314a3f3c06
- Complete SLURM test scripts for all environment types - Gym fine-tuning: walker2d, halfcheetah validation tests - Robomimic fine-tuning: lift validation test with scheduler fix - D3IL validation: avoid_m1 pre-training and fine-tuning tests - Updated experiment plan with current validation status - All major environments now have automated testing pipeline
38 lines
1.3 KiB
Bash
38 lines
1.3 KiB
Bash
#!/bin/bash
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#SBATCH --job-name=dppo_lift_ft
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#SBATCH --account=hk-project-p0022232
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#SBATCH --partition=dev_accelerated
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#SBATCH --gres=gpu:1
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#SBATCH --nodes=1
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#SBATCH --ntasks-per-node=1
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#SBATCH --cpus-per-task=8
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#SBATCH --time=00:30:00
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#SBATCH --mem=24G
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#SBATCH --output=logs/dppo_lift_ft_%j.out
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#SBATCH --error=logs/dppo_lift_ft_%j.err
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module load devel/cuda/12.4
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# MuJoCo environment for fine-tuning
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export MUJOCO_PY_MUJOCO_PATH=/home/hk-project-robolear/ys1087/.mujoco/mujoco210
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export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/home/hk-project-robolear/ys1087/.mujoco/mujoco210/bin:/usr/lib/nvidia
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export MUJOCO_GL=egl
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# Environment variables
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export WANDB_MODE=online
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export DPPO_WANDB_ENTITY=${DPPO_WANDB_ENTITY:-"dominik_roth"}
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export DPPO_DATA_DIR=${DPPO_DATA_DIR:-$SLURM_SUBMIT_DIR/data}
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export DPPO_LOG_DIR=${DPPO_LOG_DIR:-$SLURM_SUBMIT_DIR/log}
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cd $SLURM_SUBMIT_DIR
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source .venv/bin/activate
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# Apply HoReKa MuJoCo compilation fix
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echo "Applying HoReKa MuJoCo compilation fix..."
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python -c "exec(open('fix_mujoco_compilation.py').read()); apply_mujoco_fix(); import mujoco_py; print('MuJoCo ready!')"
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echo "Testing robomimic lift fine-tuning..."
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python script/run.py --config-name=ft_ppo_diffusion_mlp \
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--config-dir=cfg/robomimic/finetune/lift \
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train.n_train_itr=50 \
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train.save_model_freq=25 |