参考tensorflow 公众号《tensorflow2.0 安装指南》

https://mp.weixin.qq.com/s/7rNXFEC5HYe91RJ0-9CKdQ

# 1. NVIDIA驱动程序安装

安装对应的CUDA 和 cudnn  (在tensorflow 公众号《tensorflow2.0 安装指南》得知 2.0-beta1对应CUDA 10.0 cudnn 7.6.0)

之前安装tensorflow-gpu 1.14的时候安装了CUDA 10.0 和CUDNN 7.6.1

# 2. anaconda 环境创建与安装

conda create --name tf2.0 python=3.7

activate tf2.0

pip install -i https://pypi.tuna.tsinghua.edu.cn/simple tensorflow-gpu==2.0.0-beta1    ///清华源

# 3.测试

import tensorflow as tf

A = tf.constant([[1, 2], [3, 4]])
B = tf.constant([[5, 6], [7, 8]])
C = tf.matmul(A, B) print(C)

输出如下,安装成功

tf.Tensor(
[[19 22]
[43 50]], shape=(2, 2), dtype=int32)

中间输出了一些提示信息

(tf2.0) C:\Users\lenovo>python
Python 3.7.6 (default, Jan 8 2020, 20:23:39) [MSC v.1916 64 bit (AMD64)] :: Anaconda, Inc. on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow as tf
F:\Anaconda\envs\tf2.0\lib\site-packages\tensorflow\python\framework\dtypes.py:516: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint8 = np.dtype([("qint8", np.int8, 1)])
F:\Anaconda\envs\tf2.0\lib\site-packages\tensorflow\python\framework\dtypes.py:517: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_quint8 = np.dtype([("quint8", np.uint8, 1)])
F:\Anaconda\envs\tf2.0\lib\site-packages\tensorflow\python\framework\dtypes.py:518: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint16 = np.dtype([("qint16", np.int16, 1)])
F:\Anaconda\envs\tf2.0\lib\site-packages\tensorflow\python\framework\dtypes.py:519: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_quint16 = np.dtype([("quint16", np.uint16, 1)])
F:\Anaconda\envs\tf2.0\lib\site-packages\tensorflow\python\framework\dtypes.py:520: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint32 = np.dtype([("qint32", np.int32, 1)])
F:\Anaconda\envs\tf2.0\lib\site-packages\tensorflow\python\framework\dtypes.py:525: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
np_resource = np.dtype([("resource", np.ubyte, 1)])
F:\Anaconda\envs\tf2.0\lib\site-packages\tensorboard\compat\tensorflow_stub\dtypes.py:541: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint8 = np.dtype([("qint8", np.int8, 1)])
F:\Anaconda\envs\tf2.0\lib\site-packages\tensorboard\compat\tensorflow_stub\dtypes.py:542: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_quint8 = np.dtype([("quint8", np.uint8, 1)])
F:\Anaconda\envs\tf2.0\lib\site-packages\tensorboard\compat\tensorflow_stub\dtypes.py:543: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint16 = np.dtype([("qint16", np.int16, 1)])
F:\Anaconda\envs\tf2.0\lib\site-packages\tensorboard\compat\tensorflow_stub\dtypes.py:544: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_quint16 = np.dtype([("quint16", np.uint16, 1)])
F:\Anaconda\envs\tf2.0\lib\site-packages\tensorboard\compat\tensorflow_stub\dtypes.py:545: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint32 = np.dtype([("qint32", np.int32, 1)])
F:\Anaconda\envs\tf2.0\lib\site-packages\tensorboard\compat\tensorflow_stub\dtypes.py:550: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
np_resource = np.dtype([("resource", np.ubyte, 1)])
>>> A=tf.constant([[1,2],[3,4]])
2020-02-02 16:05:20.597693: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library nvcuda.dll
2020-02-02 16:05:23.206508: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1640] Found device 0 with properties:
name: GeForce GTX 1050 major: 6 minor: 1 memoryClockRate(GHz): 1.493
pciBusID: 0000:01:00.0
2020-02-02 16:05:23.215470: I tensorflow/stream_executor/platform/default/dlopen_checker_stub.cc:25] GPU libraries are statically linked, skip dlopen check.
2020-02-02 16:05:23.224739: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1763] Adding visible gpu devices: 0
2020-02-02 16:05:23.231882: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
2020-02-02 16:05:23.244758: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1640] Found device 0 with properties:
name: GeForce GTX 1050 major: 6 minor: 1 memoryClockRate(GHz): 1.493
pciBusID: 0000:01:00.0
2020-02-02 16:05:23.259879: I tensorflow/stream_executor/platform/default/dlopen_checker_stub.cc:25] GPU libraries are statically linked, skip dlopen check.
2020-02-02 16:05:23.269339: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1763] Adding visible gpu devices: 0
2020-02-02 16:05:24.446747: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1181] Device interconnect StreamExecutor with strength 1 edge matrix:
2020-02-02 16:05:24.456384: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1187] 0
2020-02-02 16:05:24.460137: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1200] 0: N
2020-02-02 16:05:24.466395: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1326] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 1347 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1050, pci bus id: 0000:01:00.0, compute capability: 6.1)
>>> B=tf.constant([[1,2],[3,4]])
>>> B=tf.constant([[5,6],[7,8]])
>>> C=tf.matmul(A,B)
>>> print(C)
tf.Tensor(
[[19 22]
[43 50]], shape=(2, 2), dtype=int32)
>>>

# 4. IDE设置 PyCharm

点击蓝圈处,add,选择对应的环境

# 5 偶尔遇到的问题  no module named tensorflow

有一次   import  tensorflow 时报没有这个module,试了好几次也不行,重启终端好了,不知道是什么原因(汗)

anaconda python3.7 安装 tensorflow-gpu 2.0.0 beta1 配置PyCharm的更多相关文章

  1. 通过Anaconda在Ubuntu16.04上安装 TensorFlow(GPU版本)

    一. 安装环境 Ubuntu16.04.3 LST GPU: GeForce GTX1070 Python: 3.5 CUDA Toolkit 8.0 GA1 (Sept 2016) cuDNN v6 ...

