ipex-llm/docs/readthedocs/source/doc/Orca/Overview/install.md

Installation

Install Java

You need to download and install JDK in the environment, and properly set the environment variable JAVA_HOME. JDK8 is highly recommended.

# For Ubuntu
sudo apt-get install openjdk-8-jre
export JAVA_HOME=/usr/lib/jvm/java-8-openjdk-amd64/

# For CentOS
su -c "yum install java-1.8.0-openjdk"
export JAVA_HOME=/usr/lib/jvm/java-1.8.0-openjdk-1.8.0.282.b08-1.el7_9.x86_64/jre

export PATH=$PATH:$JAVA_HOME/bin
java -version  # Verify the version of JDK.

Install Anaconda

We recommend using conda to prepare the Python environment.

You can follow the steps below to install conda:

# Download Anaconda installation script 
wget -P /tmp https://repo.anaconda.com/archive/Anaconda3-2020.02-Linux-x86_64.sh

# Execute the script to install conda
bash /tmp/Anaconda3-2020.02-Linux-x86_64.sh

# Run this command in your terminal to activate conda
source ~/.bashrc

Then create a Python environment for BigDL Orca:

conda create -n py37 python=3.7  # "py37" is conda environment name, you can use any name you like.
conda activate py37

To use basic Orca features

You can install Orca in your created conda environment for distributed data processing, training and inference with the following command:

pip install bigdl-orca  # For the official release version

or for the nightly build version, use:

pip install --pre --upgrade bigdl-orca  # For the latest nightly build version

To additionally use RayOnSpark

If you wish to run RayOnSpark or sklearn-style Estimator APIs in Orca with "ray" backend, use the extra key [ray] during the installation above:

pip install bigdl-orca[ray]  # For the official release version

or for the nightly build version, use:

pip install --pre --upgrade bigdl-orca[ray]  # For the latest nightly build version

Note that with the extra key of [ray], pip will automatically install the additional dependencies for RayOnSpark, including ray[default]==1.9.2, aiohttp==3.8.1, async-timeout==4.0.1, aioredis==1.3.1, hiredis==2.0.0, prometheus-client==0.11.0, psutil, setproctitle.

To additionally use AutoML

If you wish to run AutoML, use the extra key [automl] during the installation above:

pip install bigdl-orca[automl]  # For the official release version

or for the nightly build version, use:

pip install --pre --upgrade bigdl-orca[automl]  # For the latest nightly build version

Note that with the extra key of [automl], pip will automatically install the additional dependencies for distributed hyper-parameter tuning, including ray[tune]==1.9.2, scikit-learn, tensorboard, xgboost together with the dependencies given by the extra key [ray].

• To use Pytorch AutoEstimator, you need to install Pytorch with pip install torch==1.8.1.

• To use TensorFlow/Keras AutoEstimator, you need to install TensorFlow with pip install tensorflow==1.15.0.