5 ms·
There's absolutely no evidence that MXNet is faster than TF. At the high end, all three (TF/PyTorch/MXNet) are similarly performant. The reality is that impleme
by solidasparagus 7y ago
There's absolutely no evidence that MXNet is faster than TF. At the high end, all three (TF/PyTorch/MXNet) are similarly performant. The reality is that implementation matters more than framework when you are talking about performance.
- StreamBright 7y agoMy question was more about usability or interchangeability. Could TF get replaced by Mxnet in a typical deep learning project?
- solidasparagus 7y agoIn terms of features and functionality, they are very much interchangeable. A new project could be written in any of the three major frameworks and be equally good. The only standout feature I'm aware of is that TF has the best support for doing inference on devices, but that won't be true forever. In terms of actually migrating a codebase from one to the other, the APIs are different enough in small ways that it would be a large amount of effort.