Tensorflow.js tf.io.moveModel()函数

Tensorflow.js 是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。

.moveModel()函数用于将模型从一个 URL 移到一个新 URL。此外，该方法有利于在存储介质内部，即在相同种类的记录介质内或在两个存储介质之间，即在不同种类的记录介质之间移动。

句法：

tf.io.moveModel(sourceURL, destURL)

参数：

• sourceURL：指定的移动源URL。它是字符串类型。
• destURL：是指定的移动目标URL。它是字符串类型。

返回值：返回ModelArtifactsInfo的 Promise 。

示例 1：

• 两种不同存储介质之间的移动。
• 使用“logSigmoid”作为激活，“Local Storage”和“IndexedDB”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/mymodel');
 
// Calling moveModel() method with its parameters
await tf.io.moveModel(
     'localstorage://display/command/mymodel',
     'indexeddb://display/command/mymodel1');
 
// Calling listModels() method and
// Printing output
console.log(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/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://demo/management/model1": {
    "dateSaved": "2021-06-24T11:52:29.368Z",
    "modelTopologyType": "JSON",
    "modelTopologyBytes": 611,
    "weightSpecsBytes": 124,
    "weightDataBytes": 44
  },
  "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": "2021-06-24T18:55:00.803Z",
    "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
  }
}

示例 2：

• 在同种存储介质内移动。
• 使用“prelu”作为激活，“Local Storage”作为存储介质和“JSON.stringify”，以便以字符串格式返回输出。

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: 1, inputShape: [7], stimulation: 'prelu'}));
 
// Calling save() method with a storage medium
await mymodel.save('localstorage://display/command/mymodel1');
 
// Calling moveModel() method with its parameters
await tf.io.moveModel(
     'localstorage://display/command/mymodel1',
     'localstorage://display/command/mymodel2');
 
// 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
    }
}

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