Local
Contents
Local#
DeepHyper installation requires Python>=3.7
. By default, only hyperparameter search features will be installed.
Conda environment#
This installation procedure shows you how to create your own Conda virtual environment and install DeepHyper in it.
Linux#
Install Miniconda, and create the dh
environment:
$ conda create -n dh python=3.8 -y
$ conda activate dh
$ conda install gxx_linux-64 gcc_linux-64
Finally install DeepHyper in the previously created dh
environment:
$ pip install pip --upgrade
$ pip install deephyper["analytics"]
MacOS#
Install Xcode command line tools:
xcode-select --install
Check you current platform:
python3 -c "import platform; print(platform.platform());"
x86_64#
If your architecture is x86_64
install Miniconda, and create the dh
environment:
$ conda create -n dh python=3.8 -y
$ conda activate dh
Then install DeepHyper in the previously created dh
environment:
$ pip install pip --upgrade
$ pip install deephyper["analytics"]
arm64#
If your architecture is arm64
download MiniForge then install it:
chmod +x ~/Downloads/Miniforge3-MacOSX-arm64.sh
sh ~/Downloads/Miniforge3-MacOSX-arm64.sh
After installing MiniForge clone the DeepHyper repo and install the package:
git clone https://github.com/deephyper/deephyper.git
cd deephyper/
conda env create -f install/environment.macOS.arm64.yml
Jupyter Notebooks#
To create a custom Jupyter kernel run the following from your activated Conda environment:
$ python -m ipykernel install --user --name deephyper --display-name "Python (deephyper)"
Now when you open a Jupyter notebook the Python (deephyper)
kernel will be available.
Docker Image (CPU)#
A Docker image with DeepHyper is provided. Assuming Docker is installed on the system you are using you can access the image with the following commands:
$ docker pull ghcr.io/deephyper/deephyper:0.3.3
$ docker run -i -t ghcr.io/deephyper/deephyper:0.3.3 /bin/bash
Developer Installation#
Follow the Conda environment installation and replace pip install deephyper[analytics]
by:
$ git clone https://github.com/deephyper/deephyper.git
$ cd deephyper/ && git checkout develop
$ pip install -e ".[dev,analytics]"