最新版tensorflow1.12-gpu安装详细避坑(windows10 64位+anaconda+cuda+cudnn+pycharm环境配置)

本文详细介绍了在Windows10 64位系统上,如何配置TensorFlow1.12-GPU版本的环境,包括安装Anaconda3、CUDA9.0和cudnn v7.1,以及PyCharm的环境配置。特别强调了不同软件版本的兼容性和环境变量设置的重要性,同时提供了安装过程中可能遇到的问题及解决方案。

摘要生成于 C知道 ,由 DeepSeek-R1 满血版支持, 前往体验 >

放假回家,在笔记本(老爷显卡)上捣腾上了最新的1.12版TensorFlow-gpu。具体配置如下:
windows10 64位,nvidia GT 745M(注意cuda加速平台只支持英伟达显卡);
anaconda3-5.2.0(内置python3.6);
cuda9.0.176,cudnn v7.1;
pycharm社区版。
也参考了很多博文,具体安装套路都差不多,关键一点就是各版本对应兼容,就会很顺利,不会各种报错。其他的细节会在下面详细说明。

1.anaconda
anaconda是基于python的科学计算平台,内置python,最人性化的是集成了数百个科学包,包括最常用的pandas,matplotlib,keras,numpy等,已经能满足大部分需求,不需要自己再安装各种包。截止目前,python已经更新到3.7,最新的anaconda3-5.3.1即是默认内置python3.7,而最新版1.12的TensorFlow只能支持python3.6(已经有大神解决了python3.7适配TensorFlow1.12的问题,可去站内搜索他们的博文参考),不想折腾,所以直接装上一个版本的anaconda,即anaconda3-5.2.0,内置python3.6(其实anaconda 的cmd可以直接把python3.7退回3.6或者之前更老的版本,见https://blog.youkuaiyun.com/jcdiv_/article/details/79095353,考虑到python环境可能会冲突,其实还是因为懒,所以直接装上一个版本的anadonda5.2)。
下载地址:https://www.anaconda.com/download/,
注意下64位的,TensorFlow只支持64位。
在这里插入图片描述

自编译tensorflow1.python3.5,tensorflow1.12; 2.支持cuda10.0,cudnn7.3.1,TensorRT-5.0.2.6-cuda10.0-cudnn7.3; 3.无mkl支持; 软硬件硬件环境:Ubuntu16.04,GeForce GTX 1080 TI 配置信息: hp@dla:~/work/ts_compile/tensorflow$ ./configure WARNING: --batch mode is deprecated. Please instead explicitly shut down your Bazel server using the command "bazel shutdown". You have bazel 0.19.1 installed. Please specify the location of python. [Default is /usr/bin/python]: /usr/bin/python3 Found possible Python library paths: /usr/local/lib/python3.5/dist-packages /usr/lib/python3/dist-packages Please input the desired Python library path to use. Default is [/usr/local/lib/python3.5/dist-packages] Do you wish to build TensorFlow with XLA JIT support? [Y/n]: XLA JIT support will be enabled for TensorFlow. Do you wish to build TensorFlow with OpenCL SYCL support? [y/N]: No OpenCL SYCL support will be enabled for TensorFlow. Do you wish to build TensorFlow with ROCm support? [y/N]: No ROCm support will be enabled for TensorFlow. Do you wish to build TensorFlow with CUDA support? [y/N]: y CUDA support will be enabled for TensorFlow. Please specify the CUDA SDK version you want to use. [Leave empty to default to CUDA 10.0]: Please specify the location where CUDA 10.0 toolkit is installed. Refer to README.md for more details. [Default is /usr/local/cuda]: /usr/local/cuda-10.0 Please specify the cuDNN version you want to use. [Leave empty to default to cuDNN 7]: 7.3.1 Please specify the location where cuDNN 7 library is installed. Refer to README.md for more details. [Default is /usr/local/cuda-10.0]: Do you wish to build TensorFlow with TensorRT support? [y/N]: y TensorRT support will be enabled for TensorFlow. Please specify the location where TensorRT is installed. [Default is /usr/lib/x86_64-linux-gnu]://home/hp/bin/TensorRT-5.0.2.6-cuda10.0-cudnn7.3/targets/x86_64-linux-gnu Please specify the locally installed NCCL version you want to use. [Default is to use https://github.com/nvidia/nccl]: Please specify a list of comma-separated Cuda compute capabilities you want to build with. You can find the compute capability of your device at: https://developer.nvidia.com/cuda-gpus. Please note that each additional compute capability significantly increases your build time and binary size. [Default is: 6.1,6.1,6.1]: Do you want to use clang as CUDA compiler? [y/N]: nvcc will be used as CUDA compiler. Please specify which gcc should be used by nvcc as the host compiler. [Default is /usr/bin/gcc]: Do you wish to build TensorFlow with MPI support? [y/N]: No MPI support will be enabled for TensorFlow. Please specify optimization flags to use during compilation when bazel option "--config=opt" is specified [Default is -march=native -Wno-sign-compare]: Would you like to interactively configure ./WORKSPACE for Android builds? [y/N]: Not configuring the WORKSPACE for Android builds. Preconfigured Bazel build configs. You can use any of the below by adding "--config=" to your build command. See .bazelrc for more details. --config=mkl # Build with MKL support. --config=monolithic # Config for mostly static monolithic build. --config=gdr # Build with GDR support. --config=verbs # Build with libverbs support. --config=ngraph # Build with Intel nGraph support. --config=dynamic_kernels # (Experimental) Build kernels into separate shared objects. Preconfigured Bazel build configs to DISABLE default on features: --config=noaws # Disable AWS S3 filesystem support. --config=nogcp # Disable GCP support. --config=nohdfs # Disable HDFS support. --config=noignite # Disable Apacha Ignite support. --config=nokafka # Disable Apache Kafka support. --config=nonccl # Disable NVIDIA NCCL support. Configuration finished 编译: bazel build --config=opt --verbose_failures //tensorflow/tools/pip_package:build_pip_package 卸载已有tensorflow: hp@dla:~/temp$ sudo pip3 uninstall tensorflow 安装自己编译的成果: hp@dla:~/temp$ sudo pip3 install tensorflow-1.12.0-cp35-cp35m-linux_x86_64.whl
评论 2
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值