P != NP
There's a new proof. Does not seem to require too much prior knowledge. Based on plays with boolean function normal forms (conjunctive and disjunctive).
https://arxiv.org/abs/1708.03486
https://arxiv.org/abs/1708.03486
TensorFlow GPU build for Windows for TensorFlowSharp
After two days of struggling, I was finally able to build libtensorflow.dll (v1.2.1) for Windows with GPU (CUDA 8 + CUDNN 6) support. TL;DR; here's the file (~160MB). It seems (so far) usable with TensorFlowSharp from Nuget, but you have to manually swap DLL in the package cache. UPD 2019-03-29 : instead of using TensorFlowSharp , I am now using Gradient - it provides access to the full Python API. And you don't have to manually build TensorFlow for GPU - just install Python 3.6, and follow the official TensorFlow instructions to install tensorflow 1.10 or tensorflow-gpu 1.10, or tensorflow-rocm for ATI. Gradient picks it up automatically or via GradientSetup class . Some notes on the build (in case you want to reproduce it): I used Visual Studio 2017 Despite mentioning only VS 2015 C++ compiler as compatible, I was able to build with VS 2017 compiler. Build with CMake CMake files are in ./tensorflow/contrib/cmake Do not forget SWIG Download and install SWIG.
Комментарии
Отправить комментарий