How can I set keras's backend to be MXNet?
I have found only this installation guide, but after I install keras by hand in this way, Anaconda does not recognize this installation.
In other words, this command:
KERAS_BACKEND=mxnet python -c "from keras import backend"
works only in the "keras" installation folder.
Therefore, I can not use keras in a Jupyter Notebook, for example.
Do you know another way to install keras in order to be compatible with mxnet (as it is for example on aws's AMIs) ?
You can install keras for a given Anaconda env by first activating that env and then calling
pip install -e .
in keras folder. In the guide that you included the link to, this command would replace
sudo python setup.py install
which installs it system wide.
Related
I am using jetson NX xavier kit having cuda 10.2.89, open Cv 4.1.1 and tensorRT 7.1.3 . Trying to install pytorch. Tried installing with this line
conda install pytorch torchvision cpuonly -c pytorch
but when i write this line
import torch
It throws an error by saying that module not installed.
How I can verify if pytorch has been installed correctly.
Try this one
conda install -c pytorch pytorch
After executing this command, you need to enter yes(if prompted in the command line) for installing all the related packages. If there is no conflict while installing the libraries, the PyTorch library will be installed.
To check if it is properly installed or not, type the command python in your command line and type import torch to check if it is properly installed or not.
Recently, I upgraded to Anaconda3 2020.07 which uses python 3.8. In past versions of anaconda, tensorflow was installed successfully. Tensorflow failed to be installed successfully in this version.
I ran the command below;
conda install tensorflow-gpu
The error message that I received is shown below;
UnsatisfiableError: The following specifications were found
to be incompatible with the existing python installation in your environment:
Specifications:
- tensorflow-gpu -> python[version='3.5.*|3.6.*|3.7.*|>=3.7,<3.8.0a0|>=3.6,<3.7.0a0|>=3.5,<3.6.0a0|>=2.7,<2.8.0a0']
Your python: python=3.8
If python is on the left-most side of the chain, that's the version you've asked for.
When python appears to the right, that indicates that the thing on the left is somehow
not available for the python version you are constrained to. Note that conda will not
change your python version to a different minor version unless you explicitly specify
that.
The following specifications were found to be incompatible with your CUDA driver:
- feature:/win-64::__cuda==11.0=0
Your installed CUDA driver is: 11.0
Is there a conda command with the right parameters to get tensorflow installed successfully?
UPDATE:
TF is now compatible with Python 3.8
Tensorflow is not compatible with Python 3.8. See https://www.tensorflow.org/install/pip
You need to downgrade your python version :
conda install python=3.7
Create an environment with python 3.7 and then activate it:
conda create -n p37env python=3.7
conda activate p37env
And install tensorflow.
This worked for me, and found out the answer from the Anaconda user guide (under how to use a different python version: https://conda.io/projects/conda/en/latest/user-guide/getting-started.html#managing-python )
From the requirement page:
Python 3.8 support requires TensorFlow 2.2 or later.
So there is a verison of Tensorflow compatible with python 3.8.
The problem is that TensorFlow 2.2.0 is not available through conda on Windows, this should be the reason why you get PackagesNotFoundError when running
conda install tensorflow=2.2
EDIT 15/03/21
Tensorflow 2.3.0 is compatible with Windows
i think we have two options here
pip install tensorflow
or we can use another env of anaconda such as like this below
conda create -n tf tensorflow pydotplus jupyter
conda activate tf
Actually you can directly use pip inside anaconda prompt, after I tested it, I found the conda is capable with pypi, first run the anaconda prompt with administrator permission (in windows), then enter "conda update --all" to make sure all the packages are latest, finally enter "pip install tensorflow" to install (the new version of tensorflow already includes tensorflow-gpu).
Then using VS code to open an ipynb and run
import tensorflow as tf
tf.test.gpu_device_name()
everything looks good.
For more info please refer to Anaconda official docs: https://docs.anaconda.com/anaconda/ .
Latest development for tensorflow installation on anaconda.
https://anaconda.org/anaconda/tensorflow
https://anaconda.org/anaconda/tensorflow-gpu
9 days ago, Anaconda uploaded a new tensorflow v2.3 package. Anaconda3 2020.07 (uses python v3.8) users can easily upgrade to tensorflow v2.3 with the following commands;
conda install -c anaconda tensorflow
conda install -c anaconda tensorflow-gpu
I have personally tested that the installation worked successfully.
The other answers for this question have now become obsolete.
Expanding upon William's answer here with more explicit instructions and caveats. Pip is the recommended way to install latest version of tensorflow as per tensorflow's installation instructions -- "While the TensorFlow provided pip package is recommended, a community-supported Anaconda package is available."
