# Create a virtual environment (optional but recommended)
python3 -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# Install dependencies
pip install -r requirements.txt# Create conda environment
conda create -n ou-pm python=3.10
conda activate ou-pm
# Install dependencies
pip install -r requirements.txtIf you have a CUDA-capable GPU, replace the JAX installation:
# For CUDA 11.x
pip uninstall jax jaxlib
pip install jax[cuda11_pip] -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html
# For CUDA 12.x
pip uninstall jax jaxlib
pip install jax[cuda12_pip] -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.htmlSimply run:
python3 main.pyExpected output:
- Console output showing training progress
- Results saved to
results/directory
Edit config.py to change:
# True parameters
TRUE_LAMBDA = 10.0
TRUE_A = 2.0
TRUE_B = 1.0
TRUE_SIGMA = 0.5
# Training settings
N_EPOCHS = 1000
BATCH_SIZE = 64
LEARNING_RATE = 0.01