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WebGL-accelerated ML // linear algebra // automatic differentiation for JavaScript. https://js.tensorflow.org
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nsthorat Assert dimensions of a shape are non-negative integers. (#1562)
BUG

Currently we check that the shape matches values in the tensor() factory method, this introduces an explicit integer check in buffer() and tensor() for integer dimensions.
Latest commit fef134c Feb 11, 2019
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.vscode Optimize tf.slice() and tf.unstack() for the WebGL and CPU backend (#… Jan 3, 2019
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scripts Test tfjs-data during core integration tests. (#1524) Feb 3, 2019
src Assert dimensions of a shape are non-negative integers. (#1562) Feb 11, 2019
.gitignore Collect benchmarks from karma and send them to firebase. (#1197) Aug 2, 2018
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.travis.yml Revert: Run tests in Node 8 instead of Node 10. #1450 (#1494) Jan 11, 2019
CONTRIBUTING.md Implement floordiv for integer division & update CONTRIBUTING.md. (#960) Apr 17, 2018
DEVELOPMENT.md Provide hint for Chrome Remote Desktop (#1479) Jan 4, 2019
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README.md Undo chrome extension testing change (#1456) Dec 13, 2018
karma.conf.js Add string dtype to Tensor (#1408) Nov 27, 2018
package.json Update core to 1.0.0-alpha3 (#1565) Feb 11, 2019
rollup.config.js build sourcemaps for esm bundle (#1160) Jul 12, 2018
tsconfig.json Preserve docs in npm package (#1533) Feb 5, 2019
tslint.json Make varianceEpsilon an optional param with a default value assigned … Feb 11, 2019
yarn.lock Ensure axis is validated against tensor shape length in unstack. (#1493) Jan 11, 2019

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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