From 7213a8cf48caca5fc7999b6cab20562a324cc51a Mon Sep 17 00:00:00 2001 From: Jiangwei Date: Thu, 11 Mar 2021 11:26:48 +0800 Subject: [PATCH] Update Installation Guide Add installation guide through anaconda --- README.md | 33 +++++++++++++++++++++++++++++++++ 1 file changed, 33 insertions(+) diff --git a/README.md b/README.md index 1bd9f713..c0e738dc 100644 --- a/README.md +++ b/README.md @@ -24,6 +24,39 @@ version supports classification problems only. Let's start by looking at some classic classification problems and see how the framework can automatically find competitive model architectures. +## Installation using Anaconda +In this section, we explain how to install necessary enviroment through Anaconda +1. Install AnaConda, please refer to https://docs.anaconda.com/anaconda/install/ +2. Create new environment with Python3.8 +```console +conda create -n auto_search python=3.8 +``` +3. Activate the new environment +```console +conda activate auto_search +``` +4. Clone the repo +```console +git clone https://github.com/google/model_search.git +cd model_search/ +``` +5. Install Requirements +```console +pip install -r requirements.txt +``` +6. Install Protobuf +```console +conda install -c anaconda protobuf +``` +7. Compile Protobuf +```console +protoc --python_out=./ model_search/proto/phoenix_spec.proto +protoc --python_out=./ model_search/proto/hparam.proto +protoc --python_out=./ model_search/proto/distillation_spec.proto +protoc --python_out=./ model_search/proto/ensembling_spec.proto +protoc --python_out=./ model_search/proto/transfer_learning_spec.proto +``` + ## Getting Started Let us start with the simplest case. You have a csv file where the features are numbers and you would like to run let AutoML find the best model architecture for you.