Here is the code that uses pip to do the installation in a Conda environment:
conda create -n env_name python=3.8
conda activate env_name
conda install pandas scikit-learn matplotlib notebook ##installing usual Data Science packages that does include numpy and scipy
pip install tensorflow
python -c "import tensorflow as tf;print(tf.__version__)" ##checks tf version
In general, we should be careful while mixing two package managers (conda and pip). So, it is suggested that:
Only after conda has been used to install as many packages as possible
should pip be used to install any remaining software. If modifications
are needed to the environment, it is best to create a new environment
rather than running conda after pip.
For an example, if we would like to install seaborn in the just created env_name environment, we should:
conda create --name cloned_env --clone env_name
conda activate cloned_env
conda install seaborn
Once we check the cloned_env environment is working fine, we can delete the env_name environment.
I was running into the same issue in conda prompt for Python 3.8.5 and fixed it using a Python wheel instead. Here are the steps:
Open conda prompt and install pip if you don't have it already: python -m pip install --upgrade pip
python -m pip install --upgrade https://storage.googleapis.com/tensorflow/windows/gpu/tensorflow_gpu-2.4.0-cp38-cp38-win_amd64.whl
Note: If you need a CPU specific tensorflow, use this wheel: https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow_cpu-2.4.0-cp38-cp38-win_amd64.whl
I just downgraded python to 3.7 as tf is not avialable to 3.8 version also I cannot use virtualenv for code that's why
The only working answer for me is:
conda install -c conda-forge tensorflow
It appears that tensorflow 2.5 on GPU has issues with spyder. So, I made new environment and installed tensorflow gpu as suggested by anaconda. Now I have to use either prompt or jupyter . At least it works
For macos users I suggest create an environment with python 3.7 and install tensorflow there.
You can run these commands too:
conda create -n new_env_name python=3.7
conda activate new_env_name
I had a similar problem in Anaconda Spyder. Here was my solution (In the Anaconda Console):
conda install pip
pip install tensorflow ==2.2.0
so I am attempting to access the tensorboard visualizations from this project. I am not to familiar with the library, but when I try to access the tensorboard during training using the command
tensorboard --dir data
I get returned with the tensor board command not found. (Running on Ubuntu 18.04). pip list displays that I have tensorboardX 1.9 downloaded, so I am not sure why the command is not being recognized. I have pytorch installed, and I am not aware of any other dependencies that are needed.
You can check what is in the PyTorch Tensorboard documentation together with the installation instructions.
If you use conda, try to install tensorboard outside conda. That helped me.
Also, such a command could work if you have problems with bash command
python -m tensorboard.main --logdir=.
So basically, I am fairly new to programming and using python. I am trying to build an ANN model for which I have to use Tensor flow, Theano and Keras library. I have Anaconda 4.4.1 with Python 3.5.2 on Windows 10 x64 and I have installed these libraries by following method.
Create a new environment with Anaconda and Python 3.5:
conda create -n tensorflow python=3.5 anaconda
Activate the environment:
activate tensorflow
After this you can install Theano, TensorFlow and Keras:
conda install theano,
conda install mingw libpython,
pip install tensorflow,
pip install keras,
Update the packages:
conda update --all
All these packages are installed correctly and I have check them with conda list.
However, when I am trying to import any of these 3 libraries (i.e. Tensor flow, Theano and Keras), it is giving me the following error:
Traceback (most recent call last):
File "<ipython-input-3-c74e2bd4ca71>", line 1, in <module>
import keras
ImportError: No module named 'keras'
Hi I have an solution try this if you are using Anaconda-Navigator
go to Anaconda Environment and search keras package and then install.
after install just type import keras in shell its working.
Have you tried using keras documentation
Install Keras from PyPI (recommended):
Note: These installation steps assume that you are on a Linux or Mac environment. If you are on Windows, you will need to remove sudo to run the commands below.
sudo pip install keras
If you are using a virtualenv, you may want to avoid using sudo:
pip install keras
from: https://keras.io/
Now you need to have Tensorflow installed and then write, for example:
import tensorflow as tf
...
model = tf.keras.models.Sequential()
model.add(tf.keras.layers.Dense(12, input_dim=8, activation='relu'))
model.add(tf.keras.layers.Dense(8, activation='relu'))
model.add(tf.keras.layers.Dense(1, activation='sigmoid'))
...
Works for Tensorflow version: 2.4.1.
Or just type:
import tensorflow as tf
from tensorflow import keras
...
Try
import sys
print(sys.path)
and see if your anaconda site-packages folder is in the list.
It should be something like WHERE_YOU_INSTALLED_ANACONDA\anaconda3\envs\ENVIRONMENT_NAME\lib\python3.5\site-packages
If the path setting is correct, then try listing the folder content, and see if Keras, TensorFlow and Theano are in this folder.
I ran into a very similar issue after switching computers and downloading the latest Anaconda, which comes with python 3.6. It was no problem to install python 3.5 in its own environment, and install keras to this environment, but import keraskept failing.
