Add HoReKa cluster documentation to README

- Document installation process using Python 3.10 venv
- Add usage examples for SLURM job submission
- Document available environments and resource allocations
- Add WandB configuration instructions
- List all repository changes made for HoReKa compatibility

README.md

@@ -44,6 +44,104 @@ pip install -e .[all] # except for Kitchen
 source script/set_path.sh
 ```
 
+## HoReKa Cluster Setup
+
+### Installation on HoReKa
+
+The DPPO repository has been adapted to run on the HoReKa cluster. The original repository recommends conda, but we use vanilla Python with venv for consistency with cluster policies.
+
+1. **Clone the repository and navigate to it:**
+   ```bash
+   git clone git@dominik-roth.eu:dodox/dppo.git
+   cd dppo
+   ```
+
+2. **Create virtual environment with Python 3.10:**
+   ```bash
+   python3.10 -m venv .venv
+   source .venv/bin/activate
+   ```
+
+3. **Install the package and dependencies:**
+   ```bash
+   # Use the provided installation script
+   sbatch install_dppo.sh
+   
+   # Or install manually:
+   pip install --upgrade pip
+   pip install -e .
+   pip install -e .[gym]  # For Gym environments
+   ```
+
+### Running on HoReKa
+
+The repository includes pre-configured SLURM scripts for job submission:
+
+#### Quick Start
+```bash
+# Run a development test (30 minutes, 24GB RAM)
+./submit_job.sh dev
+
+# Run Gym pre-training
+./submit_job.sh gym hopper pretrain
+
+# Run Gym fine-tuning
+./submit_job.sh gym walker2d finetune
+```
+
+#### Manual Job Submission
+```bash
+# Submit development test
+sbatch slurm/run_dppo_dev.sh
+
+# Submit Gym experiments with parameters
+TASK=hopper MODE=pretrain sbatch slurm/run_dppo_gym.sh
+```
+
+#### Supported Tasks
+
+**Gym environments:**
+- `hopper`, `walker2d`, `halfcheetah`
+
+**Modes:**
+- `pretrain` - Pre-train diffusion policy
+- `finetune` - Fine-tune with PPO
+
+#### Resource Allocations
+- **Development**: 30 minutes, 24GB RAM, 8 CPUs, dev_accelerated partition
+- **Production**: 8 hours, 32GB RAM, 40 CPUs, accelerated partition
+
+#### Monitoring Jobs
+```bash
+# Check job status
+squeue -u $USER
+
+# View logs
+tail -f logs/dppo_<job_id>.out
+```
+
+### Configuration
+
+Before running experiments, set your WandB credentials:
+
+```bash
+export WANDB_API_KEY=<your_api_key>
+export WANDB_ENTITY=<your_username_or_team>
+```
+
+Or disable WandB by adding `wandb=null` to your python command.
+
+### Repository Changes
+
+This fork includes the following additions for HoReKa compatibility:
+- `install_dppo.sh` - Automated installation script for SLURM
+- `submit_job.sh` - Convenient job submission wrapper
+- `slurm/` directory with job scripts for different experiment types
+- Updated `.gitignore` to allow shell scripts (removed `*.sh` exclusion)
+- Git remotes configured: `upstream` (original repository) and `origin` (this fork)
+
+Note: The installation was successful without any code modifications. All dependencies installed correctly with Python 3.10.
+
 ## Usage - Pre-training
 
 **Note**: You may skip pre-training if you would like to use the default checkpoint (available for download) for fine-tuning.