With a new SD card and Raspbian version Stretch 2018-11-13:
sudo apt install -y python3-pip python3-dev python-virtualenv
virtualenv -p python3.5 --system-site-packages myenv
source myenv/bin/activate
pip3 install --upgrade tensorflow
$ python3
Python 3.5.3 (default, Sep 27 2018, 17:25:39)
[GCC 6.3.0 20170516] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow
/home/pi/myenv/lib/python3.5/importlib/_bootstrap.py:222: RuntimeWarning: compiletime version 3.4 of module 'tensorflow.python.framework.fast_tensor_util' does not match runtime version 3.5
return f(*args, **kwds)
/home/pi/myenv/lib/python3.5/importlib/_bootstrap.py:222: RuntimeWarning: builtins.type size changed, may indicate binary incompatibility. Expected 432, got 412
return f(*args, **kwds)
>>>
Check if your Python environment is already configured (requires Python 3.4, 3.5, or 3.6):
The version of the tensorflow package that is installed by sudo python3 -m pip install --user --upgrade tensorflow has been upgraded since this question was originally posted. When this answer was last edited it required Python 3.7, 3.8, or 3.9. Check the current version of tensorflow at https://pypi.org/project/tensorflow/ before you install it.
python3 --version
pip3 --version
virtualenv --version
Install these packages if necessary:
sudo apt update
sudo apt install python3 python3-pip
TensorFlow requirements for the Raspbian operating system:
sudo apt update
sudo apt install python3-dev python3-pip
sudo apt install libatlas-base-dev # required for numpy
sudo python3 -m pip install --upgrade pip
sudo python3 -m pip install --upgrade virtualenv # system-wide install
Create a new virtual environment by choosing a Python interpreter and making a myenv directory to hold it:
virtualenv --system-site-packages -p python3 myenv
As you mentioned in your question, the python3 package version in Debian Stretch is 3.5.
Install TensorFlow (system install):
sudo python3 -m pip install --user --upgrade tensorflow
Verify the install:
python3 -c "import tensorflow as tf; tf.enable_eager_execution(); print(tf.reduce_sum(tf.random_normal([1000, 1000])))"
Success: TensorFlow is now installed. Read the tutorials to get started.
Related
On my Mac M1 (Monterey) I have created a new virtual environment with
virtualenv --python=/opt/homebrew/bin/python3.8 ~/.virtualenvs/datascience_env
to link it with specific Python 3.8 version. Now I'm trying to install tensorflow. The following command (issued in the virtual environment):
(datascience_env)% pip install tensorflow
causes the following error:
ERROR: Could not find a version that satisfies the requirement tensorflow (from versions: none)
ERROR: No matching distribution found for tensorflow
Just to be sure, I also did:
(datascience_env)% python -c "import sys; print(sys.version)" or python -c "import struct; print(struct.calcsize('P')*8)"
and the output confirms the 3.8 version:
3.8.14 (default, Sep 6 2022, 23:17:06)
[Clang 13.1.6 (clang-1316.0.21.2.5)]
I've finally opted for a simpler solution. I followed here the procedure to install Tensorflow on Mac M1 with miniforge. Works like a charm. In summary the steps are install miniforge, then:
conda config --set auto_activate_base false
conda create --name mytfenv python=3.8
conda activate mytfenv
conda install -c apple tensorflow-deps
pip install tensorflow-macos
pip install tensorflow-metal
conda install -c conda-forge -y pandas jupyter
The current default version of Python running on Google Colab is 3.7, but I need 3.9 for my notebooks to work.
How can I update Google Colab's Python version to 3.9 (or greater)?
In Google Colab you have a Debian-based Linux, and you can do whatever you can on a Debian Linux. Upgrading Python is as easy as upgrading it on your own Linux system.
Detect the current python version in Colab:
!python --version
#Python 3.8.16
Install new python version
Let's first install and upgrade to Python 3.9:
#install python 3.9
!sudo apt-get update -y
!sudo apt-get install python3.9
#change alternatives
!sudo update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.8 1
!sudo update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.9 2
#check python version
!python --version
#3.9.16
Port Colab kernel to the new installed python
As mentioned in the comments, the above commands just add a new python version to your google colab and update the default python for commandline usage. But your runtime packages such as sys are still running on the previous python version. The following commands need to be executed as well, to update the sys version.