My inelegant solution (assuming you've already got tensorflow/theano/cntk working fine in your global environment)?
Move the keras folder installed to Anaconda3/envs//Lib/site-packages/keras to Anaconda3/Lib/site-packages/keras. Now import keras gives a depreciation warning when run from a jupyter notebook launched via start menu, but it does work, and correctly returns the backend keras is running on.
I spent the whole day to install Keras, tried all the available methods online, almost dying. But I still cannot import keras.
(1). After using conda install or pip install, and delete the "1 > null > 2&1" ... I activated in conda prompt by activating tensorflow_cpu, it doesn't work anyway.
(2). Then checked the keras, and print os.path(), no virtual environment inside. I got so braindead, just copied all the keras data file from virtual environment env, and put into the "C:\Users\Administrator\Anaconda3\Lib\site-packages".
(3). Now, tensorflow and keras work well.
Click Update Index and then try searching for Keras again.
I have the same problem with:
conda 4.13.0
tensorflow 2.6.0
Note: We should not have to install Keras separately, as it ships with Tensorflow, starting with Tensorflow 2.0.
Symptoms:
Keras import (from tensorflow import keras) does not return an error, BUT any further reference to Keras does throw "ModuleNotFoundError", e.g. the following statements fail:
print(keras.__version__)
from keras import Sequential
I still don't have a direct solution for this, this is more of a workaround, but here it is:
Import ANY class from Keras JUST ONCE using full top-down import syntax AND instantiate it
Import Keras (now "for real")
E.g.:
from tensorflow.keras.layers import Dense
layer = Dense(10)
from tensorflow import keras
Now the following statements should work:
print(keras.__version__)
model = keras.models.Sequential()
This looks like some sort of lazy module loading gone wrong.
A direct and simple way to fix it is as below,
#uninstall keras and tensorflow
pip uninstall keras
pip uninstall tensorflow
#Now install keras and tensorflow for required version with dependencies.
pip install keras==2.2.4
pip install tensorflow==1.13.1
Always make sure that you install right version of tensorflow which supports that keras version as well, else you may end up in trouble again. By the way , the above fix worked for me.
I solved this problem by running one of the following in the terminal according to anaconda website.
To install this package (keras) with conda run one of the following:
conda install -c conda-forge keras conda install -c
conda-forge/label/broken keras conda install -c
conda-forge/label/cf201901 keras conda install -c
conda-forge/label/cf202003 keras
If you never use conda before you can check anaconda.
A direct and simple way to fix it is as below, #uninstall keras and tensorflow
py -3 -m pip uninstall keras
py -3 -m pip uninstall tensorflow
#Now install keras and tensorflow for required version with dependencies.
py -3 -m pip install keras
py -3 -m pip install tensorflow
the above fix worked for me.
If you are sure that you ran pip install keras at the command line, ensure that you use the small letter 'k' instead of the Capital Alphabet. I had a similar error message.
These are some simple steps to install 'keras' simply using the Anaconda Navigator:
Launch Anaconda Navigator. Go to the Environments tab.
Select ‘Not installed’, and type in ‘tensorflow’.
Then, tick ‘tensorflow’ and do the same for ‘keras’.
Click on ‘Apply’. The pop-up window will appear, go ahead and apply.
This may take several minutes.
Done.
This tutorial will guide you more graphically: https://www.freecodecamp.org/news/install-tensorflow-and-keras-using-anaconda-navigator-without-command-line/
Remember to launch spyder in the environment or activate it in line command (conda activate [my_env]. afater that, execute your script python.
Try to import keras library from its reference parent which means import tensorflow.keras
I'm having trouble installing the Keras library for Python 3.6. Whenever I try to install Keras, it is throwing an error and when I searched on the internet, Keras had been released for up to Python 3.5. Does anyone have a solution for this?
Follow this method if you have Anaconda and Python version 3.6.
First, create a new conda environment,
conda create -n keras python=3.5
Now activate it,
source activate keras
and install Keras,
conda install keras
Test if it works,
$ python
>>>import keras
You will get the following message if it was successful:
Using TensorFlow backend.
Click here to see Mike Müller's answer
I used sudo pip install keras to download.
I have both python 2.7 and 3.6 installed on my Mac. I used pip -V to check my python version of installation. Probably you used invalid version of python to download.
Screenshot of the install being done on my computer:
Follow the below steps , Tensorflow dosnt support py3.7 as of now , so 3.6 is better , I recommend using environment , (venv , conda(preferred) ),
For conda
conda create -n keras python=3.6
source activate keras
conda install tensorflow keras
#for faster installation
pip install keras
For virtualenv
virtualenv -p python3 keras
source keras/bin/activate
pip install keras tensorflow numpy
Try the following at a command prompt:
pip install --upgrade tensorflow
pip install --upgrade keras
Also, refer the following link for more detail:
https://www.tensorflow.org/install/pip