React Native with TypeScript tfjs-models/universal-sentence-encoder 模型加载错误

Question

我正在按照 these instructions 在 React Native 应用程序中使用 tfjs-models/universal-sentence-encoder。但是，当我尝试加载模型时出现以下错误：

ERROR: TypeError: undefined is not an object (evaluating '_universalSentenceEncoder.default.load'

代码：

import React, { useEffect, useState } from 'react';
require('@tensorflow/tfjs');
const use = require('@tensorflow-models/universal-sentence-encoder');

export default function App() {

  useEffect(() => {
    console.log("App is starting...")
    
    const init = async () => {
      // initialize state variables 
      // console.log("App is initializing services...")
      
      // Load the model.
      try {
        use.load().then((model: any) => {
          // Embed an array of sentences.
          const sentences = [
            'Hello.',
            'How are you?'
          ];
          model.embed(sentences).then((embeddings: any) => {
            // `embeddings` is a 2D tensor consisting of the 512-dimensional embeddings for each sentence.
            // So in this example `embeddings` has the shape [2, 512].
            embeddings.print(true /* verbose */);
          });
        });
      }
      catch (err) {
        console.log(`ERROR: ${err}`);
      }
    };
  }, []);

包版本：

react-native@0.63.3
@tensorflow-models/universal-sentence-encoder@1.3.2
@tensorflow/tfjs@3.6.0
@tensorflow/tfjs-react-native@0.5.0

Answer 1

我认为这与您导入 universal-sentence-encoder 的方式有关，试试这个：

import React, { useEffect, useState } from 'react';
import * as use from '@tensorflow-models/universal-sentence-encoder';

export default function App() {

  useEffect(() => {
    console.log("App is starting...")
    
    const init = async () => {
      // initialize state variables 
      // console.log("App is initializing services...")
      
      // Load the model.
      try {
        use.load().then((model: any) => {
          // Embed an array of sentences.
          const sentences = [
            'Hello.',
            'How are you?'
          ];
          model.embed(sentences).then((embeddings: any) => {
            // `embeddings` is a 2D tensor consisting of the 512-dimensional embeddings for each sentence.
            // So in this example `embeddings` has the shape [2, 512].
            embeddings.print(true /* verbose */);
          });
        });
      }
      catch (err) {
        console.log(`ERROR: ${err}`);
      }
    };
  }, []);

Answer 2

yudhiesh 提供的答案修复了引用的错误，但产生了另一个错误。需要对代码进行更多更改，@tensorflow/tfjs 需要从 3.3.0 降级到 3.0.0（在 this post 之后）。

这是更新后的代码：

import React, { useEffect, useState } from 'react';
import "@tensorflow/tfjs-react-native";
import * as tf from '@tensorflow/tfjs';
import * as use from '@tensorflow-models/universal-sentence-encoder';

export default function App() {

  useEffect(() => {
    console.log("App is starting...")
    
    const init = async () => {
      // initialize state variables 
      // console.log("App is initializing services...")
      
      await tf.ready();
      
      // Load the model.
      try {
        use.load().then((model: any) => {
          // Embed an array of sentences.
          const sentences = [
            'Hello.',
            'How are you?'
          ];
          model.embed(sentences).then((embeddings: any) => {
            // `embeddings` is a 2D tensor consisting of the 512-dimensional embeddings for each sentence.
            // So in this example `embeddings` has the shape [2, 512].
            embeddings.print(true /* verbose */);
          });
        });
      }
      catch (err) {
        console.log(`ERROR: ${err}`);
      }
    };
  }, []);

注意 @tensorflow/tfjs-react-native 的导入，@tensorflow/tfjs、@tensorflow-models/universal-sentence-encoder 导入方式的变化，以及添加调用 await tf.ready() 以确保在之前初始化 tensorflow正在尝试加载使用模型。

当运行在 iOS 模拟器上运行时，此代码会按预期生成嵌入，但在我的物理设备上运行时，它会生成一个充满 NaNs 的嵌入向量iPhone。这可能是一个单独的问题，因此请考虑此问题已解决。

React Native with TypeScript tfjs-models/universal-sentence-encoder 模型加载错误

React Native with TypeScript tfjs-models/universal-sentence-encoder error on model load

typescript

react-native

tensorflow

tensorflow.js