# install pip for new python
!sudo apt-get install python3.9-distutils
!wget https://bootstrap.pypa.io/get-pip.py
!python get-pip.py
# credit of these last two commands blongs to #Erik
# install colab's dependencies
!python -m pip install ipython ipython_genutils ipykernel jupyter_console prompt_toolkit httplib2 astor
# link to the old google package
!ln -s /usr/local/lib/python3.8/dist-packages/google \
/usr/local/lib/python3.9/dist-packages/google
Now you can restart runtime and check the sys version. Note that in the new python version you have to install every packages, such as pandas, tensorflow, etc. from scratch.
Also, note that you can see a list of installed Python versions and switch between them at any time with this command:
(If nothing changed after installation, use this command to select python version manually)
!sudo update-alternatives --config python3
#after running, enter the row number of the python version you want.
It's also possible to update the kernel without going through ngrok or conda with some creative package installation.
Raha's answer suggesting making a link between the default google package and the newly installed Python version is the trick that makes this work because, at least with Python 3.9, the version of pandas (0.24.0) that the google package requires fails to build.
Here's the code I used to install and switch my Colab kernel to Python 3.9:
#install python 3.9 and dev utils
#you may not need all the dev libraries, but I haven't tested which aren't necessary.
!sudo apt-get update -y
!sudo apt-get install python3.9 python3.9-dev python3.9-distutils libpython3.9-dev
#change alternatives
!sudo update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.8 1
!sudo update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.9 2
#Check that it points at the right location
!python3 --version
# install pip
!curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py
!python3 get-pip.py --force-reinstall
#install colab's dependencies
!python3 -m pip install ipython ipython_genutils ipykernel jupyter_console prompt_toolkit httplib2 astor
# link to the old google package
!ln -s /usr/local/lib/python3.8/dist-packages/google \
/usr/local/lib/python3.9/dist-packages/google
# There has got to be a better way to do this...but there's a bad import in some of the colab files
# IPython no longer exposes traitlets like this, it's a separate package now
!sed -i "s/from IPython.utils import traitlets as _traitlets/import traitlets as _traitlets/" /usr/local/lib/python3.9/dist-packages/google/colab/*.py
!sed -i "s/from IPython.utils import traitlets/import traitlets/" /usr/local/lib/python3.9/dist-packages/google/colab/*.py
If Google updates from Python 3.8, you'll have to change the path to the default package.
Then go the Runtime menu and select Restart runtime. It should reconnect and choose the updated version of Python as the default kernel. You can check that it worked with:
#check python version
import sys
print(sys.version)
!python3 --version
!python --version
To use another python version in google colab, you need to:
1- Installing Anaconda.
2- Adding (fake) google colab library.
3- Starting Jupyterlab.
4- Accessing it with ngrok.
# install Anaconda3
!wget -qO ac.sh https://repo.anaconda.com/archive/Anaconda3-2020.07-Linux-x86_64.sh
!bash ./ac.sh -b
# a fake google.colab library
!ln -s /usr/local/lib/python3.6/dist-packages/google \
/root/anaconda3/lib/python3.8/site-packages/google
# start jupyterlab, which now has Python3 = 3.8
!nohup /root/anaconda3/bin/jupyter-lab --ip=0.0.0.0&
# access through ngrok, click the link
!pip install pyngrok -q
from pyngrok import ngrok
print(ngrok.connect(8888))
you can also use:
# Install the python version
!apt-get install python3.9
# Select the version
!python3.9 setup.py
another way is to use a virtual environment with your desired python version:
virtualenv env --python=python3.9
Update 24.12.2022 - Unfortunately, the method does not work anymore.
This worked for me (copied from GitHub), I successfully installed Python 3.10.
#The code below installs 3.10 (assuming you now have 3.8) and restarts environment, so you can run your cells.
import sys #for version checker
import os #for restart routine
if '3.10' in sys.version:
print('You already have 3.10')
else:
#install python 3.10 and dev utils
#you may not need all the dev libraries, but I haven't tested which aren't necessary.
