.. raw:: html Installation Guide ================== Quick Start ----------- Create conda environment (recommended): .. code-block:: bash conda create --name vbi python=3.10 conda activate vbi Install VBI: .. code-block:: bash pip install vbi # Light version (CPU only) pip install vbi[light-gpu] # Light + Cupy pip install vbi[inference] # With (sbi, PyTorch) pip install vbi[all] # Full (sbi, PyTorch, Cupy) Installation Options -------------------- .. list-table:: VBI Installation Variants :header-rows: 1 :class: color-caption * - **Command** - **Includes** - **Best For** * - ``pip install vbi`` - CPU simulation, feature extraction, CDE-based inference - Avoiding heavy dependencies * - ``pip install vbi[light-gpu]`` - Everything + Cupy - GPU simulation * - ``pip install vbi[inference]`` - Everything + PyTorch, SBI - Parameter inference (CPU) * - ``pip install vbi[inference-gpu]`` - Everything + GPU acceleration - Full functionality with GPU Docker Usage ------------ .. code-block:: bash # Quick start with pre-built image docker run --rm -it -p 8888:8888 ghcr.io/ins-amu/vbi:main # With GPU support docker run --gpus all --rm -it -p 8888:8888 ghcr.io/ins-amu/vbi:main For Docker building and advanced usage, see :doc:`docker_build` and :doc:`docker_quickstart`. Installation From Source ------------------------- .. code-block:: bash git clone https://github.com/ins-amu/vbi.git cd vbi pip install . For development: .. code-block:: bash pip install -e .[all] Platform-Specific Instructions ------------------------------- **Google Colab** Google Colab doesn't have VBI or SBI pre-installed, and **Docker is not supported** in Colab due to security restrictions. For optimal C++ module compilation, install from source: .. code-block:: bash # In a Colab cell, run: !mkdir -p src && cd src !git clone --depth 1 https://github.com/ins-amu/vbi.git %cd src/vbi !pip install -e . **Alternative: Use Colab Pro+ with Custom Runtimes** If you have Colab Pro+ and need a containerized environment, consider: - Using **Kaggle Notebooks** (supports Docker-based custom environments) - Using **Binder** with our repository (though with limited resources) - Setting up a **local Jupyter server** with our Docker image and connecting via ngrok **Note:** The environment will be reset when the Colab runtime shuts down. You'll need to reinstall for each new session. **EBRAINS Collab** EBRAINS has dependency management restrictions. Here's a script to create a dedicated VBI environment: .. code-block:: bash #!/bin/bash # Save this as setup_vbi_ebrains.sh set -eux # Create fresh environment rm -rf /tmp/vbi python3 -m venv /tmp/vbi unset PYTHONPATH source /tmp/vbi/bin/activate # Install core dependencies pip install ipykernel scikit_learn matplotlib # Install PyTorch (CPU version to save space) pip install torch --index-url https://download.pytorch.org/whl/cpu # Install SBI without dependencies to avoid reinstalling large packages pip install sbi --no-deps # Install SBI dependencies manually pip install pyro-ppl tensorboard nflows pyknos zuko arviz pymc # Install VBI from source mkdir -p /tmp/src && pushd /tmp/src git clone --depth 1 https://github.com/ins-amu/vbi.git cd vbi pip install -e . popd # Create Jupyter kernel python -m ipykernel install --user --name VBI echo "VBI environment created! Please reload your browser and select the 'VBI' kernel." echo "Note: This environment will be lost when the lab server shuts down." Make the script executable and run it: .. code-block:: bash chmod +x setup_vbi_ebrains.sh ./setup_vbi_ebrains.sh **Important Notes:** - Both environments are temporary and will be reset when the respective platforms shut down - For EBRAINS, you'll need to rerun the setup script for each new session - For Colab, you'll need to reinstall VBI in each new runtime **Windows** Windows installation is automatic - C++ compilation is automatically skipped: .. code-block:: bash pip install vbi Verification ------------ .. code-block:: python import vbi vbi.tests() vbi.test_imports() Troubleshooting --------------- **C++ Compilation Issues** Note: the package is configured with SKIP_CPP=0 by default (C++ extensions are enabled). If you want to skip compilation of C++ components, set SKIP_CPP=1 when installing from source or via pip, for example: .. code-block:: bash export SKIP_CPP=1 pip install vbi **Common Issues** - **ImportError**: Check Python version (3.10+ recommended) - **CUDA issues**: Verify GPU drivers and CUDA compatibility - **Memory errors**: Try lighter installation variants For detailed troubleshooting, platform guides, and advanced scenarios, see the complete `Installation Guide `_.