Tensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. It also helps the developers to develop ML models in JavaScript language and can use ML directly in the browser or in Node.js.
The tf.data.zip() function is used for creating a dataset by zipping together a dict, array, or nested structure of Dataset.
Syntax:
tf.data.zip(datasets)
Parameters:
- dataset: It is the set of data.
Return Value: It returns the tf.data.Dataset.
Example 1:
Javascript
import * as tf from "@tensorflow/tfjs"
let geek1 = tf.data.array([1, 2, 3, 4]);
let geek2 = tf.data.array([5, 6, 7, 8]);
let geek3 = tf.data.zip([geek1, geek2]);
await geek3.forEachAsync( function (geek){
console.log(JSON.stringify(geek))
});
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Output:
[1,5]
[2,6]
[3,7]
[4,8]
Example 2:
Javascript
import * as tf from "@tensorflow/tfjs"
let geek = tf.data.zip({
geek1: tf.data.array([1, 2, 3, 4]),
geek2: tf.data.array([5, 6, 7, 8])
});
await geek.forEachAsync( function (e){
console.log(JSON.stringify(e))
});
|
Output:
{"geek1":1,"geek2":5}
{"geek1":2,"geek2":6}
{"geek1":3,"geek2":7}
{"geek1":4,"geek2":8}
Reference: https://js.tensorflow.org/api/3.6.0/#tf.data.zip