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> Kind of reminds me of assembly programmers that thought C wasn't for l33t 10xx pwner programmers. The problem with TensorFlow is mainly that you, as a user, have to build a data-dependency graph. This is something a C compiler can do very well, but Python is not so suitable for that. 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. However, computing a data-flow graph as-you-go (by the library, not the user), like (I think) is done in some libraries, is quite a good approach, since the overhead is quite small (percentage-wise) compared to the large tensor operations that can be performed in highly optimized code. |
You just described Swift for TensorFlow.