Tensorflow.js is an open-source library that is being developed by Google for running machine learning models as well as deep learning neural networks in the browser or node environment.
The .logSigmoid() function is used to find the log sigmoid of the stated tensor input and is done element wise.
Syntax:
tf.logSigmoid(x)
Parameters: This function accepts three parameters which are illustrated below:
- x: It is the tensor input, and it can be of type tf.Tensor, or TypedArray, or Array.
Return Value: It returns the tf.Tensor object.
Example 1:
Javascript
// Importing the tensorflow.js library import * as tf from "@tensorflow/tfjs" // Defining tensor input elements const y = tf.tensor1d([1, 15, 38, Math.E]); // Calling logSigmoid() method and // printing output y.logSigmoid().print(); |
Output:
Tensor
[-0.3132617, -3e-7, 0, -0.0639021]
Example 2: In this example, the parameter is passed directly to the logSigmoid function.
Javascript
// Importing the tensorflow.js library import * as tf from "@tensorflow/tfjs" // Defining float values var val = [0.5, 1.5, .66]; // Calling tensor1d method const y = tf.tensor1d(val); // Calling logSigmoid() method var res = tf.logSigmoid(y) // Printing output res.print(); |
Output:
Tensor
[-0.474077, -0.2014133, -0.4166367]
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