I used pip to install keras and tensorflow, yet when I import subpackages from keras, my shell fails a check for PyBfloat16_Type.tp_base.
I tried uninstalling and reinstalling tensorflow, but I don't know for certain what is causing this error.
from keras.models import Sequential
from keras.layers import Dense
3.7.0 (v3.7.0:1bf9cc5093, Jun 27 2018, 04:59:51) [MSC v.1914 64 bit (AMD64)]
Python Type "help", "copyright", "credits" or "license" for more information.
>>>[evaluate machineLearning.py]
Using TensorFlow backend. 2019-04-21 00:31:22.995541: F tensorflow/python/lib/core/bfloat16.cc:675] Check failed: PyBfloat16_Type.tp_base != nullptr
aborted (disconnected)
>>>
Can someone help me solve this issue?
You may try to downgrade python to 3.6 (I know some people have troubles with tensorflow and keras using python 3.7). One simple way is to download anaconda, create a new environment with python 3.6, then install tensorflow and keras.
conda create -n myenv python=3.6
conda activate myenv
pip3 install tensorflow
pip3 install keras
You have a few options to try:
First, try to uninstall and re-install the TensorFlow and see whether the problem is resolved or not (replace tensorflow with tensorflow-gpu in the following commands if you have installed the GPU version):
pip uninstall tensorflow
pip install --no-cache-dir tensorflow
If the problem is not resolved, try to do the same thing with numpy:
pip uninstall numpy
pip install --no-cache-dir numpy
Hopefully, one of these two would resolve the problem.
Related
I recently bought a MacBook Air with the Apple M1 chip, and I'm trying to install keras for Python 3.9.10 (installed using homebrew). Using the command
pip3 install keras
in the terminal, I get the following output:
Collecting keras
Using cached keras-2.8.0-py2.py3-none-any.whl (1.4 MB)
Installing collected packages: keras
Successfully installed keras-2.8.0
Next, I entered the following series of commands (find output included as well):
~ % python3
Python 3.9.10 (main, Jan 15 2022, 11:40:53)
[Clang 13.0.0 (clang-1300.0.29.3)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import keras
After running the last line (import keras), I got the following output in the terminal:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/opt/homebrew/lib/python3.9/site-packages/keras/__init__.py", line 21, in <module>
from tensorflow.python import tf2
ModuleNotFoundError: No module named 'tensorflow'
My understanding was that keras is built on top of TensorFlow, however this seems to indicate that I need TensorFlow installed on my computer as well. Is this correct? Or is there something else I'm missing?
I've heard that TensorFlow can be very difficult to install on Apple M1 computers, so I've been trying to avoid doing so, but if I do need to, how should I go about it?
Thank you ahead of time.
UPDATE:
I decided to try and install TensorFlow2 in the terminal using the command
pip3 install tf2
and got the following output:
ERROR: Could not find a version that satisfies the requirement tf2 (from versions: none)
ERROR: No matching distribution found for tf2
I guess this is where the difficulty starts... is there any straightforward way to install TensorFlow2 on an Apple M1 computer? I'd really prefer not to switch compilers or anything as I don't have a great deal of experience with macOS and don't want to make any irreversible mistakes.
Thank you again.
UPDATE 2:
I just tried the command
pip3 install tensorflow
and I got the following output:
ERROR: Could not find a version that satisfies the requirement tensorflow (from versions: none)
ERROR: No matching distribution found for tensorflow
Thank you to Dr. Snoopy for pointing out that the package was called tensorflow and not tf2. I've read the problem might have something to do with a missing multi-threading file or something, but still can't figure out how to fix it.
A tested method using conda:
Ensure you upgrade Mac OS X > 12.3.
Install XCode CLI tools
xcode-select --install
Install Miniforge. I prefer installing using brew
brew install miniforge
Create a conda environment and activate it
conda create --name tensyflow python=3.8
conda activate tensyflow
Install Tensorflow-MacOS
conda install -c apple tensorflow-deps
pip install tensorflow-macos # or pip3
I have zero clue why my numpy is not getting recognized right now in conda env. I have all the packages installed but when I try to use numpy it says numpy Module not found. Because of that, pandas and sklearn also failing.
(ds) user-mbp:ibos_automation user$ python
Python 3.7.3 | packaged by conda-forge | (default, Mar 27 2019, 15:43:19)
[Clang 4.0.1 (tags/RELEASE_401/final)] :: Anaconda, Inc. on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import numpy
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
ModuleNotFoundError: No module named 'numpy'
This all started happening when I tried to install pdfminer.six using
pip install pdfminer.six
I also tried to roll back my conda env using revisions by doing
conda install --revision <prior_version>
but apparently it is throwing an error that some pytorch target lib is not available.
(ds) user-mbp:ibos_automation user$ conda install --revision 9
PackagesNotFoundError: The following packages are missing from the target environment:
- pytorch::pytorch==1.3.1=py3.7_0
- pytorch::torchvision==0.2.2=py_3
- pytorch::captum==0.1.0=0
I have tried updating numpy by doing
conda update numpy
but apparently numpy is the latest version installed already
(ds) user-mbp:ibos_automation user$ conda update numpy
Collecting package metadata (repodata.json): done
Solving environment: done
# All requested packages already installed.
Can someone help how to fix this? I am apparently stuck because of this.
First remove numpy from conda
conda remove numpy
Install it using pip
pip install numpy
First checked
pip list
Please checked here numpy library having or not
if having the numpy library then..
try this if you are using anaconda:
conda uninstall numpy
conda install numpy=1.18
or this if you are using python pip:
pip uninstall numpy
pip install numpy==1.18
I have tensorflow listed as a requirement in the install_requires section of the setup.py of my project.
When I attempt to install my project into a new Anaconda environment I get the following error:
$ python setup.py install
...
