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WebGL-accelerated ML // linear algebra // automatic differentiation for JavaScript. https://js.tensorflow.org
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dsmilkov Remove paging from the WebGL backend (#1647)
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Paging has been the source of various problems, so we've decided to remove it. Instead we will warn the user when the memory usage in WebGL is above a dynamically decided threshold.
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.travis.yml Remove command to log benchmarks since it's happening in union now. (#… Mar 12, 2019
CONTRIBUTING.md Implement floordiv for integer division & update CONTRIBUTING.md. (#960) Apr 17, 2018
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package.json Update core to 1.0.3 (#1645) Mar 25, 2019
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README.md

TensorFlow.js Core API

A part of the TensorFlow.js ecosystem, this repo hosts @tensorflow/tfjs-core, the TensorFlow.js Core API, which provides low-level, hardware-accelerated linear algebra operations and an eager API for automatic differentiation.

Check out js.tensorflow.org for more information about the library, tutorials and API docs.

To keep track of issues we use the tensorflow/tfjs Github repo.

Importing

You can install TensorFlow.js via yarn or npm. We recommend using the @tensorflow/tfjs npm package, which gives you both this Core API and the higher-level Layers API:

import * as tf from '@tensorflow/tfjs';
// You have the Core API: tf.matMul(), tf.softmax(), ...
// You also have Layers API: tf.model(), tf.layers.dense(), ...

On the other hand, if you care about the bundle size and you do not use the Layers API, you can import only the Core API:

import * as tfc from '@tensorflow/tfjs-core';
// You have the Core API: tfc.matMul(), tfc.softmax(), ...
// No Layers API.

For info about development, check out DEVELOPMENT.md.

For more information

Thanks BrowserStack for providing testing support.

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