!sudo apt-get update -y
!sudo apt-get install python3.10 python3.10-dev python3.10-distutils libpython3.10-dev
!sudo apt-get install python3.10-venv binfmt-support #recommended in install logs of the command above
#change alternatives
!sudo update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.8 1
!sudo update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.10 2
# install pip
!curl -sS https://bootstrap.pypa.io/get-pip.py | python3.10
!python3 get-pip.py --force-reinstall
#install colab's dependencies
!python3 -m pip install setuptools ipython ipython_genutils ipykernel jupyter_console prompt_toolkit httplib2 astor
#minor cleanup
!sudo apt autoremove
#link to the old google package
!ln -s /usr/local/lib/python3.8/dist-packages/google /usr/local/lib/python3.10/dist-packages/google
#this is just to verify if 3.10 folder was indeed created
!ls /usr/local/lib/python3.10/
#restart environment so you don't have to do it manually
os.kill(os.getpid(), 9)
In addition to Kaveh's answer, I added the following code. (This colab python version is python 3.8 and I tried to downgrade to python 3.7)
!pip install google-colab==1.0.0
# install colab's dependencies
!python -m pip install ipython==7.9.0 ipython_genutils==0.2.0 ipykernel==5.3.4 jupyter_console==6.1.0 prompt_toolkit==2.0.10 httplib2==0.17.4 astor==0.8.1 traitlets==5.7.1 google==2.0.3
This way, I solved the crashing runtime error.
Simple as that: -
!wget -O mini.sh https://repo.anaconda.com/miniconda/Miniconda3-py39_4.9.2-Linux-x86_64.sh
!chmod +x mini.sh
!bash ./mini.sh -b -f -p /usr/local
!conda install -q -y jupyter
!conda install -q -y google-colab -c conda-forge
!python -m ipykernel install --name "py39" --user
Source: https://colab.research.google.com/drive/1m47aWKayWTwqJG--x94zJMXolCEcfyPS?usp=sharing#scrollTo=r3sLiMIs8If3
screen shot
As Python2.7 will be deprecated on 01/01/2020. I was planning to start using python3. So, I tried to install the tensorflow==1.14.0 on the raspberry pi and it was successful, but when I am loading the Tensorflow for further operations then it throws a load error.
Python - 3.7 (Default installed by Raspbian OS)
Any suggestions why am I facing this issue?
Thanks for your time
You can't install later versions of Tensorflow on the Raspberry Pi using pip. You have to install from source. I made a video doing this: https://youtu.be/GNRg2P8Vqqs
Installing Tensorflow requires some extra steps on the Pi's ARM architecture.
This is how I installed tf 2.0 on my Pi 4:
Make your project directory:
cd Desktop
mkdir tf_pi
cd tf_pi
Make a virtual environment:
python3 -m pip install virtualenv
virtualenv env
source env/bin/activate
Run the commands based on https://github.com/PINTO0309/Tensorflow-bin/#usage:
sudo apt-get install -y libhdf5-dev libc-ares-dev libeigen3-dev
python3 -m pip install keras_applications==1.0.8 --no-deps
python3 -m pip install keras_preprocessing==1.1.0 --no-deps
python3 -m pip install h5py==2.9.0
sudo apt-get install -y openmpi-bin libopenmpi-dev
sudo apt-get install -y libatlas-base-dev
python3 -m pip install -U six wheel mock
Pick a tensorflow release from https://github.com/lhelontra/tensorflow-on-arm/releases (I picked 2.0.0). Picking a higher version of Tensorflow (like 2.1.0) requires a higher version of scipy that wasn't compatible with my Raspberry Pi:
wget https://github.com/lhelontra/tensorflow-on-arm/releases/download/v2.0.0/tensorflow-2.0.0-cp37-none-linux_armv7l.whl
python3 -m pip uninstall tensorflow
python3 -m pip install tensorflow-2.0.0-cp37-none-linux_armv7l.whl
RESTART YOUR TERMINAL
Reactivate your virtual environment:
cd Desktop
cd tf_pi
source env/bin/activate
Test:
Open a python interpreter by executing:
python3
import tensorflow
tensor.__version__
This should have no errors and output: 2.0.0
I got the same issue today when trying to run the fresh tf installation on my pi 3+
C:\Users\Sudhit> pip install --ignore-installed --upgrade storage.googleapis.com/tensorflow/windows/cpu/…
tensorflow-1.1.0-cp34-cp34m-win_amd64.whl is not a supported wheel on this platform.
