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@tensorflow/tfjs-converter

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@tensorflow/tfjs-converter

Tensorflow model converter for javascript

  • 4.22.0
  • latest
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  • npm
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increased by11.93%
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What is @tensorflow/tfjs-converter?

@tensorflow/tfjs-converter is a library that allows you to import TensorFlow SavedModel and Keras models into TensorFlow.js. This enables you to run pre-trained models in the browser or in Node.js, making it easier to deploy machine learning models in web applications.

What are @tensorflow/tfjs-converter's main functionalities?

Import TensorFlow SavedModel

This feature allows you to import a TensorFlow SavedModel into TensorFlow.js. The code sample demonstrates how to load a SavedModel from a specified path and log the model to the console.

const tf = require('@tensorflow/tfjs');
const tfConverter = require('@tensorflow/tfjs-converter');

async function loadModel() {
  const model = await tfConverter.loadGraphModel('path/to/saved_model');
  console.log(model);
}

loadModel();

Import Keras Model

This feature allows you to import a Keras model into TensorFlow.js. The code sample demonstrates how to load a Keras model from a specified JSON file and log the model to the console.

const tf = require('@tensorflow/tfjs');
const tfConverter = require('@tensorflow/tfjs-converter');

async function loadKerasModel() {
  const model = await tfConverter.loadLayersModel('path/to/keras_model.json');
  console.log(model);
}

loadKerasModel();

Run Inference

This feature allows you to run inference using a loaded model. The code sample demonstrates how to load a SavedModel, create a tensor as input, run the model's predict function, and print the output.

const tf = require('@tensorflow/tfjs');
const tfConverter = require('@tensorflow/tfjs-converter');

async function runInference() {
  const model = await tfConverter.loadGraphModel('path/to/saved_model');
  const input = tf.tensor([1, 2, 3, 4]);
  const output = model.predict(input);
  output.print();
}

runInference();

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Package last updated on 21 Oct 2024

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