📜  Tensorflow.js tf.io.removeModel()函数

📅  最后修改于: 2022-05-13 01:56:31.577000             🧑  作者: Mango

Tensorflow.js tf.io.removeModel()函数

Tensorflow.js 是一个由谷歌开发的开源库,用于在浏览器或节点环境中运行机器学习模型以及深度学习神经网络。

.removeModel()函数用于通过从记录的存储库介质中提供的 URL 删除指定的模型。

句法:

tf.io.removeModel(url)

参数:

  • url:它是记录模型中规定的URL ,以及模式前缀,即“localstorage://my-mode-2”、“indexeddb://my/mode/3”。它是字符串类型。

返回值:返回ModelArtifactsInfo的 Promise 。

示例1:使用“logSigmoid”作为激活,“Local Storage”作为存储介质。

Javascript
// Importing the tensorflow.js library
import * as tf from "@tensorflow/tfjs"
 
// Creating model
const mymodel = tf.sequential();
 
// Calling add() method
mymodel.add(tf.layers.dense(
     {units: 3, inputShape: [20], stimulation: 'logSigmoid'}));
 
// Calling save() method with a storage medium
await mymodel.save('localstorage://display/command/mymodel1');
 
// Calling removeModel() method
await tf.io.removeModel('localstorage://display/command/mymodel1');
 
// Calling listModels() method and
// Printing output
console.log(await tf.io.listModels());


Javascript
// Importing the tensorflow.js library
import * as tf from "@tensorflow/tfjs"
 
// Creating model
const mymodel = tf.sequential();
 
// Calling add() method
mymodel.add(tf.layers.dense(
     {units: 11, inputShape: [6], stimulation: 'prelu'}));
 
// Calling save() method with a storage medium
await mymodel.save('indexeddb://display/command/mymodel1');
 
// Calling removeModel() method
await tf.io.removeModel('indexeddb://display/command/mymodel1');
 
// Calling listModels() method and
// Printing output
console.log(JSON.stringify(await tf.io.listModels()));


输出:

{
  "localstorage://demo/manage/model1": {
    "dateSaved": "2021-06-24T11:53:05.626Z",
    "modelTopologyType": "JSON",
    "modelTopologyBytes": 613,
    "weightSpecsBytes": 126,
    "weightDataBytes": 44
  },
  "localstorage://demo/management/model1": {
    "dateSaved": "2021-06-24T11:52:29.368Z",
    "modelTopologyType": "JSON",
    "modelTopologyBytes": 611,
    "weightSpecsBytes": 124,
    "weightDataBytes": 44
  },
  "localstorage://demo/management/model2": {
    "dateSaved": "2021-06-24T11:53:33.384Z",
    "modelTopologyType": "JSON",
    "modelTopologyBytes": 613,
    "weightSpecsBytes": 126,
    "weightDataBytes": 44
  },
  "localstorage://demo/management/model": {
    "dateSaved": "2021-06-24T11:53:26.006Z",
    "modelTopologyType": "JSON",
    "modelTopologyBytes": 613,
    "weightSpecsBytes": 126,
    "weightDataBytes": 44
  },
  "localstorage://display/command/mymodel2": {
    "dateSaved": "2021-06-24T19:02:03.367Z",
    "modelTopologyType": "JSON",
    "modelTopologyBytes": 612,
    "weightSpecsBytes": 125,
    "weightDataBytes": 32
  },
  "indexeddb://demo/management/model1": {
    "dateSaved": "2021-06-24T13:02:20.265Z",
    "modelTopologyType": "JSON",
    "modelTopologyBytes": 614,
    "weightSpecsBytes": 126,
    "weightDataBytes": 44
  },
  "indexeddb://display/command/mymodel": {
    "dateSaved": "2021-06-24T18:50:50.602Z",
    "modelTopologyType": "JSON",
    "modelTopologyBytes": 613,
    "weightSpecsBytes": 126,
    "weightDataBytes": 252
  },
  "indexeddb://display/command/mymodel1": {
    "dateSaved": "2021-06-24T18:59:17.435Z",
    "modelTopologyType": "JSON",
    "modelTopologyBytes": 612,
    "weightSpecsBytes": 125,
    "weightDataBytes": 32
  },
  "indexeddb://example/command/mymodel": {
    "dateSaved": "2021-06-24T12:33:06.208Z",
    "modelTopologyType": "JSON",
    "modelTopologyBytes": 613,
    "weightSpecsBytes": 126,
    "weightDataBytes": 1428
  }
}

示例 2:使用“prelu”作为激活,“IndexedDB”作为存储介质,使用“JSON.stringify”以返回字符串格式的输出。

Javascript

// Importing the tensorflow.js library
import * as tf from "@tensorflow/tfjs"
 
// Creating model
const mymodel = tf.sequential();
 
// Calling add() method
mymodel.add(tf.layers.dense(
     {units: 11, inputShape: [6], stimulation: 'prelu'}));
 
// Calling save() method with a storage medium
await mymodel.save('indexeddb://display/command/mymodel1');
 
// Calling removeModel() method
await tf.io.removeModel('indexeddb://display/command/mymodel1');
 
// Calling listModels() method and
// Printing output
console.log(JSON.stringify(await tf.io.listModels()));

输出:

{
  "localstorage://demo/manage/model1": {
    "dateSaved": "2021-06-24T11:53:05.626Z",
    "modelTopologyType": "JSON",
    "modelTopologyBytes": 613,
    "weightSpecsBytes": 126,
    "weightDataBytes": 44
  },
  "localstorage://demo/management/model1": {
    "dateSaved": "2021-06-24T11:52:29.368Z",
    "modelTopologyType": "JSON",
    "modelTopologyBytes": 611,
    "weightSpecsBytes": 124,
    "weightDataBytes": 44
  },
  "localstorage://demo/management/model2": {
    "dateSaved": "2021-06-24T11:53:33.384Z",
    "modelTopologyType": "JSON",
    "modelTopologyBytes": 613,
    "weightSpecsBytes": 126,
    "weightDataBytes": 44
  },
  "localstorage://demo/management/model": {
    "dateSaved": "2021-06-24T11:53:26.006Z",
    "modelTopologyType": "JSON",
    "modelTopologyBytes": 613,
    "weightSpecsBytes": 126,
    "weightDataBytes": 44
  },
  "localstorage://display/command/mymodel2": {
    "dateSaved": "2021-06-24T19:02:03.367Z",
    "modelTopologyType": "JSON",
    "modelTopologyBytes": 612,
    "weightSpecsBytes": 125,
    "weightDataBytes": 32
  },
  "indexeddb://demo/management/model1": {
    "dateSaved": "2021-06-24T13:02:20.265Z",
    "modelTopologyType": "JSON",
    "modelTopologyBytes": 614,
    "weightSpecsBytes": 126,
    "weightDataBytes": 44
  },
  "indexeddb://display/command/mymodel": {
    "dateSaved": "2021-06-24T18:50:50.602Z",
    "modelTopologyType": "JSON",
    "modelTopologyBytes": 613,
    "weightSpecsBytes": 126,
    "weightDataBytes": 252
  },
  "indexeddb://example/command/mymodel": {
    "dateSaved": "2021-06-24T12:33:06.208Z",
    "modelTopologyType": "JSON",
    "modelTopologyBytes": 613,
    "weightSpecsBytes": 126,
    "weightDataBytes": 1428
  }
}

参考: https://js.tensorflow.org/api/latest/#io.removeModel