Introduction: Tensorflow.js is an open-source library that is developed by Google for running machine learning models as well as deep learning neural networks in the browser or node environment.
The .ready() function is used to return a promise which determines at what time the recently picked backend or else the topmost priority one has been initialized. Moreover, we need to await this promise if we are utilizing a backend that possesses asynchronous initialization.
Syntax:
tf.ready()
Parameters: This method does not hold any parameter.
Return Value: It returns promise of void.
Example 1:
Javascript
// Importing the tensorflow.js library import * as tf from "@tensorflow/tfjs"Â Â // Calling setBackend() method tf.setBackend('wasm'); Â Â // Calling ready() method and // Printing output await tf.ready().then(() => { Â Â console.log(tf.backend().blockSize) }); |
Output:
48
Example 2:
Javascript
// Importing the tensorflow.js library import * as tf from "@tensorflow/tfjs"Â Â // Calling setBackend() method tf.setBackend('webgl'); Â Â // Calling ready() method and // Printing output await tf.ready().then(() => { Â Â console.log(JSON.stringify(tf.getBackend())) }); |
Output:
"webgl"
Reference: https://js.tensorflow.org/api/latest/#ready
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