tensorflow安装问题：ImportError：没有名为tensorflow的模块

Question

environments: Ubuntu 14.04(64bit) Python2.7.11

Firstly, I installed tensorflow in the way of Virtualenz installation.

$ sudo apt-get install python-pip python-dev python-virtualenv
$ virtualenv --system-site-packages ~/tensorflow
$ source ~/tensorflow/bin/activate  
$export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.12.1-cp27-none-linux_x86_64.whl

$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-0.12.1-cp27-none-linux_x86_64.whl

$ pip install --upgrade $TF_BINARY_URL

and then, I test my installation and some issue appear. I know I didn't install tensorflow successfully. import tensorflow Traceback (most recent call last): File "", line 1, in ImportError: No module named tensorflow

import tensorflow as tf Traceback (most recent call last): File "", line 1, in ImportError: No module named tensorflow

I don't know how to solve the problem. Please help me, it cost me one day. I tried to uninstall tensorflow and then I installed in the way of pip installation. But I get the same error. The protocbuf is 3.1.0.

Answer 1

Are you running python in the same virtual environment you installed tensorflow in?

To access your tensorflow installation, you have to first "activate" the virtualenv in any new terminals, as follows:

source ~/tensorflow/bin/activate
python
import tensorflow as tf

If you run the above in a new terminal, does it solve your problem?

Answer 2

When you did $ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-0.12.1-cp27-none-linux_x86_64.whl

this step you are specifying that you are going to use Nvidia card. To run tensorflow with GPU(Nvidia graphics card) you need to satisfy all Nvidia requirements

Nvidia requires some special privileges to its CUDA cores

You also need to check for Cuda pathnames to the LD_LIBRARY_PATH environment variable, check in Nvidia Documentation .Also, you need to install an profiling support, this can be done by libcupti-dev library, which is the NVIDIA CUDA Profile Tools Interface. This library provides advanced profiling support. To install this library, issue the following command: sudo apt-get install libcupti-dev

But if you want to run tensorflow in CPU mode only, do not specify $ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-0.12.1-cp27-none-linux_x86_64.whl .With this you are overriding TF_BINARY_URL variable to use Nvidia CUDA core So, to use CPU from all your steps remove $ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-0.12.1-cp27-none-linux_x86_64.whl and include only $export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.12.1-cp27-none-linux_x86_64.whl and reinstall

I hope this should clear the problem

Answer 3

In case, your prerequisite python packages are not installed properly, check several things.

$ source $HOME/tensorflow/bin/activate
$ which python
$ which pip

please check these binaries are in the path $HOME/tensorflow/bin/activate . If so, try

$ pip install -I --upgrade $TF_BINARY_URL

where -I option forces to install packages.

Answer 4

INSTALLATION OF TENSORFLOW ON UBUNTU 18.04

download anaconda python package

install it via shell using bash

$bash anaconda*.sh

editing the .bashrc script //location home

$sudo apt-get install python3-pip
$sudo apt-get update
$cd
$nano .bashrc

nano is the text editor insert the given line at the end of the file

export PATH=-/anaconda3/bin:$PATH

create a virtual environment using conda

$conda create -n myenv python=3.5

//SPECIFY THE VERSION REQUIRED DO NOT USE 3.7 AS THERE IS A COMPATIBLITY ISSUE WITH TENSORFLOW 10

$source activate myenv
$pip install -U tensorflow
$python
>>import tensorflow as tf
>>  //get this prompt without an error it means the installation is successful
>>exit()
source deactivate

fully tested if an issue arises do let me know whenever you install python packages i would suggest to do it in a virtual environment