From f66668d4160cb14a7d76cade8593d6290318218e Mon Sep 17 00:00:00 2001 From: Dan Crescimanno Date: Wed, 18 May 2022 22:37:40 -0700 Subject: [PATCH] updated readme --- README.md | 48 +++++++++++++++++++++++++++++------------------- 1 file changed, 29 insertions(+), 19 deletions(-) diff --git a/README.md b/README.md index 3af37d66..d755753a 100644 --- a/README.md +++ b/README.md @@ -21,34 +21,33 @@ Documentation site: [www.scikitjs.org](https://www.scikitjs.org) For use with modern bundlers in a frontend application, simply ```bash +npm i @tensorflow/tfjs npm i scikitjs ``` -Usage is similar to other js libraries. +We depend on the tensorflow library in order to make our calculations fast, but we don't ship it in our bundle. +We use it as a peer dependency. General usage is as follows. ```js -import { LinearRegression } from 'scikitjs' +import * as tf from '@tensorflow/tfjs' +import * as sk from 'scikitjs' +sk.setBackend(tf) ``` +This allows us to build a library that can be used in Deno, Node, and the browser with the same configuration. ### Backend Users -For Node.js users who wish to bind to the Tensorflow C++ library, simply +For Node.js users who wish to bind to the Tensorflow C++ library, simply import the tensorflow C++ version, and use that as the tf library ```bash +npm i @tensorflow/tfjs-node npm i scikitjs ``` -But then import the node bindings - -```js -import { LinearRegression } from 'scikitjs/node' -``` - -The `scikitjs/node` path uses the new "exports" feature of node (which is available in node v13.3+). -If you are using an older version of node, simply pass in the path to the cjs build - ```js -import { LinearRegression } from 'scikitjs/dist/cjs/index.js' +import * as tf from '@tensorflow/tfjs-node' +import * as sk from 'scikitjs' +sk.setBackend(tf) ``` ### Script src @@ -57,16 +56,21 @@ For those that wish to use script src tags, simply ```html ``` ## Simple Example ```js -import { LinearRegression } from 'scikitjs' +import * as tf from '@tensorflow/tfjs-node' +import { setBackend, LinearRegression } from 'scikitjs' +setBackend(tf) const lr = new LinearRegression({ fitIntercept: false }) const X = [[1], [2]] // 2D Matrix with a single column vector @@ -124,7 +128,9 @@ Turns into #### JavaScript ```js -import { LinearRegression } from 'scikitjs' +import * as tf from '@tensorflow/tfjs-node' +import { setBackend, LinearRegression } from 'scikitjs' +setBackend(tf) let X = [[1], [2]] let y = [10, 20] @@ -154,7 +160,9 @@ Turns into #### JavaScript ```js -import { LinearRegression } from 'scikitjs' +import * as tf from '@tensorflow/tfjs-node' +import { setBackend, LinearRegression } from 'scikitjs' +setBackend(tf) let X = [[1], [2]] let y = [10, 20] @@ -189,7 +197,9 @@ Turns into #### JavaScript ```js -import { LogisticRegression } from 'scikitjs' +import * as tf from '@tensorflow/tfjs-node' +import { setBackend, LogisticRegression } from 'scikitjs' +setBackend(tf) let X = [[1], [-1]] let y = [1, 0] pFad - Phonifier reborn

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