autogen/website/docs/Installation.md

• Installation
• • Python
  • • Optional Dependencies
    • • Auto Generation
      • Task-oriented AutoML
      • Extra learners/models
      • Notebook
      • Distributed tuning
      • Test and Benchmark
  • .NET

Installation

Python

FLAML requires Python version >= 3.7. It can be installed from pip:

pip install flaml

or conda:

conda install flaml -c conda-forge

Optional Dependencies

Auto Generation

pip install "flaml[autogen]"

Task-oriented AutoML

pip install "flaml[automl]"

Extra learners/models

• openai models

pip install "flaml[openai]"

• catboost

pip install "flaml[catboost]"

• vowpal wabbit

pip install "flaml[vw]"

• time series forecaster: prophet, statsmodels

pip install "flaml[forecast]"

• huggingface transformers

pip install "flaml[hf]"

Notebook

To run the notebook examples,
install flaml with the [notebook] option:

pip install "flaml[notebook]"

Distributed tuning

• ray

pip install "flaml[ray]"

• spark

Spark support is added in v1.1.0

pip install "flaml[spark]>=1.1.0"

For cloud platforms such as Azure Synapse, Spark clusters are provided.
But you may also need to install Spark manually when setting up your own environment.
For latest Ubuntu system, you can install Spark 3.3.0 standalone version with below script.
For more details of installing Spark, please refer to Spark Doc.

sudo apt-get update && sudo apt-get install -y --allow-downgrades --allow-change-held-packages --no-install-recommends \
    ca-certificates-java ca-certificates openjdk-17-jdk-headless \
    && sudo apt-get clean && sudo rm -rf /var/lib/apt/lists/*
wget --progress=dot:giga "https://www.apache.org/dyn/closer.lua/spark/spark-3.3.0/spark-3.3.0-bin-hadoop2.tgz?action=download" \
    -O - | tar -xzC /tmp; archive=$(basename "spark-3.3.0/spark-3.3.0-bin-hadoop2.tgz") \
    bash -c "sudo mv -v /tmp/\${archive/%.tgz/} /spark"
export SPARK_HOME=/spark
export PYTHONPATH=/spark/python/lib/py4j-0.10.9.5-src.zip:/spark/python
export PATH=$PATH:$SPARK_HOME/bin

• nni

pip install "flaml[nni]"

• blendsearch

pip install "flaml[blendsearch]"

• synapse

To install flaml in Azure Synapse and similar cloud platform

pip install flaml[synapse]

Test and Benchmark

• test

pip install flaml[test]

• benchmark

pip install flaml[benchmark]

.NET

FLAML has a .NET implementation in ML.NET, an open-source, cross-platform machine learning framework for .NET.

You can use FLAML in .NET in the following ways:

Low-code

• Model Builder - A Visual Studio extension for training ML models using FLAML. For more information on how to install the, see the install Model Builder guide.
• ML.NET CLI - A dotnet CLI tool for training machine learning models using FLAML on Windows, MacOS, and Linux. For more information on how to install the ML.NET CLI, see the install the ML.NET CLI guide.

Code-first

• Microsoft.ML.AutoML - NuGet package that provides direct access to the FLAML AutoML APIs that power low-code solutions like Model Builder and the ML.NET CLI. For more information on installing NuGet packages, see the install and use a NuGet package in Visual Studio or dotnet CLI guides.

To get started with the ML.NET API and AutoML, see the csharp-notebooks.