[sanxiyn]

> So, in my view, TensorFlow chose the wrong substrate for their "more efficient" library. Instead, they should have developed their own language, where the whole data-flow graph determination could be implicit, and not a concern for the programmer.

You just described Swift for TensorFlow.

[amelius]

Well, apparently :) They say: We believe that machine learning tools are so important that they deserve a first-class language and a compiler.

However, I'd like to see some numbers on how more efficient it is to build a graph in advance, given that the lion's share of the computations will be in tensor math anyway (which can be heavily optimized, and is independent of the graph).

[liuliu]

The problem is that if you build the graph as-you-go, dataflow graph optimizations cannot be done efficiently (some high level optimizations such as data layout optimization, automatic data / model parallelism etc.). Swift can do all these because the compiler can extract the graph out ahead of time.

[codetrotter]

> You just described Swift for TensorFlow

This one? https://www.tensorflow.org/api_docs/swift/

[SalimoS]

isn't work in progress ? https://github.com/tensorflow/swift/blob/master/docs/WhySwif...