Tensorflow.js tf.data.generator() Function
Last Updated :
26 May, 2021
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.generator() function is used to create a dataset using provided JavaScript generator which produces each element.
Syntax:
tf.data.generator(generator)
Parameters:
- generator: It is a JavaScript generator function which returns a JavaScript iterator.
Return value: It returns tf.data.Dataset.
Example 1: This example illustrates how to create a dataset from an iterator factory.
Javascript
import * as tf from "@tensorflow/tfjs"
let geek = tf.data.generator(function () {
let numbers = 4;
let indices = 1;
let outcome;
let repeator = {
next: function () {
if (indices <= numbers) {
outcome =
{
value: indices,
done: false
};
indices++;
return outcome;
}
else {
outcome =
{
value: indices,
done: true
};
return outcome;
}
}
};
return repeator;
});
await geek.forEachAsync(function (geeks) {
console.log(geeks);
});
|
Output:
1
2
3
4
Example 2: This example illustrates how to create a dataset from a generator.
Javascript
import * as tf from "@tensorflow/tfjs"
let geek = tf.data.generator(function* () {
let data = 3;
let a;
for (i = 0; i <= data; ++i) {
a = i;
yield a;
}
});
await geek.forEachAsync(function (geeks) {
console.log(geeks);
});
|
Output:
0
1
2
3
Reference: https://js.tensorflow.org/api/3.6.0/#data.generator
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