#!/bin/bash #PJM -L rscgrp=b-batch #PJM -L gpu=1 #PJM -L elapse=04:00:00 #PJM -N eval_scalar_15k #PJM -j #PJM -o /home/hp250092/ku50001222/qian/aivc/lfj/GRN/result/evl/eval_scalar_15k_%j.out module load cuda/12.2.2 module load cudnn/8.9.7 module load gcc-toolset/12 source /home/hp250092/ku50001222/qian/aivc/lfj/stack_env/bin/activate cd /home/hp250092/ku50001222/qian/aivc/lfj/GRN/grn_scalar export PYTORCH_CUDA_ALLOC_CONF=max_split_size_mb:256 CKPT=/home/hp250092/ku50001222/qian/aivc/lfj/GRN/result/scalar/scalar-norman-f1-topk30-negTrue-d128-ld1-lr5e-05-lw1.0-lp0.4-agg_signed_l2-dtk100-ema0.9999-ln-wu2000-rk4/iteration_15000/checkpoint.pt OUT_DIR=/home/hp250092/ku50001222/qian/aivc/lfj/GRN/result/evl/scalar_15k echo "==========================================" echo "Job ID: $PJM_JOBID" echo "Job Name: $PJM_JOBNAME" echo "Start: $(date)" echo "Node: $(hostname)" echo "GPU: $(nvidia-smi --query-gpu=name,memory.total --format=csv,noheader 2>/dev/null || echo 'N/A')" echo "Checkpoint: $CKPT" echo "Output: $OUT_DIR" echo "==========================================" accelerate launch --num_processes=1 scripts/run_cascaded.py \ --data-name norman \ --d-model 128 \ --d-hid 512 \ --nhead 8 \ --nlayers 4 \ --batch-size 96 \ --lr 5e-5 \ --steps 200000 \ --fusion-method differential_perceiver \ --perturbation-function crisper \ --noise-type Gaussian \ --infer-top-gene 1000 \ --n-top-genes 5000 \ --use-mmd-loss \ --gamma 0.5 \ --split-method additive \ --fold 1 \ --latent-dim 1 \ --agg-mode signed_l2 \ --latent-weight 1.0 \ --choose-latent-p 0.4 \ --delta-topk 100 \ --warmup-batches 200 \ --print-every 5000 \ --topk 30 \ --use-negative-edge \ --ema-decay 0.9999 \ --t-sample-mode logit_normal \ --warmup-steps 2000 \ --ode-method rk4 \ --eval-batch-size 8 \ --sparse-cache-path /home/hp250092/ku50001222/qian/aivc/lfj/GRN/grn_ccfm/cache/norman_attn_L11_sparse.h5 \ --checkpoint-path "$CKPT" \ --test-only # Copy results to evl directory EVAL_DIR=/home/hp250092/ku50001222/qian/aivc/lfj/GRN/result/scalar/scalar-norman-f1-topk30-negTrue-d128-ld1-lr5e-05-lw1.0-lp0.4-agg_signed_l2-dtk100-ema0.9999-ln-wu2000-rk4/eval_only mkdir -p "$OUT_DIR" if [ -f "${EVAL_DIR}/agg_results.csv" ]; then cp "${EVAL_DIR}/agg_results.csv" "$OUT_DIR/" cp "${EVAL_DIR}/results.csv" "$OUT_DIR/" 2>/dev/null cp "${EVAL_DIR}/pred.h5ad" "$OUT_DIR/" 2>/dev/null cp "${EVAL_DIR}/real.h5ad" "$OUT_DIR/" 2>/dev/null echo "[DONE] Results copied to $OUT_DIR" ls -lh "$OUT_DIR" else echo "[WARN] No agg_results.csv produced in $EVAL_DIR" fi echo "==========================================" echo "Finished: $(date)" echo "=========================================="