| #!/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.}" |
|
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| mkdir -p "${RESULT_ROOT}/refinement" |
|
|
| cd "${GENERANNO_DIR}" |
|
|
| python3 src/tasks/downstream/discrete_diffusion_refine_evaluate.py \ |
| --diffusion_model "${DIFFUSION_MODEL}" \ |
| --base_model_for_code "${GENERANNO_BASE_MODEL}" \ |
| --predictor_model "${PREDICTOR_MODEL}" \ |
| --dataset_dir "${DEEPSTARR_DIR}" \ |
| --output_dir "${RESULT_ROOT}/refinement/paired_refinement_${REFINEMENT_SPLIT:-test}" \ |
| --split "${REFINEMENT_SPLIT:-test}" \ |
| --conditioned \ |
| --target_bucket "${REFINEMENT_TARGET_BUCKET:-high}" \ |
| --mask_ratios ${REFINEMENT_MASK_RATIOS:-0.01 0.03 0.05 0.10 0.20} \ |
| --strategies ${REFINEMENT_STRATEGIES:-random entropy logit_gap} \ |
| --num_sequences "${REFINEMENT_NUM_SEQUENCES:-1024}" \ |
| --num_samples_per_sequence "${REFINEMENT_NUM_SAMPLES:-8}" \ |
| --sequence_length "${SEQUENCE_LENGTH:-246}" \ |
| --num_diffusion_steps "${REFINEMENT_DIFFUSION_STEPS:-32}" \ |
| --batch_size "${REFINEMENT_BATCH_SIZE:-16}" \ |
| --predictor_batch_size "${PREDICTOR_SCORE_BATCH_SIZE:-256}" \ |
| --max_length "${DIFFUSION_MAX_LENGTH:-256}" \ |
| --temperature "${DIFFUSION_TEMPERATURE:-1.0}" \ |
| --bf16 \ |
| --attn_implementation "${ATTN_IMPLEMENTATION:-sdpa}" |
|
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| echo "Paired refinement evaluation completed: ${RESULT_ROOT}/refinement/paired_refinement_${REFINEMENT_SPLIT:-test}" |
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