#!/usr/bin/env bash
# Hyperparameter sweep for dev3 (MotionCache) and dev4 (MotionDetailCache).
set -euo pipefail

GPU_ID="${CUDA_VISIBLE_DEVICES:-1}"
SWEEP_FRAMES="${SWEEP_FRAMES:-120}"
PROMPT="${PROMPT:-a woman dancing.}"
BASELINE="/home/dyvm6xra/dyvm6xrauser11/workspace/cz/FlowCache/FlowCache4MAGI-1/outputs/a_woman_dancing_2026-05-19_09-49-14/output_2026-05-19_09-49-14.mp4"
FLOWCACHE_ROOT="/home/dyvm6xra/dyvm6xrauser11/workspace/cz/FlowCache/FlowCache4MAGI-1-dev3-motion"
DETAIL_ROOT="/home/dyvm6xra/dyvm6xrauser11/workspace/cz/FlowCache/FlowCache4MAGI-1-dev4-detail"
SWEEP_ROOT="${SWEEP_ROOT:-$FLOWCACHE_ROOT/outputs/hparam_sweep_$(date +%Y%m%d_%H%M%S)}"
REPORT_DIR="$SWEEP_ROOT/report"
mkdir -p "$REPORT_DIR"

export MASTER_ADDR=localhost
export CUDA_VISIBLE_DEVICES="$GPU_ID"
export PYTHONPATH="${FLOWCACHE_ROOT}:${DETAIL_ROOT}:${PYTHONPATH:-}"
export PAD_HQ=1
export PAD_DURATION=1
export PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True
export OFFLOAD_T5_CACHE=true
export OFFLOAD_VAE_CACHE=true

if [ -z "${CONDA_DEFAULT_ENV:-}" ] || [ "${CONDA_DEFAULT_ENV}" != "magi" ]; then
    # shellcheck disable=SC1091
    source "${HOME}/miniforge3/etc/profile.d/conda.sh" 2>/dev/null || source "${HOME}/anaconda3/etc/profile.d/conda.sh"
    conda activate magi
fi

ensure_numpy_compat() {
    if ! python3 - <<'PY'
import numpy as np
major = int(np.__version__.split(".")[0])
raise SystemExit(0 if major < 2 else 1)
PY
    then
        echo "Fixing numpy for transformers (found incompatible version)..."
        pip install -q "numpy>=1.24,<2.0"
    fi
}
ensure_numpy_compat

make_runtime_config() {
    local dst="$1" frames="$2"
    python3 - "$dst" "$frames" <<'PY'
import json, sys
dst, frames = sys.argv[1], int(sys.argv[2])
src = "/home/dyvm6xra/dyvm6xrauser11/workspace/cz/FlowCache/FlowCache4MAGI-1-dev3-motion/config/single_run/flowcache_t2v.json"
with open(src) as f:
    cfg = json.load(f)
cfg["runtime_config"]["num_frames"] = frames
with open(dst, "w") as f:
    json.dump(cfg, f, indent=4)
PY
}

RUNTIME_CFG="$SWEEP_ROOT/runtime_${SWEEP_FRAMES}f.json"
make_runtime_config "$RUNTIME_CFG" "$SWEEP_FRAMES"
echo "Sweep output: $SWEEP_ROOT (num_frames=$SWEEP_FRAMES, GPU=$GPU_ID, host=$(hostname))"

RESULTS_CSV="$REPORT_DIR/results.csv"
echo "variant,version,tau,alpha,detail_alpha,detail_window,combine_mode,detail_lambda,psnr_db,ssim,black_ratio,reuse_rate_pct,wall_sec,peak_gb,video_path,log_path" > "$RESULTS_CSV"

run_one() {
    local version="$1" run_id="$2" yaml_path="$3" root_dir="$4"
    local exp_dir="$SWEEP_ROOT/${version}_${run_id}"
    mkdir -p "$exp_dir"
    local out="$exp_dir/output.mp4"
    local log="$exp_dir/infer.log"
    local metric="$exp_dir/metrics.json"
    local t0 t1 elapsed

    export MASTER_PORT=$((6000 + RANDOM % 500))
    if [ "$root_dir" = "$DETAIL_ROOT" ]; then
        export PYTHONPATH="${DETAIL_ROOT}:${FLOWCACHE_ROOT}:${PYTHONPATH:-}"
    else
        export PYTHONPATH="${FLOWCACHE_ROOT}:${DETAIL_ROOT}:${PYTHONPATH:-}"
    fi

