AI News, Frequently Asked Questions

Frequently Asked Questions

This allows the same JavaScript code to work on both the browser and node.js, while binding to the underlying TensorFlow C implementation in node.

For training, we have seen small models train faster in the browser and large models train up to 10-15x slower in the browser, compared to TensorFlow Python with AVX.

TensorFlow.js also includes a Layers API—a higher level library for building machine learning models—as well as tools for automatically porting TensorFlow SavedModels and Keras HDF5 models.

We also have a community mailing list for people to ask questions, get technical help, and share what they are doing with TensorFlow.js!

tensorflow/tfjs-converter

TensorFlow.js converter is an open source library to load a pretrained TensorFlow

2-step process to import your model: Usage: SavedModel example: Frozen model example: Session bundle model example: Tensorflow Hub module example: Keras h5 model example: The conversion script above produces 3 types of files: For example, here is the MobileNet model converted and served in following

location: yarn add @tensorflow/tfjs-converter or npm install @tensorflow/tfjs-converter Check out our working MobileNet demo.

While the browser supports loading 100-500MB models, the page load time, the inference time and the user experience would not be great.

You can warm up the cache by calling the predict method with an all zero inputs, right after the completion of the model loading.

Before submitting a pull request, make sure the code passes all the tests and is clean of lint errors: To run a subset of tests and/or on a specific browser: To run the tests once and exit the karma process (helpful on Windows): To generate the static js file for GraphDef proto, run following steps:

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