#!/bin/bash
# Gemma 4 31B data: RULER (re-fetch generator), RULER 6 tasks x 4K/32K/128K with the Gemma tokenizer, MRCR bins, DocVQA link.
set -x
source ~/kvq-env/bin/activate
cd ~/datasets
[ -d ruler/RULER ] || git clone --depth 1 https://github.com/NVIDIA/RULER.git ruler/RULER
(cd ruler/RULER && git log -1 --format="RULER commit %h %cd")
cd ruler/RULER/scripts/data/synthetic/json
[ -f PaulGrahamEssays.json ] || python download_paulgraham_essay.py
[ -f squad.json ] && [ -f hotpotqa.json ] || bash download_qa_dataset.sh
ls -la
cd ~/bench
export KVQ_TOK=~/models/gemma-4-31B-it KVQ_DATA=data_gemma
mkdir -p data_gemma
ln -sf ~/bench/data/docvqa_1000.jsonl data_gemma/docvqa_1000.jsonl
KVQ_RULER_TASKS=niah_single_2,niah_multikey_1,niah_multikey_3,niah_multivalue,vt,qa_2 KVQ_RULER_LENGTHS=4k,32k,128k \
  python prep_data.py --stage ruler --workers 18
python make_6t.py
python mrcr.py prep
echo PREP_GEMMA_DONE