]]; then
|
||||
log "Instance is $STATUS — cannot rsync; skipping download"
|
||||
fi
|
||||
|
||||
# ── Confirm deletion ──────────────────────────────────────────────────────────
|
||||
echo ""
|
||||
log "About to DELETE instance: $INSTANCE_NAME (zone=$ZONE, project=$PROJECT)"
|
||||
if [[ "$LOCAL_FILE_COUNT" -gt 0 ]] || [[ "$SKIP_DOWNLOAD" == "true" ]]; then
|
||||
log "Checkpoints are saved locally at: $OUTPUT_DIR"
|
||||
fi
|
||||
echo ""
|
||||
read -r -p "[teardown] Confirm deletion of '$INSTANCE_NAME'? [y/N] " CONFIRM
|
||||
if [[ "$CONFIRM" != "y" && "$CONFIRM" != "Y" ]]; then
|
||||
log "Teardown aborted — instance NOT deleted"
|
||||
exit 0
|
||||
fi
|
||||
|
||||
# ── Delete instance ───────────────────────────────────────────────────────────
|
||||
log "Deleting instance $INSTANCE_NAME ..."
|
||||
gcloud compute instances delete "$INSTANCE_NAME" \
|
||||
--project="$PROJECT" \
|
||||
--zone="$ZONE" \
|
||||
--quiet
|
||||
|
||||
log "Instance deleted successfully"
|
||||
|
||||
# ── Final cost summary ────────────────────────────────────────────────────────
|
||||
log ""
|
||||
log "=== Teardown complete ==="
|
||||
if [[ -n "${TOTAL_COST:-}" ]]; then
|
||||
log "Final cost estimate: ~\$$TOTAL_COST (${UPTIME_HR} hr × \$$RATE/hr for $MACHINE_TYPE)"
|
||||
fi
|
||||
if [[ "$SKIP_DOWNLOAD" == "false" ]] && [[ -d "$OUTPUT_DIR" ]]; then
|
||||
log "Checkpoints at : $OUTPUT_DIR"
|
||||
log "Files kept : $LOCAL_FILE_COUNT (${LOCAL_SIZE})"
|
||||
fi
|
||||
Reference in New Issue
Block a user