0424a080c1
- Updated all WandB project names to use dppo- prefix for organization - Added flexible dev testing script for all environments - Created organized dev_tests directory for test scripts - Fixed MuJoCo compilation issues (added GCC compiler flags) - Documented Python 3.10 compatibility and Furniture-Bench limitation - Validated pre-training for Gym, Robomimic, D3IL environments - Updated experiment tracking with validation results - Enhanced README with troubleshooting and setup instructions
35 lines
989 B
Bash
35 lines
989 B
Bash
#!/bin/bash
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#SBATCH --job-name=dppo_d3il_test
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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_d3il_%j.out
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#SBATCH --error=logs/dppo_d3il_%j.err
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# Load modules and set environment
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module load devel/cuda/12.4
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export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/lib/nvidia
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export CC=gcc
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export CXX=g++
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export WANDB_MODE=online
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export DPPO_WANDB_ENTITY=${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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echo "Testing D3IL avoid_m1 pretrain..."
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echo "Job ID: $SLURM_JOB_ID"
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python script/run.py --config-name=pre_diffusion_mlp \
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--config-dir=cfg/d3il/pretrain/avoid_m1 \
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train.n_epochs=2 \
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train.save_model_freq=1
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echo "D3IL test completed!" |