    echo ""
    echo "========== [$version] $run_id =========="
    t0=$(date +%s)
    set +e
    (
        cd "$root_dir"
        python3 inference/pipeline/motioncache.py \
            --config_file "$RUNTIME_CFG" \
            --mode t2v \
            --prompt "$PROMPT" \
            --output_path "$out" \
            --additional_config "$yaml_path" \
            --motioncache_metric_stats_path "$metric" \
            2>&1 | tee "$log"
    )
    local rc=${PIPESTATUS[0]}
    set -e
    t1=$(date +%s)
    elapsed=$((t1 - t0))

    if [ ! -f "$out" ] || [ "$rc" -ne 0 ]; then
        echo "FAILED: $run_id (rc=$rc, no video)"
        return 1
    fi

    eval_out=$(python3 "$FLOWCACHE_ROOT/tools/eval_run.py" \
        --baseline "$BASELINE" \
        --generated "$out" \
        --log "$log" \
        --metric "$metric" 2>/dev/null || true)
    PSNR="NA"; SSIM="NA"; BLACK="NA"; REUSE="NA"; PEAK="NA"
    while IFS='=' read -r k v; do
        case "$k" in PSNR) PSNR="$v" ;; SSIM) SSIM="$v" ;; BLACK) BLACK="$v" ;; REUSE) REUSE="$v" ;; PEAK) PEAK="$v" ;; esac
    done <<< "$eval_out"
    echo "$run_id,$version,$TAU,$ALPHA,$DETAIL_ALPHA,$DETAIL_WINDOW,$COMBINE,$DETAIL_LAM,$PSNR,$SSIM,$BLACK,$REUSE,$elapsed,$PEAK,$out,$log" >> "$RESULTS_CSV"
    echo "  PSNR=${PSNR}dB reuse=${REUSE}% time=${elapsed}s"
}

write_yaml() {
    local path="$1"
    shift
    python3 - "$path" "$@" <<'PY'
import sys, yaml
path = sys.argv[1]
params = {}
for kv in sys.argv[2:]:
    k, v = kv.split("=", 1)
    if v.lower() in ("true", "false"):
        params[k] = v.lower() == "true"
    elif v.replace(".", "", 1).isdigit():
        params[k] = float(v) if "." in v else int(v)
    else:
        params[k] = v
base = {
    "warmup_steps": 5,
    "phase1_steps": 9,
    "alpha": 0.5,
    "discard_nearly_clean_chunk": True,
    "compress_kv_cache": True,
    "total_cache_chunk_nums": 5,
    "compress_strategy": "token",
    "mix_lambda": 0.07,
    "query_granularity": "frame",
    "score_weighting_method": "no_weight",
    "power": 3,
    "log": False,
    "print_peak_memory": True,
}
base.update(params)
with open(path, "w") as f:
    yaml.dump(base, f, default_flow_style=False)
PY
}

# ---------- Phase 1: dev3 tau sweep ----------
BEST_DEV3_TAU="0.015"

for tau in 0.010 0.012 0.015 0.018 0.020 0.025 0.030; do
    y="$SWEEP_ROOT/dev3_tau${tau}.yaml"
    write_yaml "$y" "rel_l1_thresh=$tau"
    export TAU="$tau" ALPHA="0.5" DETAIL_ALPHA="" DETAIL_WINDOW="" COMBINE="" DETAIL_LAM=""
    run_one "dev3" "tau${tau}" "$y" "$FLOWCACHE_ROOT" || true
done

BEST_DEV3_TAU=$(python3 - "$RESULTS_CSV" <<'PY'
import csv, sys
rows = [r for r in csv.DictReader(open(sys.argv[1])) if r["version"] == "dev3" and r["psnr_db"] not in ("NA", "")]
if not rows:
    print("0.015")
else:
    def score(r):
        psnr = float(r["psnr_db"]) if r["psnr_db"] != "inf" else 100.0
        reuse = float(r["reuse_rate_pct"] or 0)
        return psnr + 0.02 * reuse
    print(max(rows, key=score)["tau"])
PY
)
echo "Best dev3 tau from sweep: $BEST_DEV3_TAU"

# ---------- Phase 2: dev4 detail sweep ----------
for spec in \
    "max|3|0.5|0.5" \
    "max|5|0.5|0.5" \
    "max|3|0.4|0.5" \
    "max|3|0.6|0.5" \
    "blend|3|0.5|0.3" \
    "blend|3|0.5|0.5" \
    "blend|3|0.5|0.7" \
    "product|3|0.5|0.5" \
    "product|5|0.5|0.5"; do
    IFS='|' read -r mode win da lam <<< "$spec"
    rid="tau${BEST_DEV3_TAU}_${mode}_w${win}_da${da}_lam${lam}"
    y="$SWEEP_ROOT/dev4_${rid}.yaml"
    write_yaml "$y" \
        "rel_l1_thresh=$BEST_DEV3_TAU" \
        "detail_alpha=$da" \
        "detail_window_size=$win" \
        "weight_combine_mode=$mode" \
        "detail_lambda=$lam"
    export TAU="$BEST_DEV3_TAU" ALPHA="0.5" DETAIL_ALPHA="$da" DETAIL_WINDOW="$win" COMBINE="$mode" DETAIL_LAM="$lam"
    run_one "dev4" "$rid" "$y" "$DETAIL_ROOT" || true
done

# ---------- Phase 3: 240-frame validation ----------
RUNTIME_CFG="$SWEEP_ROOT/runtime_240f.json"
make_runtime_config "$RUNTIME_CFG" 240
echo "Full validation at 240 frames..."

DEV3_COUNT=$(python3 - "$RESULTS_CSV" <<'PY'
import csv, sys
print(sum(1 for r in csv.DictReader(open(sys.argv[1])) if r["version"] == "dev3" and r["psnr_db"] not in ("NA", "")))
PY
)
DEV4_COUNT=$(python3 - "$RESULTS_CSV" <<'PY'
import csv, sys
print(sum(1 for r in csv.DictReader(open(sys.argv[1])) if r["version"] == "dev4" and r["psnr_db"] not in ("NA", "")))
PY
)

if [ "$DEV3_COUNT" -gt 0 ]; then
    BEST_DEV3_ID=$(python3 - "$RESULTS_CSV" <<'PY'
import csv, sys
rows = [r for r in csv.DictReader(open(sys.argv[1])) if r["version"] == "dev3" and r["psnr_db"] not in ("NA", "")]
def score(r):
    psnr = float(r["psnr_db"]) if r["psnr_db"] != "inf" else 100.0
    return psnr + 0.02 * float(r["reuse_rate_pct"] or 0)
print(max(rows, key=score)["variant"])
PY
)
    y3="$SWEEP_ROOT/dev3_${BEST_DEV3_ID}_full.yaml"
    write_yaml "$y3" "rel_l1_thresh=${BEST_DEV3_TAU}"
    export TAU="$BEST_DEV3_TAU" ALPHA="0.5" DETAIL_ALPHA="" DETAIL_WINDOW="" COMBINE="" DETAIL_LAM=""
    run_one "dev3_full" "${BEST_DEV3_ID}_240f" "$y3" "$FLOWCACHE_ROOT" || true
fi

if [ "$DEV4_COUNT" -gt 0 ]; then
    read -r y4 da dw cm dl BEST_DEV4_ID <<< "$(python3 - "$RESULTS_CSV" "$SWEEP_ROOT" "$BEST_DEV3_TAU" <<'PY'
import csv, sys, yaml, os
csv_path, sweep_root, tau = sys.argv[1:4]
rows = [r for r in csv.DictReader(open(csv_path)) if r["version"] == "dev4" and r["psnr_db"] not in ("NA", "")]
def score(r):
    psnr = float(r["psnr_db"]) if r["psnr_db"] != "inf" else 100.0
    return psnr + 0.02 * float(r["reuse_rate_pct"] or 0)
row = max(rows, key=score)
y = {
    "rel_l1_thresh": float(tau),
    "warmup_steps": 5, "phase1_steps": 9, "alpha": 0.5,
    "detail_alpha": float(row["detail_alpha"]),
    "detail_window_size": int(float(row["detail_window"])),
    "weight_combine_mode": row["combine_mode"],
    "detail_lambda": float(row["detail_lambda"]),
    "discard_nearly_clean_chunk": True,
    "compress_kv_cache": True, "total_cache_chunk_nums": 5,
    "compress_strategy": "token", "mix_lambda": 0.07,
    "query_granularity": "frame", "score_weighting_method": "no_weight",
    "power": 3, "log": False, "print_peak_memory": True,
}
path = os.path.join(sweep_root, f"dev4_{row['variant']}_full.yaml")
with open(path, "w") as f:
    yaml.dump(y, f, default_flow_style=False)
print(path, row["detail_alpha"], row["detail_window"], row["combine_mode"], row["detail_lambda"], row["variant"])
PY
)"
    export TAU="$BEST_DEV3_TAU" ALPHA="0.5" DETAIL_ALPHA="$da" DETAIL_WINDOW="$dw" COMBINE="$cm" DETAIL_LAM="$dl"
    run_one "dev4_full" "${BEST_DEV4_ID}_240f" "$y4" "$DETAIL_ROOT" || true
fi

python3 "$FLOWCACHE_ROOT/tools/generate_comparison_report.py" \
    --results "$RESULTS_CSV" \
    --baseline "$BASELINE" \
    --output "$REPORT_DIR/comparison_report.md" \
    --sweep_dir "$SWEEP_ROOT"

echo ""
echo "Sweep complete."
echo "  CSV: $RESULTS_CSV"
echo "  Report: $REPORT_DIR/comparison_report.md"