#!/bin/sh
#PJM -L rscgrp=b-batch
#PJM -L gpu=4
#PJM -L elapse=24:00:00
#PJM -N baseline_ccfm
#PJM -j
#PJM -o logs/baseline_ccfm_%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/ori_scDFM_env/bin/activate

cd /home/hp250092/ku50001222/qian/aivc/lfj/transfer/code/ori_scDFM

export PYTHONPATH=./
export PYTORCH_CUDA_ALLOC_CONF=max_split_size_mb:256

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 "Run:       baseline_ccfm_aligned (topk=15, no negative edge)"
echo "=========================================="

accelerate launch --num_processes=4 src/script/run.py \
    --batch_size=48 \
    --model_type=origin \
    --lr=5e-5 \
    --steps=200000 \
    --data_name=norman \
    --d_model=128 \
    --eta_min=1e-6 \
    --fusion_method=differential_perceiver \
    --infer_top_gene=1000 \
    --n_top_genes=5000 \
    --perturbation_function=crisper \
    --noise_type=Gaussian \
    --mode=predict_y \
    --gamma=0.5 \
    --split_method=additive \
    --use_mmd_loss \
    --fold=1 \
    --print_every=10000 \
    --topk=15 \
    --result_path=./result/baseline_ccfm_aligned

echo "=========================================="
echo "Finished:  $(date)"
echo "=========================================="