Installation

The Deep LVPM toolbox is distributed as a Python package that depends on Keras and TensorFlow. The most recent release has been tested with TensorFlow 2.16.2 and Python 3.11 (recommended for best stability).

We recommend creating a fresh virtual environment using either conda or Python’s built-in venv module before installing the package. Deep LVPM now supports installation extras so you can choose the appropriate TensorFlow build for your hardware.

Note

Intel-based Macs should use the [cpu] extra. The [gpu] extra is only useful if you have an NVIDIA GPU with supported CUDA drivers. The [apple] extra is only for Apple Silicon M-series chips.

Conda environment

To create a conda environment and install the package from GitHub:

# create a new conda environment with Python 3.11
conda create -n myenv python=3.11
conda activate myenv

# CPU-only install (Linux/Windows/Intel Mac)
pip install "git+https://github.com/alexjamesing/Deep_LVPM.git#egg=deep-lvpm[cpu]"

# GPU install (Linux/Windows with NVIDIA GPU)
pip install "git+https://github.com/alexjamesing/Deep_LVPM.git#egg=deep-lvpm[gpu]"

# Apple Silicon install (M-series only)
pip install "git+https://github.com/alexjamesing/Deep_LVPM.git#egg=deep-lvpm[apple]"

Virtualenv

To use Python’s venv module instead of conda:

# create a new virtual environment (use Python 3.11 for best stability)
python3 -m venv myenv

# activate the environment on macOS/Linux
source myenv/bin/activate

# activate the environment on Windows
# myenv\Scripts\activate

# CPU-only install (Linux/Windows/Intel Mac)
pip install "git+https://github.com/alexjamesing/Deep_LVPM.git#egg=deep-lvpm[cpu]"

# GPU install (Linux/Windows with NVIDIA GPU)
pip install "git+https://github.com/alexjamesing/Deep_LVPM.git#egg=deep-lvpm[gpu]"

# Apple Silicon install (M-series only)
pip install "git+https://github.com/alexjamesing/Deep_LVPM.git#egg=deep-lvpm[apple]"

Warning

The [gpu] extra installs tensorflow[and-cuda]==2.16.2 which includes the full CUDA and cuDNN runtime. This is a large download and will fall back to CPU if no GPU is detected. The [apple] extra installs tensorflow-macos and tensorflow-metal for GPU acceleration on Apple Silicon.

The current version of DLVPM is built on Keras 2 (with a TensorFlow backend). We are actively updating the package to Keras 3, which will enable compatibility with multiple backends (TensorFlow, PyTorch and JAX). Users should ensure that they install the correct version of TensorFlow as specified above to avoid compatibility issues.