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Tensorflow.js tf.Tensor class .buffer() Method

  • Last Updated : 26 May, 2021

Tensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. It also helps the developers to develop ML models in JavaScript language and can use ML directly in the browser or in Node.js.

The tf.Tensor class.buffer() method is used to return a promise of tf.TensorBuffer that holds the underlying data.

Syntax:

buffer()

Parameters: It does not accept any parameters.

Return Value: It returns Promise <tf.TensorBuffer>.



Example 1: Creating a 2d tensor.

Javascript




const a= tf.tensor2d([[0, 1], [2, 3]])
  
console.log(a.buffer())

Output:

Example 2:

Javascript




const a= tf.tensor([1, 3, 5, 4, 2])
  
console.log(a.buffer())

Output:

Reference: https://js.tensorflow.org/api/latest/#tf.Tensor.buffer

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