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

SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
source "${SCRIPT_DIR}/../00_setup/env.sh"

: "${DEEPSTARR_DIR:?Set DEEPSTARR_DIR to the local DeepSTARR parquet directory.}"
: "${DIFFUSION_MODEL:?Set DIFFUSION_MODEL to the trained diffusion saved model directory.}"
: "${GENERANNO_BASE_MODEL:?Set GENERANNO_BASE_MODEL to the local GENERanno model.}"
: "${PREDICTOR_MODEL:?Set PREDICTOR_MODEL to the trained predictor best_model directory.}"

export NUM_PER_BUCKET="${NUM_PER_BUCKET:-128}"
export NUM_DIFFUSION_STEPS="${NUM_DIFFUSION_STEPS:-64}"
export DIFFUSION_EVAL_BATCH_SIZE="${DIFFUSION_EVAL_BATCH_SIZE:-512}"
export PREDICTOR_SCORE_BATCH_SIZE="${PREDICTOR_SCORE_BATCH_SIZE:-64}"

cd "${GENERANNO_DIR}"
python3 src/tasks/downstream/discrete_diffusion_evaluate.py \
  --diffusion_model "${DIFFUSION_MODEL}" \
  --base_model_for_code "${GENERANNO_BASE_MODEL}" \
  --dataset_dir "${DEEPSTARR_DIR}" \
  --predictor_model "${PREDICTOR_MODEL}" \
  --split test \
  --conditioned \
  --num_per_bucket "${NUM_PER_BUCKET}" \
  --sequence_length "${SEQUENCE_LENGTH:-246}" \
  --num_diffusion_steps "${NUM_DIFFUSION_STEPS}" \
  --batch_size "${DIFFUSION_EVAL_BATCH_SIZE}" \
  --predictor_batch_size "${PREDICTOR_SCORE_BATCH_SIZE}" \
  --max_length "${DIFFUSION_MAX_LENGTH:-256}" \
  --temperature "${DIFFUSION_TEMPERATURE:-1.0}" \
  --bf16 \
  --attn_implementation "${ATTN_IMPLEMENTATION:-sdpa}" \
  --output_dir "${RESULT_ROOT}/diffusion_test_predictor"

echo "P2 test split diffusion evaluation completed under ${RESULT_ROOT}/diffusion_test_predictor"