3 ms·
TensorFire is up to an order of magnitude faster than keras-js because it doesn't have to shuffle data back and forth between the gpu and cpu. Also TensorFire
by bijection 9y ago
TensorFire is up to an order of magnitude faster than keras-js because it doesn't have to shuffle data back and forth between the gpu and cpu. Also TensorFire can run on browsers and devices that don't support OES_TEXTURE_FLOAT.
We will probably release it under an MIT license.
- espadrine 9y agoHow does it compare to WebDNN[0]? It seems like a closer comparison, especially with WebGPU. It would be good if you had a comparative benchmark on the website. [0]: https://mil-tokyo.github.io/webdnn/ https://mil-tokyo.github.io/webdnn/
- bijection 9y agoAt the moment WebDNN only runs models on the GPU in Safari Technology Preview, falling back to CPU on all other platforms / browsers: https://mil-tokyo.github.io/webdnn/#compatibility https://mil-tokyo.github.io/webdnn/#compatibility
- zitterbewegung 9y agoI'm really interested in using Smartphones / Mobile devices for inference. Can this work with react-native so that I can build it without a bridge ? I would assume I would create a webview that would load a local website.