I have Tensorflow installed on the Debian Server using virtual environment
export url=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.5.0-cp34-cp34m-linux_x86_64.whl
pip3 install --user $url
This installs tensorflow-gpu==1.5.0 on ~/.local/lib/python3.4/site-packages
But when I import tensor flow package in Ipython notebook like:
import tensorflow as tf
I get the following error:
ImportError: libcublas.so.9.0: cannot open shared object file: No such file or directory
In /usr/local/cuda-8.0 I do have ./lib64/libcublas.so.8.0. Then why can't Tensorflow find it? Now do I need to install cuda-9.0? Unfortunately, I don't have root permissions on the system. Is there a way around this?
Thanks in advance,
Related
I installed the numpy with Conda, pip and pip3, also tried installing from the requirements.txt file but I am still getting the following issue. Has anyone encountered this before and could please kindly suggest something?
ModuleNotFoundError Traceback (most recent call last)
/tmp/ipykernel_732/1818554654.py in
1 import os
----> 2 import numpy as np
3 import matplotlib.pyplot as plt
4 import pandas as pd
5 import random
ModuleNotFoundError: No module named 'numpy'
numpy is built-in the default:Python environment in Studio Lab. If you open a new notebook with the File -> New -> Notebook, and choose the default:Python kernel, you should be able to import numpy without having to install the package.
If you would like to have a reproducible environment with a set of packages, see this sample repo on creating custom environments.
Numpy isn't preinstalled as a module you will need to install it yourself using pip or conda. Using notebooks just include a code block with the following:
!python -m pip install numpy
Suggestion to compile a list of required modules in a 'requirements.txt' file and install using:
!python -m pip install -r requirements.txt
Just as an FYI, the base package list is as follows:
Python 3.9 bzip2 build-essential curl git libgl1-mesa-glx nano rsync
unzip wget ca-certificates pip ipykernel-6.4
Have a look at this link for more info.
SageMaker - Manage your environment
from tensorflow.keras.preprocessing.text import Tokenizer
ImportError: No module named keras.preprocessing.text
Any solution?
thank you
my operating system: Ubuntu 19.10
Upgrade your keras package to latest version with command
pip install -U pip keras tensorflow
I installed tensorflow 2.0 from source, following the official instructions: https://www.tensorflow.org/install/source
It works when I access from python console (Outside of tensorflow folder), I want to get access from Jupyter notebook.
I copied tensorflow's folder to:
/home/kati/anaconda3/pkgs/tensorflow
but still not working
ModuleNotFoundError Traceback (most recent call last)
<ipython-input-2-d6579f534729> in <module>
----> 1 import tensorflow
ModuleNotFoundError: No module named 'tensorflow'
System Info
Ubuntu 18.04.3
jupyter core : 4.5.0
jupyter-notebook : 6.0.0
Here are the steps:
Download Anaconda
Create a virtual environment and activate it
Install K̵e̵r̵a̵s̵ ̵a̵n̵d̵ TensorFlow etc.
Launch Jupyter Notebook
Since you already have Jupyter Notebook, you will need to create an env variable, install tensorflow and keras. Commands are mentioned below:
update conda in your default environment
$ conda upgrade --all
create a new environment with conda
$ conda create -n [my-env-name] python=[python-version]
activate the environment you created
$ source activate [my-env-name]
install pip in the virtual environment
$ conda install pip
install Tensorflow CPU version
$ pip3 install --upgrade tensorflow # for python 3.*
install Keras (Note: please install TensorFlow first)
$ pip install Keras
remove an environment
$ conda env remove --name [my-env-name]
Install pip package and then you can just use "pip install [package name]" command to install any package easily.
Did you start running jupyter notebook from the virtual environment which you installed tensorflow?
Also you don't need to copy tensorflow to anaconda3 folder it's better to install by using pip or anconda navigator.
pip install tensorflow
Reference:
https://pypi.org/project/tensorflow/
I am trying to install keras on an anaconda environment (OSX), because I want to use it with spyder - ipython. To do that I just used pip install keras (I already have tensorflow). After the installation when I call python 2.7 from the terminal, keras works fine. But, when I call python 3.5 or spyder and try to import keras I receive:
No module named 'keras'
I assume the issue might be with the PATHS on my MacBook, because which python returns
/usr/local/bin/python2.7
while which python3.5 (or spyder) returns
/Users/georgiospapadopoulos/anaconda/bin/python3.5
/Users/georgiospapadopoulos/anaconda/bin/spyder
Also, during pip install keras shows that
Requirement already satisfied: keras in /Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages
My ~/.bash_profile contains
# added by Anaconda3 2.4.0 installer
export PATH="/Users/georgiospapadopoulos/anaconda/bin:$PATH"
# added by Anaconda3 4.2.0 installer
export PATH="/Users/georgiospapadopoulos/anaconda/bin:$PATH"
export CUDA_HOME=/usr/local/cuda
export DYLD_LIBRARY_PATH="$DYLD_LIBRARY_PATH:$CUDA_HOME/lib"
export PATH="$CUDA_HOME/bin:$PATH"
# Setting PATH for Python 2.7
# The original version is saved in .bash_profile.pysave
#PATH="/Library/Frameworks/Python.framework/Versions/2.7/bin:${PATH}"
PATH="/usr/local/bin/python:$PATH"
export PATH
You are probably mixing up the virtual environments. The best way to handle this is to create a vertual env in Anaconda - say, neural-net-venv, and then open the terminal for that venv, and install keras and other related modules. Then go back to Anaconda dash and select that venv as active environment to work on. Then select Jupyter and Spyder and run your imports.
