2.3 KiB
Installation
We recommend using conda to prepare the Python environment. Install conda and create an 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].
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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.