Tensorflow.js tf.softplus() Function
Last Updated :
18 May, 2021
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 .softplus() function is used to find softplus of the stated input tensor i.e. log(exp(x) + 1) and is done element wise.
Syntax :
tf.softplus(x)
Parameters:
- x: It is the stated tensor input, and it can be of type tf.Tensor, TypedArray, or Array.
Return Value: It returns the tf.Tensor object.
Example 1:
Javascript
import * as tf from "@tensorflow/tfjs"
const y = tf.tensor1d([11, 17, 0, NaN, -41]);
y.softplus().print();
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Output:
Tensor
[11.0000162, 17, 0.6931472, NaN, 0]
Example 2:
Javascript
import * as tf from "@tensorflow/tfjs"
var val = [1.5, .4, .23, null, 'a'];
const y = tf.tensor1d(val);
var res = tf.softplus(y)
res.print();
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Output:
Tensor
[1.7014132, 0.9130152, 0.8147451, 0.6931472, NaN]
Reference: https://js.tensorflow.org/api/latest/#softplus
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