  2. tensor搭建--windows 10 64bit下安装Tensorflow+Keras+VS2015+CUDA8.0 GPU加速

    windows 10 64bit下安装Tensorflow+Keras+VS2015+CUDA8.0 GPU加速 原文见于:http://www.jianshu.com/p/c245d46d43f0 ...

  3. Ubuntu在Anaconda中安装TensorFlow GPU,Keras,Pytorch

    安装TensorFlow GPU pip install --ignore-installed --upgrade tensorflow-gpu 安装测试: $ source activate tf ...

  4. Windows10+anaconda,python3.5, 安装glove-python

    Windows10+anaconda,python3.5, 安装glove-python安装glove安装之前 Visual C++ 2015 Build Tools开始安装安装glove最近因为一个 ...

  5. Python3 离线安装TensorFlow包

    Python3 离线安装TensorFlow包 1,下载包 官网地址:https://pypi.org/project/tensorflow/1.1.0rc2/#files 清华镜像:https:// ...

  6. windows 10 64bit下安装Tensorflow+Keras+VS2015+CUDA8.0 GPU加速

    原文地址:http://www.jianshu.com/p/c245d46d43f0 写在前面的话 2016年11月29日,Google Brain 工程师团队宣布在 TensorFlow 0.12 ...

  7. Anaconda 安装tensorflow(GPU)

    1.安装 如果是安装CPU模式的tensorflow,只要输入一下代码就可以了 pip3 install tensorflow #python3pip install tensorflow #pyth ...

  8. Windows7 64bits下安装TensorFlow GPU版本(图文详解)

    不多说,直接上干货! Installing TensorFlow on Windows的官网 https://www.tensorflow.org/install/install_windows 首先 ...

  9. win10系统下安装TensorFlow GPU版本

    首先要说,官网上的指南是最好的指南. https://www.tensorflow.org/install/install_windows 需要FQ看. 想要安装gpu版本的TensorFlow.我们 ...

随机推荐

  1. 2.4V升5V芯片,8uA功耗,低功耗升压电路图

    2.4V升5V,可用于USB拔插充电,也可以用于把两节镍氢电池2.4V升压到5V,的固定输出稳压电压值,同时输出电流可达1A,0.5A等 首先是先说下0.5A的这款的话,是比较低功耗的,8uA左右的输 ...

  2. JSAAS BPM快速开发平台-企业管理软件,专属你的企业管家

    前言: 2020年,企业该如何去选择合适的信息化规划管理软件,基于目前社会软件杂乱无章,选择企业业务贴近的管理软件,甚是困难,市场上一些大品牌公司的产品,定位高,价格高,扩展难,等等一系列的问题,对于 ...

  3. ETCD数据迁移

    ETCD数据迁移 本文阅读对象为想要将Rainbond平台rbd-etcd切换至外部etcd的相关人员. 在k8s master节点创建secret 本文中将要切换的ETCD为根据Rainbond官方 ...

  4. CSS奇思妙想 -- 使用 CSS 创造艺术

    本文属于 CSS 绘图技巧其中一篇.之前有过一篇:在 CSS 中使用三角函数绘制曲线图形及展示动画 想写一篇关于 CSS 创造艺术的文章已久,本文主要介绍如何借助 CSS-doodle ,利用 CSS ...

  5. 常用的hadoop和yarn的端口总结

    节点 默认端口 用途说明 HDFS DataNode 50010 datanode服务端口,用于数据传输 50075 http服务的端口 50475 https服务的端口 50020 ipc服务的端口 ...

  6. Java反序列化: 基于CommonsCollections4的Gadget分析 Java 序列化与反序列化安全分析

    Java反序列化: 基于CommonsCollections4的Gadget分析 welkin 京东安全 5天前 https://mp.weixin.qq.com/s/OqIWUsJe9XV39SPN ...

  7. POSTGIS

    https://blog.csdn.net/qq_35732147/article/details/85256640 官方文档:http://www.postgis.net/docs/ST_Buffe ...

  8. Hive on MR调优

    当HiveQL跑不出来时,基本上是数据倾斜了,比如出现count(distinct),groupby,join等情况,理解 MR 底层原理,同时结合实际的业务,数据的类型,分布,质量状况等来实际的考虑 ...

  9. 飞塔5.4和5.6版本IPSec互备冗余测试

    主电信.备联通:测试方法:修改诚盈的IPSec,将阶段一电信的对端地址改为错误的. 方法一: 通过静态路由的管理距离:电信设置为10:联通为15.经测试,可以实现自动切换,且电信恢复后 可以切换回电信 ...

  10. .NET使用DinkToPdf将HTML转成PDF

    0.介绍 C# .NET Core wrapper for wkhtmltopdf library that uses Webkit engine to convert HTML pages to P ...