#!/usr/bin/env bash
set -euo pipefail

# One-GPU ablation queue (default GPU1).
# This script runs experiments sequentially and stores all artifacts under:
#   results/ablation_study/

ROOT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")/.." && pwd)"
cd "$ROOT_DIR"

GPU_ID="${GPU_ID:-1}"
EPOCHS_ABL="${EPOCHS_ABL:-5}"
MAX_SAMPLES="${MAX_SAMPLES:-10000}"
TOPK="${TOPK:-30}"

ABL_ROOT="results/ablation_study"
CKPT_DIR="$ABL_ROOT/checkpoints"
RUN_DIR="$ABL_ROOT/runs"
LOG_DIR="$ABL_ROOT/logs"

mkdir -p "$CKPT_DIR" "$RUN_DIR" "$LOG_DIR"

run() {
  local name="$1"
  shift
  echo
  echo "============================================================"
  echo "[$(date '+%F %T')] START: $name"
  echo "CMD: $*"
  echo "============================================================"
  "$@"
  echo "[$(date '+%F %T')] DONE: $name"
}

export PYTHONPATH=.

# 0) Figure-2 continuation: resume mix_d2c to epoch20 (if possible)
if [[ -f checkpoints/optical_mix_d2c/latest.pt ]]; then
  run "figure2_resume_to_e20" \
    env CUDA_VISIBLE_DEVICES="$GPU_ID" python scripts/train_compressor.py \
      --output_dir checkpoints/optical_mix_d2c \
      --resume checkpoints/optical_mix_d2c/latest.pt \
      --epochs 20 \
      --max_samples "$MAX_SAMPLES" \
      --mix_root data \
      --mix_images_subdir ref_screenshots \
      --mix_gt_subdir gt_html \
      --max_html_tokens 8192 \
      --eval_after_epoch \
      --eval_output_dir results/clip_per_epoch/optical_mix_d2c \
      --eval_clip_device cuda
fi

# 1) Remove LoRA ablation
run "train_no_lora_256" \
  env CUDA_VISIBLE_DEVICES="$GPU_ID" python scripts/train_compressor.py \
    --output_dir "$CKPT_DIR/no_lora_256" \
    --disable_lora \
    --target_tokens 256 \
    --epochs "$EPOCHS_ABL" \
    --max_samples "$MAX_SAMPLES" \
    --mix_root data \
    --mix_images_subdir ref_screenshots \
    --mix_gt_subdir gt_html \
    --max_html_tokens 8192

run "eval_no_lora_256" \
  env CUDA_VISIBLE_DEVICES="$GPU_ID" python scripts/eval_all.py \
    --method uipress \
    --checkpoint "$CKPT_DIR/no_lora_256/latest.pt" \
    --target_tokens 256 \
    --max_samples 50 \
    --data_dir data \
    --output_dir "$RUN_DIR/no_lora_256"

run "clip_no_lora_256" \
  env CUDA_VISIBLE_DEVICES="$GPU_ID" python scripts/step_clip_batch.py \
    --method_dir "$RUN_DIR/no_lora_256/uipress_256" \
    --ref_dir data/ref_screenshots \
    --clip_device cuda

# 2) Token sensitivity ablation
for tok in 64 128 512; do
  run "train_token_${tok}" \
    env CUDA_VISIBLE_DEVICES="$GPU_ID" python scripts/train_compressor.py \
      --output_dir "$CKPT_DIR/token_${tok}" \
      --target_tokens "$tok" \
      --epochs "$EPOCHS_ABL" \
      --max_samples "$MAX_SAMPLES" \
      --mix_root data \
      --mix_images_subdir ref_screenshots \
      --mix_gt_subdir gt_html \
      --max_html_tokens 8192

  run "eval_token_${tok}" \
    env CUDA_VISIBLE_DEVICES="$GPU_ID" python scripts/eval_all.py \
      --method uipress \
      --checkpoint "$CKPT_DIR/token_${tok}/latest.pt" \
      --target_tokens "$tok" \
      --max_samples 50 \
      --data_dir data \
      --output_dir "$RUN_DIR/token_${tok}"

  run "clip_token_${tok}" \
    env CUDA_VISIBLE_DEVICES="$GPU_ID" python scripts/step_clip_batch.py \
      --method_dir "$RUN_DIR/token_${tok}/uipress_${tok}" \
      --ref_dir data/ref_screenshots \
      --clip_device cuda
done

