#!/bin/bash
#SBATCH --job-name=dppo_install
#SBATCH --account=hk-project-p0022232
#SBATCH --partition=dev_accelerated
#SBATCH --gres=gpu:1
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=1
#SBATCH --cpus-per-task=4
#SBATCH --time=00:30:00
#SBATCH --mem=16G
#SBATCH --output=logs/dppo_install_%j.out
#SBATCH --error=logs/dppo_install_%j.err

# Load CUDA module (required for PyTorch)
module load devel/cuda/12.4

# Print job info
echo "Starting DPPO installation..."
echo "Job ID: $SLURM_JOB_ID"
echo "Node: $SLURM_NODELIST"
echo "GPU: $CUDA_VISIBLE_DEVICES"

# Navigate to dppo directory (uses current directory)
cd $SLURM_SUBMIT_DIR

# Create and activate virtual environment with Python 3.10
python3.10 -m venv .venv
source .venv/bin/activate

# Upgrade pip
pip install --upgrade pip

# Install base package
pip install -e .

# Install ALL optional dependencies (except Kitchen which has conflicts)
pip install -e .[all]

echo "Installation completed!"
echo "Python version: $(python --version)"
echo "Pip version: $(pip --version)"

echo ""
echo "=== IMPORTANT: MuJoCo Setup for Fine-tuning ==="
echo "1. Install MuJoCo 2.1.0: https://github.com/openai/mujoco-py#install-mujoco"
echo "2. Add these environment variables to your SLURM scripts:"
echo "export MUJOCO_PY_MUJOCO_PATH=\$HOME/.mujoco/mujoco210"
echo "export LD_LIBRARY_PATH=\$LD_LIBRARY_PATH:\$HOME/.mujoco/mujoco210/bin:/usr/lib/nvidia"
echo "export MUJOCO_GL=egl"
echo ""
echo "Pre-training works without MuJoCo setup."
echo ""

echo "Installed packages:"
pip list