Adaptive-Block-Forcing / FlexMDM /scripts /generate_samples_single.sh
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#!/bin/bash
#SBATCH --job-name=generate_samples_single
#SBATCH --account=kempner_albergo_lab
#SBATCH --partition=kempner_requeue
#SBATCH --nodes=1
#SBATCH --gpus-per-node=1
#SBATCH --mem=100GB
#SBATCH --constraint h100
#SBATCH --time=1-00:00:00
#SBATCH --output=slurm_logs/vlmdm/job-%j.out
#SBATCH --mail-type=END,FAIL
#SBATCH --mail-user=brianlee.lck@gmail.com
source /n/netscratch/albergo_lab/Lab/brianlck/interpretable-flow/.venv/bin/activate
export CUDA_LAUNCH_BLOCKING=1
export TORCH_USE_CUDA_DSA=1
export HF_HOME=/n/netscratch/albergo_lab/Everyone/hf_cache
export HF_HUB_ENABLE_HF_TRANSFER=1
# Configuration parameters - modify these as needed
MODEL="flow"
CKPT="/n/netscratch/albergo_lab/Lab/brianlck/interpretable-flow/outputs/2025-07-29/00-17-21/checkpoints/openwebtext/any_order/20250729-001723/last.ckpt"
SAMPLER="tau-leaping"
STEP=1024
TOTAL_SAMPLES=1024
SUBDIR="new_linear"
echo "Running model=$MODEL sampler=$SAMPLER step=$STEP"
# Create output directory
mkdir -p "tmp/owt/${SAMPLER}"
# generate samples
# srun python generate_samples.py \
# --checkpoint_path "${CKPT}" \
# --total_samples "${TOTAL_SAMPLES}" \
# --model_type "${MODEL}" \
# --sampler_type "${SAMPLER}" \
# --step_size "${STEP}" \
# -o "tmp/owt/${SAMPLER}/${SUBDIR}/${MODEL}_generated_samples_${STEP}.json"
# evaluate samples
srun python evaluate_samples.py \
--input-json "tmp/owt/${SAMPLER}/${SUBDIR}/${MODEL}_generated_samples_${STEP}.json" \
--batch-size 32 \
--results-output "/n/netscratch/albergo_lab/Lab/brianlck/interpretable-flow/tmp/owt/${SAMPLER}/${SUBDIR}/${MODEL}_eval_results_${STEP}.json" \
--length-plot-output "/n/netscratch/albergo_lab/Lab/brianlck/interpretable-flow/tmp/owt/${SAMPLER}/${SUBDIR}/${MODEL}_length_plot_${STEP}.png" \
--eval-mode "sentence" \
--perplexity \
--entropy \
--mauve \
--reference-perplexity
echo "Job completed successfully"