TensorFlow.js is an open-source web framework that allows developers to train and deploy machine learning models in the browser. The TensorFlow.js Core API is a low-level API that allows developers to create, manipulate, and optimize numerical computations in JavaScript.
A tensor is a data structure that represents a linear transformation. In simple terms, a tensor is an array of numbers. In TensorFlow.js, a tensor has a shape and a data type. The shape of a tensor is the size and dimensionality of the array, and the data type is the type of data that the tensor contains (e.g. float32
, int32
, string
).
There are a few ways to create tensors in TensorFlow.js. The simplest way is to create a tensor from a JavaScript array using the tf.tensor
function:
const a = tf.tensor([1, 2, 3, 4]);
The tf.tensor
function also allows you to specify the shape and data type of the tensor:
const b = tf.tensor([1, 2, 3, 4], [2, 2], 'int32');
You can also create a tensor from a scalar (a single number):
const c = tf.scalar(5);
Tensors can be manipulated using a variety of functions in the TensorFlow.js API. For example, you can add two tensors using the tf.add
function:
const a = tf.tensor([1, 2, 3, 4]);
const b = tf.tensor([5, 6, 7, 8]);
const c = tf.add(a, b);
You can also perform element-wise operations on tensors. Element-wise operations are operations that are applied to each element in the tensor independently. For example, you can multiply two tensors element-wise using the tf.mul
function:
const a = tf.tensor([1, 2, 3, 4]);
const b = tf.tensor([5, 6, 7, 8]);
const c = tf.mul(a, b);
Tensors can be converted to other data structures using the .toXXX
methods. For example, you can convert a tensor to a JavaScript array using the .toArray
method:
const a = tf.tensor([1, 2, 3, 4]);
const b = a.toArray(); // [1, 2, 3, 4]
You can also convert a tensor to a string using the .toString
method:
const a = tf.tensor([1, 2, 3, 4]);
const b = a.toString(); // "1 2 3 4"
TensorFlow.js provides a variety of optimization functions that can be used to optimize numerical computations. For example, you can use the tf.clipByValue
function to clip tensor values to a specified range:
const a = tf.tensor([-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5]);
const b = tf.clipByValue(a, -2, 2);
You can also use the tf.addN
function to perform element-wise addition on a list of tensors:
const a = tf.tensor([1, 2, 3, 4]);
const b = tf.tensor([5, 6, 7, 8]);
const c = tf.tensor([9, 10, 11, 12]);
const d = tf.addN([a, b, c]);
TensorFlow.js is a powerful tool that allows developers to create, manipulate, and optimize numerical computations in JavaScript. The TensorFlow.js Core API is a low-level API that provides the building blocks for creating, manipulating, and optimizing numerical computations in JavaScript.
If you want to learn more about TensorFlow.js, we recommend checking out the following resources: