Jupyter Notebook kernel dies when importing tensorflow 1.5.0
I have read a lot of posts relating to this but they have all had higher version numbers of tensorflow and have solved it by downgrading to 1.5.0. I also had higher version number and followed the advice to downgrade but I still have the problem.
Does anyone know what to try next?
pip install h5py==2.8.0
worked for me
When trying using the command prompt I got an error message not related to the tensorflow issue (I think);
"Warning! HDF5 library version mismatched error"
The key information from that message body was "Headers are 1.10.1, library is 1.10.2" so I downgraded hdf5 library by "conda install -c anaconda hdf5=1.10.1" and now the error message is gone and the kernel does not die when importing tensorflow.
I got similar problems, any tensorflow or tensorflow related packages (e.g. keras) made my kernel to die when loading, from any interface (jupyter, spyder, console....)
For those having this kind of problems, try running python from the console with verbose mode (python -v) then import tensorflow and look for errors.
I spot errors related to h5py, similar to the reply of #DBSE. I just upgraded the h5py package then everything was solved !
If you are using a conda environment, then the easiest method for fixing this issue is to just create a new environment and install tensorflow with just a single command. I had the same issue, I have tried a lot on most of the version of python and tensorflow. But at the last I have successfully configured it with just a single steps.
Run this command for installing GPU version
conda create --name tf_gpu tensorflow-gpu
The above line of code will automatically install that version of python and tf which is comaptible with your GPU or CPU.
For CPU, Run this command
conda create --name tf_env tensorflow
Both of these command work 100 % with my system for GPU and CPU access and will download the latest version which are compatible with system. It will resolved/fixed "Illegal Instruction (code dumps)" error.
pip install h5py==3.1.0
This is the most updated version which worked for me.
Try using import numpy before Keras and Tensorflow.
Related
i followed the instructions given by the official tf documentation, but i just cannot resolve the various problems encountered.
Did anyone have the experience installing tff on m1 mac and can show me your overall process?
conda create -n federated python=3.8
conda activate federated
pip install --upgrade tensorflow_federated
everything seems to be fine according to the terminal output, however,
after
import tensorflow_federated as tff
i got a RunTimeError:
RuntimeError: This version of jaxlib was built using AVX instructions, which your CPU and/or operating system do not support. You may be able work around this issue by building jaxlib from source.
how to resolve this?
When I start "Running Train a GPT-2 (or GPT Neo) Text-Generating Model w/ GPU on Colab" in my Colab, following error comes up:
ERROR: tensorflow 2.5.0 has requirement tensorboard~=2.5, but you'll
have tensorboard 2.4.1 which is incompatible. ERROR: pytorch-lightning
1.3.8 has requirement PyYAML<=5.4.1,>=5.1, but you'll have pyyaml 3.13 which is incompatible.
What to do? Is it because of my Mac, or do I need to upgrade my Colab account would that help?
The problem comes from the default packages installed in the Colab environment. I does not depend on the platform you are using to access Colab or on the type of your subscription.
You have to upgrade the Python packages using pip.
In general you can run shell commands like pip in Colab prepending a ! character,
so in your case the following lines should be sufficient to fix the problem
!pip install tensorboard==2.5
!pip install pyyaml==5.4.1
If you need to run more shell commands, you can use more user-friedly methods (see the answers to this question).
I installed Tensorflow with GPU support and Keras to an environment in Anaconda (v1.6.5) by using following commands:
conda install -n EnvName tensorflow-gpu
conda install -n EnvName -c conda-forge keras-gpu
I have NVIDIA Quadro 2200K on my machine with driver v384.66, cuda-8.0, cudnn 7.0
When I am trying to run a python code with Keras at the stage of training I get the following
Intel MKL ERROR: Parameter 4 was incorrect on entry to DLASCL.
and later
File
"/home/User/anaconda3/envs/keras_gpu/lib/python3.6/site-packages/numpy/linalg/linalg.py",
line 99, in _raise_linalgerror_svd_nonconvergence
raise LinAlgError("SVD did not converge") numpy.linalg.linalg.LinAlgError: SVD did not converge
Other relevant sources suggest to check data for NaNs and Infs, but my data is clean for sure. By the way, CPU version of the installation is working fine, the issue occurs only when trying to run on GPU
I tried to reinstall Anaconda, to reinstall CUDA and numpy, but it didn't work out.
The problem was in package mkl (2018.0.0) - it seems like it has recently been released and conflicts with the version of some packages supplied with Tensorflow(1.3.0) and Keras(2.0.5) via conda*.
So I manually downgraded mkl using Anaconda Navigator to v11.3.3 which led automatically to downgrade of other packages and everything is working well now.
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
Trying to install Tensorflow in windows7 with CPU support only.
The installation was successful using a native pip, as instructed in tensorflow site. But i am not able to validate the installation. It is generating an error message instead of printing Hello, Tensorflow.
error showing- tf is not defined,.
sees is not defined.
the screenshot of the error: [1]: https://i.stack.imgur.com/hFLvr.png
Working
py -m 3.6 pip install tensorflow
The lack of AVX instruction in CPU can cause this error.
Try this wheel for python3.6