gaojie
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36 lines
905 B
Bash
36 lines
905 B
Bash
#!/bin/bash
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#SBATCH --job-name=lejepa_ou
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#SBATCH --output=logs/ou_%A_%a.out
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#SBATCH --error=logs/ou_%A_%a.err
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#SBATCH --partition=gpuq
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#SBATCH --qos=slow_nice
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#SBATCH --gres=gpu:v100:1
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#SBATCH --cpus-per-task=4
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#SBATCH --mem=32G
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#SBATCH --time=24:00:00
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#SBATCH --array=0-6
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# Each task: prerender eval (skipped if exists) + 200k images for one rho,
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# then train 4 lambdas × 3 seeds × 3 inits = 36 training runs
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RHOS=(0.3 0.5 0.7 0.8 0.9 0.95 0.99)
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RHO_RAW=${RHOS[$SLURM_ARRAY_TASK_ID]}
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RHO=$(printf "%.2f" $RHO_RAW)
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eval "$(conda shell.bash hook)"
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conda activate pytorch
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export MUJOCO_GL=egl
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mkdir -p logs
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echo "Node: $(hostname) | rho=${RHO} | Start: $(date)"
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# Step 1: Prerender (eval + this rho)
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python prerender.py eval
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python prerender.py ou --rho "${RHO}"
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# Step 2: Train
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python run_reacher.py --config configs/reacher.yaml \
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--data_dir "data/reacher/ou/rho=${RHO}"
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echo "Done: $(date)"
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