Note that you also should not mix your Python versions - if you must work on Py2 and Py3 - create separate virtual environments for both, install keras, theanos/tensorflows separately in these environments, and you should be good to go.
I have run this setup on MacOS and it works like a charm.
For installing keras in Anaconda, the best and hassle free way is just use open the anaconda prompt and then type:
conda install keras
Keras runs on either tensorflow or theano backends. Once the keras install is complete, just open the python shell and type
>>>import keras
If some error is thrown, then there must be some problem with the backend. So just open the anaconda prompt, and type
conda import tensorflow
theano also can be used. Nevertheless tensorflow is the default one.
I wanted to insatll keras on Anaconda, tried the above approach, but it still did not work. Specifically, I started Anaconda Navigator and then opened a Mac OS terminal in the base environment. Then I followed the conda install commands for keras and tensorflow. It worked fine for keras. But with tensorflow, I got the following error message:
Downloading and Extracting Packages
_tflow_select-2.3.0 | 3 KB | ######################################################### | 100%
ChecksumMismatchError: Conda detected a mismatch between the expected content and downloaded content
for url 'https://conda.anaconda.org/Anaconda/osx-64/_tflow_select-2.3.0-mkl.tar.bz2'.
download saved to: /Users/dlin/opt/anaconda3/pkgs/_tflow_select-2.3.0-mkl.tar.bz2
expected sha256: cc155b27e7bf91ec5370ce1fd2d5fceccbf13ac19706229674ba971fa3751446
actual sha256: aad248699de112a7a5ead1695dfdf51b5693c2927303844b29dd7d9138dc95b9
On Ubuntu 10.10, I am unable to install lxml to python 2.7. Here are the steps I take.
sudo su -
apt-get install python2.7
apt-get install python-lxml
Note when running the install for python-lxml package, the following appeared:
INFO: using unknown version '/usr/bin/python2.7' (debian_defaults not up-to-date?)"
Importing the module in python2.6 (the version that comes standard with Ubuntu) works. However, importing the module under python2.7 does not. So how does one install Python modules to a non-default Python installation?
Try to install libxml2, libxml2-dev, libxslt, libxslt-dev, python-dev. These are header files. Then try to install lxml again.
On Ubuntu 10.10 the python packages installed from the repositories get installed to /usr/lib/python2.6/dist-packages so one option is to add this path to your $PYTHONPATH environmental variable so python2.7 will look to the python2.6 directory for the libs.
What I've done on Ubuntu 10.10 is add
export PYTHONPATH="$PYTHONPATH:/usr/lib/python2.6/dist-packages"
to my .bashrc file, and also to my .gnomerc file. This sets the $PYTHONPATH for python instances started from the shell or from the gnome desktop. You should then be able to import the python libs which you have installed from the Ubuntu repositories in python2.7.
.bashrc and .gnomerc are both located in your home directory; you might have to create .gnomerc if it doesn't already exist. And one caution: I had a syntax error in my .gnomerc which stopped the gnome desktop from loading, and I couldn't log in. I had to use a recovery console to fix this syntax error and then I could log in again.
This seems a little hackish to me, so I'm interested in hearing better solutions.
Another solution might be to use the following code:
try:
from lxml import etree
except ImportError:
try:
# Python 2.5
import xml.etree.cElementTree as etree
except ImportError:
try:
# Python 2.5
import xml.etree.ElementTree as etree
except ImportError:
try:
# normal cElementTree install
import cElementTree as etree
except ImportError:
try:
# normal ElementTree install
import elementtree.ElementTree as etree
except ImportError:
print("Failed to import ElementTree from any known place")
[Source]
This will import lxml if it is available, or the original ElementTree otherwise.
I use this code for my application on Google App Engine (using Python 2.7): on the server it will use lxml, on my machine it will use ElementTree.
I have one easiest trick Just open synaptic package manager type "python-lxml" in search box it will show you all the dependencies and available packages select packages which you want to install and hit apply.