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📜  Tensorflow.js tf.data.Dataset 类 .prefetch() 方法

📅  最后修改于: 2022-05-13 01:56:23.837000             🧑  作者: Mango

Tensorflow.js tf.data.Dataset 类 .prefetch() 方法

Tensorflow.js是谷歌开发的一个开源库,用于在浏览器或节点环境中运行机器学习模型和深度学习神经网络。

tf.data.Dataset 类 .prefetch()函数用于生成从给定数据集中预取指定元素的数据集。

句法:

prefetch (bufferSize)

参数:此函数接受一个参数,如下所示:

  • bufferSize:它是一个整数值,指定要预取的元素个数。

返回值:它返回元素的数据集。

示例 1:

Javascript
// Importing the tensorflow.js library
import * as tf from "@tensorflow/tfjs"
 
// Calling the .prefetch() function over
// the specified dataset of some elements
const a = tf.data.array([5, 10, 15, 20]).prefetch(4);
 
// Getting the dataset of prefetched elements
await a.forEachAsync(a => console.log(a));


Javascript
// Importing the tensorflow.js library
import * as tf from "@tensorflow/tfjs"
 
// Specifying a dataset of some elements
const a = tf.data.array(["a", "b", "c", "d", "e"]);
 
// Calling the .prefetch() function over
// the above dataset along with the
// batch of size 2
const b = a.batch(2)
const c = b.prefetch(2)
 
// Getting the dataset of prefetched elements
await c.forEachAsync(c => console.log(c));


输出:

5
10
15
20

示例 2:

Javascript

// Importing the tensorflow.js library
import * as tf from "@tensorflow/tfjs"
 
// Specifying a dataset of some elements
const a = tf.data.array(["a", "b", "c", "d", "e"]);
 
// Calling the .prefetch() function over
// the above dataset along with the
// batch of size 2
const b = a.batch(2)
const c = b.prefetch(2)
 
// Getting the dataset of prefetched elements
await c.forEachAsync(c => console.log(c));

输出:

Tensor
    ['a', 'b']
Tensor
    ['c', 'd']
Tensor
    ['e']

参考: https://js.tensorflow.org/api/latest/#tf.data.Dataset.prefetch