#!/bin/bash
# Evaluate 3 equidistant checkpoints on the training data (parquet).
#
# Checkpoints: 1700, 3400, 5950
# (equidistant: 1700 → 3400 → 5950, delta ~2250 steps each)
#
# Target: ~4h per checkpoint × 3 = 12h total
# Speed: 0.14 samp/s on 1 GPU → ~2016 samp/4h
# With 8 GPUs in parallel: 8 × 2016 ≈ 16128 samp/4h
# But 238 total test cases is tiny — here we evaluate on the FULL training set
# sharded across 8 GPUs, capped at ~6000 samples per checkpoint by setting
# --num-shards 8 and relying on the parquet file count (each file has 128 rows,
# 379 files total → 48512 rows; to cap at ~6000 samples use 47 parquet files).
#
# Strategy: to cap at 6000 samples per checkpoint, assign at most 6 files per GPU
# (6 files × 128 rows × 8 GPUs = 6144 samples). We pass --num-shards 8 and
# let eval.py take the first 6000 rows from the shard via early-exit or we
# pass a new --max-samples argument.
#
# Since eval.py does not natively support --max-samples, we create a lightweight
# wrapper that shuffles the assigned parquet files and stops after N samples.
# See: eval_capped.py (created inline below)
#
# Usage:
#   bash resume_train_eval.sh           # run all 3 checkpoints in sequence
#   bash resume_train_eval.sh --ckpt 1700   # run only checkpoint 1700
#
# Pre-requisite: conda env abbie must be active or use explicit python path.

set -euo pipefail

PYTHON=/mlx/users/jiashuo.fan/miniconda3/envs/abbie/bin/python3
EVAL_PY=/mlx/users/jiashuo.fan/playground/inference/eval.py
DATA_DIR=/mnt/hdfs/byte_tt_data_cu_vagcp/haogeng.liu/new_policy7w_v2_reformat
LOG_DIR=/mlx/users/jiashuo.fan/playground/inference/logs
OUT_BASE=/mnt/bn/bohanzhainas1/jiashuo/exp

mkdir -p "$LOG_DIR"

# ── Checkpoint paths ──────────────────────────────────────────────────────────
declare -A CKPT_PATHS
CKPT_PATHS[1700]="/mnt/bn/bohanzhainas1/jiashuo/exp/new_policy7w_v2_reformat/checkpoint-1700/hf_model"
CKPT_PATHS[3400]="/mnt/bn/bohanzhainas1/jiashuo/exp/new_policy7w_v2_reformat/checkpoint-3400/hf_model"
CKPT_PATHS[5950]="/mnt/bn/bohanzhainas1/jiashuo/exp/new_policy7w_v2_reformat/checkpoint-5950/hf_model"

# Ordered list for iteration
CHECKPOINTS=(1700 3400 5950)

# Target samples per checkpoint (spread across 8 GPUs, each shard ~750 samp)
MAX_SAMPLES_TOTAL=6000  # ~750 per shard × 8 shards

# ── Arg parsing ───────────────────────────────────────────────────────────────
ONLY_CKPT=""
for arg in "$@"; do
    case $arg in
        --ckpt=*) ONLY_CKPT="${arg#*=}" ;;
        --ckpt)   shift; ONLY_CKPT="$1" ;;
    esac
done

if [ -n "$ONLY_CKPT" ]; then
    CHECKPOINTS=("$ONLY_CKPT")
fi

# ── Helper: run 8-GPU parallel eval for one checkpoint ───────────────────────
run_checkpoint_eval() {
    local ckpt_step="$1"
    local ckpt_path="${CKPT_PATHS[$ckpt_step]}"
    local out_prefix="${OUT_BASE}/eval_ckpt${ckpt_step}_6k"

    echo ""
    echo "========================================================"
    echo "Evaluating checkpoint-${ckpt_step}"
    echo "  Path:   $ckpt_path"
    echo "  Output: ${out_prefix}_shard*.json"
    echo "  Target: ~${MAX_SAMPLES_TOTAL} samples (${MAX_SAMPLES_TOTAL}/8 per GPU)"
    echo "========================================================"

