ubuntu16.04 + GTX1060 + CUDA9.0 + CUDANN7.0 tensorflow (GPU) installed, the measured effective installation package I put a cloud dish, direct download. - Code World

ubuntu16.04 + GTX1060 + CUDA9.0 + CUDANN7.0 tensorflow (GPU) installed, the measured effective installation package I put a cloud dish, direct download.

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Origin blog.csdn.net/weixin_42535742/article/details/89501857

ubuntu16.04 + GTX1060 + CUDA9.0 + CUDANN7.0 tensorflow (GPU) installed, the measured effective installation package I put a cloud dish, direct download.

ubuntu16.04 + GTX1060 + CUDA9.0 + CUDANN7.0 tensorflow (GPU) установлено, измеренный эффективная установка пакет я положил облако блюда, прямая загрузка.

Ubuntu installation TensorFlow-gpu and cuda9.0 (not trouble yourself)

Dockerr installation environment ubuntu16.04 + CUDA10.0 + cudnn = 7.0 + Anaconda + tensorflow-gpu = 1.13.1

Ubuntu16.04 GTX750 installation CUDA9.0, Pytorch, Anaconda Guide

ubuntu16.04 + GTX1060 + CUDA9.0 + CUDANN7.0 tensorflow（GPU）をインストールし、私は雲皿、直接ダウンロードを入れて測定した効果的なインストールパッケージ。

ubuntu16.04 + GTX1060 + CUDA9.0 + CUDANN7.0 tensorflow (GPU)를 설치, 나는 구름 접시, 직접 다운로드를 넣어 측정 효과적인 설치 패키지.

cuda9.1 installation record of gtx1060

The DL IDE: detailed flow depth learning computer vision development environment built (Ubuntu16.04 + cuda9.0 + cuDNN7.4.2 + tensorflow-gpu)

TensorFlow environment configuration and installation (win10+GeForce GTX1060+CUDA 9.0+cuDNN7.3+tensorflow-gpu 1.12.0+python3.5.5)

CUDA11.6, CUDA11.3, CUDA10.2, CUDA9.0 installation package (windows10) [CUDA and Pytorch version correspondence table] [With corresponding version cudnn] [Baidu cloud link download]

And a corresponding version Installation CUDA9.0 under Ubuntu16.04 CUDNN

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