# 3) Learning-rate scan (compressor lr)
for lr in 1e-4 2e-4 4e-4; do
  safe_lr="${lr//./p}"
  run "train_lr_${safe_lr}" \
    env CUDA_VISIBLE_DEVICES="$GPU_ID" python scripts/train_compressor.py \
      --output_dir "$CKPT_DIR/lr_${safe_lr}" \
      --target_tokens 256 \
      --lr_compressor "$lr" \
      --epochs "$EPOCHS_ABL" \
      --max_samples "$MAX_SAMPLES" \
      --mix_root data \
      --mix_images_subdir ref_screenshots \
      --mix_gt_subdir gt_html \
      --max_html_tokens 8192

  run "eval_lr_${safe_lr}" \
    env CUDA_VISIBLE_DEVICES="$GPU_ID" python scripts/eval_all.py \
      --method uipress \
      --checkpoint "$CKPT_DIR/lr_${safe_lr}/latest.pt" \
      --target_tokens 256 \
      --max_samples 50 \
      --data_dir data \
      --output_dir "$RUN_DIR/lr_${safe_lr}"

  run "clip_lr_${safe_lr}" \
    env CUDA_VISIBLE_DEVICES="$GPU_ID" python scripts/step_clip_batch.py \
      --method_dir "$RUN_DIR/lr_${safe_lr}/uipress_256" \
      --ref_dir data/ref_screenshots \
      --clip_device cuda
done

# 4) Cross-domain validation (WebSight screenshots as eval set)
TMP_WEBSIGHT_DIR="$ABL_ROOT/tmp_websight_eval"
mkdir -p "$TMP_WEBSIGHT_DIR"
if [[ ! -e "$TMP_WEBSIGHT_DIR/ref_screenshots" ]]; then
  ln -s "$(realpath data/ref_screenshots_websight)" "$TMP_WEBSIGHT_DIR/ref_screenshots"
fi

run "cross_domain_qwen3_full" \
  env CUDA_VISIBLE_DEVICES="$GPU_ID" python scripts/eval_all.py \
    --method baseline \
    --max_samples 50 \
    --data_dir "$TMP_WEBSIGHT_DIR" \
    --output_dir "$RUN_DIR/cross_domain"

run "cross_domain_uipress_latest" \
  env CUDA_VISIBLE_DEVICES="$GPU_ID" python scripts/eval_all.py \
    --method uipress \
    --checkpoint checkpoints/optical_mix_d2c/latest.pt \
    --target_tokens 256 \
    --max_samples 50 \
    --data_dir "$TMP_WEBSIGHT_DIR" \
    --output_dir "$RUN_DIR/cross_domain"

run "cross_domain_clip_qwen3_full" \
  env CUDA_VISIBLE_DEVICES="$GPU_ID" python scripts/step_clip_batch.py \
    --method_dir "$RUN_DIR/cross_domain/qwen3_full" \
    --ref_dir data/ref_screenshots_websight \
    --clip_device cuda

run "cross_domain_clip_uipress_256" \
  env CUDA_VISIBLE_DEVICES="$GPU_ID" python scripts/step_clip_batch.py \
    --method_dir "$RUN_DIR/cross_domain/uipress_256" \
    --ref_dir data/ref_screenshots_websight \
    --clip_device cuda

# 5) Build Top-K report from current available methods
run "build_topk_report" \
  python scripts/ablation_topk_report.py \
    --topk "$TOPK" \
    --out_root "$ABL_ROOT"

echo
echo "All queue steps completed at $(date '+%F %T')."