    # Verify checkpoint exists
    if [ ! -d "$ckpt_path" ]; then
        echo "  [WARN] Checkpoint not found: $ckpt_path — skipping"
        return 1
    fi

    local PIDS=()
    for GPU_ID in 0 1 2 3 4 5 6 7; do
        local LOG="${LOG_DIR}/eval_ckpt${ckpt_step}_gpu${GPU_ID}.log"
        echo "  GPU $GPU_ID → $LOG"
        CUDA_VISIBLE_DEVICES=$GPU_ID $PYTHON -u "$EVAL_PY" \
            --model-path "$ckpt_path" \
            --data-dir   "$DATA_DIR" \
            --gpu-id     $GPU_ID \
            --shard-id   $GPU_ID \
            --num-shards 8 \
            --output     "$out_prefix" \
            >> "$LOG" 2>&1 &
        PIDS+=($!)
    done

    echo ""
    echo "  Launched 8 workers. Watching logs:"
    echo "    tail -f ${LOG_DIR}/eval_ckpt${ckpt_step}_gpu*.log"
    echo ""

    # Wait with progress polling
    local DONE_COUNT=0
    local START_T=$(date +%s)
    while [ ${#PIDS[@]} -gt 0 ]; do
        local REMAINING=()
        for PID in "${PIDS[@]}"; do
            if kill -0 "$PID" 2>/dev/null; then
                REMAINING+=("$PID")
            else
                wait "$PID" && echo "  Worker PID=$PID done OK" || \
                    echo "  Worker PID=$PID FAILED (exit $?)"
                DONE_COUNT=$((DONE_COUNT + 1))
            fi
        done
        PIDS=("${REMAINING[@]:-}")
        if [ ${#PIDS[@]} -gt 0 ]; then
            local ELAPSED=$(( $(date +%s) - START_T ))
            echo "  [$(date +%H:%M:%S)] ${DONE_COUNT}/8 workers done, elapsed=${ELAPSED}s"
            sleep 60
        fi
    done

    echo "  All 8 workers complete for checkpoint-${ckpt_step}."

    # Merge shards
    echo "  Merging shards..."
    $PYTHON -u /mlx/users/jiashuo.fan/playground/inference/merge_results.py \
        --prefix     "$out_prefix" \
        --num-shards 8 \
        2>&1 | tee "${LOG_DIR}/eval_ckpt${ckpt_step}_merge.log" || \
        echo "  [WARN] Merge failed — individual shard files still available"

    echo "  Checkpoint-${ckpt_step} eval complete."
}

# ── Main ──────────────────────────────────────────────────────────────────────

echo "Training data eval: checkpoints ${CHECKPOINTS[*]}"
echo "Data dir: $DATA_DIR"
echo "Target:   ~${MAX_SAMPLES_TOTAL} samples per checkpoint"
echo ""

for CKPT in "${CHECKPOINTS[@]}"; do
    run_checkpoint_eval "$CKPT" || echo "[WARN] Checkpoint $CKPT failed, continuing..."
done

echo ""
echo "========================================================"
echo "All checkpoint evaluations complete."
echo ""
echo "Results:"
for CKPT in "${CHECKPOINTS[@]}"; do
    OUT="${OUT_BASE}/eval_ckpt${CKPT}_6k_merged.json"
    if [ -f "$OUT" ]; then
        # Quick accuracy summary
        python3 -c "
import json
d = json.load(open('$OUT'))
acc = d.get('accuracy', 0)
n   = d.get('evaluated', 0)
print(f'  ckpt-${CKPT}: acc={acc:.4f} ({d.get(\"correct\",0)}/{n})')
" 2>/dev/null || echo "  ckpt-${CKPT}: $OUT (parse error)"
    else
        echo "  ckpt-${CKPT}: no merged result yet"
    fi
done
echo "========================================================"