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# Tensorflow.js tf.metrics.meanAbsolutePercentageError() Function

Tensorflow.js is an open-source library developed by Google for running machine learning models as well as deep learning neural networks in the browser or node environment.

The .metrics.meanAbsolutePercentageError() function is a loss or else a metric function i.e. mean absolute percentage error which uses truth and prediction tensor inputs in order to return tf.Tensor object.

Syntax:

`tf.metrics.meanAbsolutePercentageError(yTrue, yPred)`

Parameters:

• yTrue: It is the stated truth tensor and it can be of type tf.Tensor.
• yPred: It is the stated prediction tensor and it can be of type tf.Tensor.

Return Value: It returns the tf.Tensor object.

Example 1:

## Javascript

 `// Importing the tensorflow.js library``import * as tf from ``"@tensorflow/tfjs"`` ` `// Defining truth and prediction tensors``const y = tf.tensor2d([[0, 2], [20, 30]]);``const z = tf.tensor2d([[0, 2], [21, 34]]);`` ` `// Calling metrics.meanAbsolutePercentageError() ``// method``const mape = tf.metrics.meanAbsolutePercentageError(y, z);`` ` `// Printing output``mape.print();`

Output:

```Tensor
[0, 9.166666]```

Example 2:

## Javascript

 `// Importing the tensorflow.js library``import * as tf from ``"@tensorflow/tfjs"`` ` `// Calling metrics.meanAbsolutePercentageError() ``// method with its parameter directly and then``// Printing output``const output = tf.metrics.meanAbsolutePercentageError(tf.tensor(``    ``[``      ``[0, 1, 0, 0],``      ``[0, 1, 1, 0],``      ``[0, 0, 0, 1],``      ``[1, 1, 0, 0],``      ``[0, 0, 1, 0]``    ``]``), tf.tensor(``    ``[``      ``[0, 0, 1, 1],``      ``[0, 1, 1, 0],``      ``[0, 0, 0, 1],``      ``[0, 1, 0, 1],``      ``[1, 1, 0, 0]``    ``]``)).print();`

Output:

```Tensor
[500025, 0, 0, 250025, 500025]```

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