How will I know which will be supported wheel for my platform?
This question already asked by someone here Tensorflow installation error: not a supported wheel on this platform
If you are using conda use below command to install tensorflow.
conda create --name tensorflow python=3.5
activate tensorflow
conda install jupyter
conda install scipy
pip install tensorflow
\# or
\# pip install tensorflow-gpu
or
On Linux
python2.7 -m pip install https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.5.0-cp27-none-linux_x86_64.whl
Tensorflow is only compatible for 64 bit version of Python. So, make sure it is by :
>python
Python 3.7.3 (v3.7.3:ef4ec6ed12, Mar 25 2019, 22:22:05) [MSC v.1916 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>>
Then, simply, upgrade pip using:
python -m pip install --upgrade pip
Lastly, install tensorflow:
pip install tensorflow
Done!
You can verify the install using:
python3 -c "import tensorflow as tf; print(tf.reduce_sum(tf.random.normal([1000, 1000])))"
For python 3.2 I used sudo apt-get install python3.2-numpy.It worked.
What to do for python3.3? Nothing I could think of works. Same goes for scipy, etc.
Thanks.
Edit: this is how it looks like
radu#sunlit-inspired:~$ python3
Python 3.3.2 (default, Jul 3 2013, 10:17:40)
[GCC 4.6.3] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import numpy
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
ImportError: No module named 'numpy'
In the solution below I used python3.4 as binary, but it's safe to use with any version or binary of python. it works fine on windows too (except the downloading pip with wget obviously but just save the file locally and run it with python).
This is great if you have multiple versions of python installed, so you can manage external libraries per python version.
So first, I'd recommend get-pip.py, it's great to install pip:
wget https://bootstrap.pypa.io/get-pip.py
Then you need to install pip for your version of python, I have python3.4 so for me this is the command:
python3.4 get-pip.py
Now pip is installed for this version and in order to get libraries for python3.4 I have to use pip like this:
python3.4 -m pip
So if I want to install numpy I'd use :
python3.4 -m pip install numpy
Note that numpy is quite the heavy library. I thought my system was hanging and failing.
But using the verbose option, you can see that the system is fine :
python3.4 -m pip install numpy -v
This may tell you that you lack python.h but you can easily get it :
On RHEL (Red hat, CentOS, Fedora) it would be something like this:
yum install python34-devel
On debian-like (Debian, Ubuntu, Kali, ...) :
apt-get install python34-dev
Then rerun this :
python3.4 -m pip install numpy -v
From the terminal run:
sudo apt-get install python3-numpy
This package contains Numpy for Python 3.
For scipy:
sudo apt-get install python3-scipy
For for plotting graphs use pylab:
sudo apt-get install python3-matplotlib
The normal way to install Python libraries is with pip. Your way of installing it for Python 3.2 works because it's the system Python, and that's the way to install things for system-provided Pythons on Debian-based systems.
If your Python 3.3 is system-provided, you should probably use a similar command. Otherwise you should probably use pip.
I took my Python 3.3 installation, created a virtualenv and run pip install in it, and that seems to have worked as expected:
$ virtualenv-3.3 testenv
$ cd testenv
$ bin/pip install numpy
blablabl
$ bin/python3
Python 3.3.2 (default, Jun 17 2013, 17:49:21)
[GCC 4.6.3] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import numpy
>>>
I'm on Ubuntu 15.04. This seemed to work:
$ sudo pip3 install numpy
On RHEL this worked:
$ sudo python3 -m pip install numpy
My issue was the failure to import numpy into my python files. I was receiving the "ModuleNotFoundError: No module named 'numpy'". I ran into the same issue and I was not referencing python3 on the installation of numpy. I inputted the following into my terminal for OSX and my problems were solved:
python3 -m pip install numpy
On fedora/rhel/centos you need to
sudo yum install -y python3-devel
before
mkvirtualenv -p /usr/bin/python3.3 test-3.3
pip install numpy
otherwise you'll get
SystemError: Cannot compile 'Python.h'. Perhaps you need to install python-dev|python-devel.