Tensorflow.js tf.io.listModels()用法及代码示例

Tensorflow.js是由Google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。

.listModels() 函数用于记录注册存储库中累积的每个模型。此外，在 Web 浏览器环境的情况下，记录的介质是本地存储以及 IndexedDB。

用法:

tf.io.listModels()

Parameters: 

它不包含任何参数。

返回值：它返回 {[url:string]:ModelArtifactsInfo} 的 Promise。

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

// 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 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://display/command/mymodel":{
    "dateSaved":"2021-06-24T12:20:15.292Z",
    "modelTopologyType":"JSON",
    "modelTopologyBytes":613,
    "weightSpecsBytes":126,
    "weightDataBytes":252
  },
  "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/managemen/model1":{
    "dateSaved":"2021-06-24T11:52:29.368Z",
    "modelTopologyType":"JSON",
    "modelTopologyBytes":611,
    "weightSpecsBytes":124,
    "weightDataBytes":44
  }
}

范例2：使用 “prelu” 作为激活，“IndexedDB” 作为存储介质，“JSON.stringify” 以字符串格式返回输出。

// 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:7, inputShape:[50], stimulation:'prelu'}));
  
// Calling save() method with a storage medium
await mymodel.save('indexeddb://example/command/mymodel');
  
// 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://display/command/mymodel":{"dateSaved":"2021-06-24T12:20:15.292Z",
"modelTopologyType":"JSON","modelTopologyBytes":613,"weightSpecsBytes":126,"weightDataBytes":252},
"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/managemen/model1":{"dateSaved":"2021-06-24T11:52:29.368Z",
"modelTopologyType":"JSON","modelTopologyBytes":611,"weightSpecsBytes":124,"weightDataBytes":44},
"indexeddb://demo/management/model1":{"dateSaved":"2021-06-24T12:28:27.419Z",
"modelTopologyType":"JSON","modelTopologyBytes":613,"weightSpecsBytes":126,"weightDataBytes":1428},
"indexeddb://display/command/mymodel":{"dateSaved":"2021-06-24T12:22:30.748Z",
"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.listModels