UIPress / scripts /run_ablation_queue_gpu1.sh
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#!/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')."