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 .addLoss() function is used to attach losses to the stated layer. Moreover, the loss might be probably conditional on a few input tensors, for example operation losses are dependent on the inputs of the stated layers.
Syntax:
addLoss(losses)
Parameters:
- losses: It is the stated losses. It can be of type RegularizerFn or RegularizerFn[].
Return Value: It returns void.
Example 1:
Javascript
// Importing the tensorflow.js library import * as tf from "@tensorflow/tfjs" // Creating a model const model = tf.sequential(); // Adding a layer model.add(tf.layers.dense({units: 1, inputShape: [3]})); // Defining input const input = tf.tensor1d([1, 2, 3, 4]); // Calling addLoss() method with its // parameter const res = model.layers[0].addLoss([tf.abs(input)]); // Printing output console.log(JSON.stringify(input)); model.layers[0].getWeights()[0].print(); |
Output:
{"kept":false,"isDisposedInternal":false,"shape":[4],"dtype":"float32",
"size":4,"strides":[],"dataId":{"id":82},"id":124,"rankType":"1","scopeId":61}
Tensor
[[0.143441 ],
[-0.58002 ],
[-0.5836995]]
Example 2:
Javascript
// Importing the tensorflow.js library import * as tf from "@tensorflow/tfjs" // Creating a model const model = tf.sequential(); // Adding layers model.add(tf.layers.dense({units: 1, inputShape: [3]})); model.add(tf.layers.dense({units: 4})); model.add(tf.layers.dense({units: 9, inputShape: [11]})); // Defining inputs const input1 = tf.tensor1d([0.5, 0.2, -33, null]); const input2 = tf.tensor1d([0.33, 0.5, -1]); const input3 = tf.tensor1d([1, 0.44]); // Calling addLoss() method with its // parameter const res1 = model.layers[0].addLoss([tf.cos(input1)]); const res2 = model.layers[0].addLoss([tf.sin(input2)]); const res3 = model.layers[0].addLoss([tf.tan(input3)]); // Printing outputs console.log(JSON.stringify(input1)); console.log(JSON.stringify(input2)); console.log(JSON.stringify(input3)); model.layers[0].getWeights()[0].print(); |
Output:
{"kept":false,"isDisposedInternal":false,"shape":[4],"dtype":"float32",
"size":4,"strides":[],"dataId":{"id":169},"id":261,"rankType":"1","scopeId":112}
{"kept":false,"isDisposedInternal":false,"shape":[3],"dtype":"float32",
"size":3,"strides":[],"dataId":{"id":170},"id":262,"rankType":"1","scopeId":112}
{"kept":false,"isDisposedInternal":false,"shape":[2],"dtype":"float32",
"size":2,"strides":[],"dataId":{"id":171},"id":263,"rankType":"1","scopeId":112}
Tensor
[[-0.0062826],
[0.0883235 ],
[-1.0633234]]
Reference: https://js.tensorflow.org/api/latest/#tf.layers.Layer.addLoss
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