Tensorflow.js tf.io.listModels()用法及代碼示例

Tensorflow.js是由Google開發的開源庫，用於在瀏覽器或節點環境中運行機器學習模型以及深度學習神經網絡。

.listModels() 函數用於記錄注冊存儲庫中累積的每個模型。此外，在 Web 瀏覽器環境的情況下，記錄的介質是本地存儲以及 IndexedDB。

用法:

tf.io.listModels()

Parameters: 

它不包含任何參數。

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

範例1：使用 “logSigmoid” 作為激活，“Local Storage” 作為存儲介質。

// 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());

輸出：

{
  "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
  }
}

範例2：使用 “prelu” 作為激活，“IndexedDB” 作為存儲介質，“JSON.stringify” 以字符串格式返回輸出。

// 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()));

輸出：

{"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}}

參考： https://js.tensorflow.org/api/latest/#io.listModels