Skip to content

Installation#

Installation from PyPI#

To install CARP-S, you can simply use pip:

conda create -n carps python=3.11
conda activate carps
pip install carps

Additionally, you need to install the requirements for the benchmark and optimizer that you want to use. For example, if you want to use the SMAC2.0 optimizer and the BBOB benchmark, you need to install the requirements for both of them via:

pip install carps[smac,bbob]

All possible install options for benchmarks are: 

dummy,bhob,hpob,mfpbench,pymoo,yahpo

All possible install options for optimizers are: 

dummy,dehb,hebo,nevergrad,optuna,skopt,smac,smac14,synetune

Please note that installing all requirements for all benchmarks and optimizers in a single environment will not be possible due to conflicting dependencies.

Installation from Source#

If you want to install from source, you can clone the repository and install CARP-S via:

git clone https://github.com/AutoML/CARP-S.git
cd CARP-S
conda create -n carps python=3.11
conda activate carps

# Install for usage
pip install .

For installing the requirements for the optimizer and benchmark, you can then use the following command: 

pip install ".[smac,bbob]"

If you want to install CARP-S for development, you can use the following command: 

make install-dev

Additional Steps for Benchmarks#

For HPOBench, it is necessary to install the requirements via: 

bash container_recipes/benchmarks/HPOBench/install_HPOBench.sh

For some benchmarks, it is necessary to download data, such as surrogate models, in order to run the benchmark:

  • For HPOB, you can download the surrogate benchmarks with 

    bash container_recipes/benchmarks/HPOB/download_data.sh

  • For MFPBench, you can download the surrogate benchmarks with 

    bash container_recipes/benchmarks/MFPBench/download_data.sh

  • For YAHPO, you can download the required surrogate benchmarks and meta-data with 

    bash container_recipes/benchmarks/YAHPO/prepare_yahpo.sh