Searching for tensorflow
Reading https://pypi.org/simple/tensorflow/
No local packages or working download links found for tensorflow
error: Could not find suitable distribution for Requirement.parse('tensorflow')
I can get past this by installing tensorflow "manually" via conda:
$ conda install tensorflow
Once I do this the install via setup.py works without a hitch.
Am I mistaken in assuming that something is amiss with my environment? If not then what is going on and how can I avoid this issue? (My concern is that users of my package will not be able to install from source using setup.py)
Another oddity that I assume is related or may provide a clue is that the version of TensorFlow listed in my Anaconda environment is 2.0 but if I import it when running Python it appears to instead be using version 1.15. For example:
$ conda list tensorflow
# packages in environment at /home/james/miniconda3/envs/cvdata_test:
#
# Name Version Build Channel
tensorflow 2.0.0 mkl_py37h66b46cc_0
tensorflow-base 2.0.0 mkl_py37h9204916_0
tensorflow-estimator 2.0.0 pyh2649769_0
$ python
Python 3.7.6 | packaged by conda-forge | (default, Jan 7 2020, 22:33:48)
[GCC 7.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow as tf
>>> tf.__version__
'1.15.0-rc2'
This is on a Dell laptop running Ubuntu 18.04 without a GPU, so perhaps the version shown in the interpreter is akin to tensorflow-cpu? If I run pip freeze I see tensorflow==2.0.0 and tensorflow-cpu==1.15.0rc2, which is a bit confusing...
This appears to have been caused by using Python version 3.8, which is currently an unsupported version of Python. Once I created a new Anaconda environment with Python version 3.7 this issue went away.
The only remaining issue is this error that I see when I run pip install -e . for my project which includes tensorflow:
ERROR: tensorflow-cpu 1.15.0rc2 has requirement tensorboard<1.16.0,>=1.15.0, but you'll have tensorboard 2.1.0 which is incompatible.
ERROR: tensorflow-cpu 1.15.0rc2 has requirement tensorflow-estimator==1.15.1, but you'll have tensorflow-estimator 2.1.0 which is incompatible.
So the issue of tensorflow-cpu version 1.15.0rc2 actually being installed when version 2.1.0 shows as being the installed version is still a mystery. To wit:
$ conda list tensorflow
# packages in environment at /home/james/miniconda3/envs/cvd:
#
# Name Version Build Channel
tensorflow 2.1.0 pypi_0 pypi
tensorflow-estimator 2.1.0 pypi_0 pypi
$ python -c "import tensorflow as tf; print(tf.__version__)"
1.15.0-rc2
I am currently using Python 3.5.5 on Anaconda and I am unable to import torch. It is giving me the following error in Spyder:
Python 3.5.5 |Anaconda, Inc.| (default, Mar 12 2018, 17:44:09) [MSC v.1900
64 bit (AMD64)]
Type "copyright", "credits" or "license" for more information.
IPython 6.2.1 -- An enhanced Interactive Python.
import torch
Traceback (most recent call last):
File "<ipython-input-1-eb42ca6e4af3>", line 1, in <module>
import torch
File "C:\Users\trish\Anaconda3\envs\virtual_platform\lib\site-
packages\torch\__init__.py", line 76, in <module>
from torch._C import *
ImportError: DLL load failed: The specified module could not be found.
Many suggestions on the internet say that the working directory should not be the same directory that the torch package is in, however I've manually set my working directory to C:/Users/trish/Downloads, and I am getting the same error.
Also I've already tried the following: reinstalling Anaconda and all packages from scratch, and I've ensured there is no duplicate "torch" folder in my directory.
Pls help! Thank you!
I had this similar problem in windows 10...
Solution:
Download win-64/intel-openmp-2018.0.0-8.tar.bz2 from https://anaconda.org/anaconda/intel-openmp/files
Extract it and put the dll files in Library\bin into C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v9.0\bin
Make sure your cuda directory is added to your %PATH% environment variable
I had the same problem. In my case I didn't want the GPU version of pytorch.
I uninstalled it. The version was pytorch: 0.3.1-py36_cuda80_cudnn6he774522_2 peterjc123.
The problem is that cuda and cudnn . then installed with the following command and now it works!
conda install -c peterjc123 pytorch-cpu
I also encountered the same problem when I used a conda environment with python 3.6.8 and pytorch installed by conda from channel -c pytorch.
Here is what worked for me:
1:) conda create -n envName python=3.6 anaconda
2:) conda update -n envName conda
3:) conda activate envName
4:) conda install pytorch torchvision cudatoolkit=9.0 -c pytorch
and then tested torch with the given code:
5:) python -c "import torch; print(torch.cuda.get_device_name(0))"
Note: 5th step will return your gpu name if you have a cuda compatible gpu
Summary: I just created a conda environment containing whole anaconda and then to tackle the issue of unmatched conda version I updated conda of new environment from the base environment and then installed pytorch in that environment and tested pytorch.
For CPU version, here is the link for my another answer: https://gist.github.com/peterjc123/6b804651288e76db7b5fabe5348e1f03#gistcomment-2842825
https://gist.github.com/peterjc123/6b804651288e76db7b5fabe5348e1f03#gistcomment-2842837
Had the same problem and fixed it by re-installing numpy with mkl (Intel's math kernel library)
https://www.lfd.uci.edu/~gohlke/pythonlibs/#numpy
Download the right .whl for your machine. For me it was numpy‑1.14.5+mkl‑cp36‑cp36m‑win_amd64.whl (python 3.6, windows, 64-bit)
and then install using pip.
pip install numpy‑1.14.5+mkl‑cp36‑cp36m‑win_amd64.whl
I am using a Windows 10 computer with an NVIDIA GeForce graphics card. NVIDIA showed I had CUDA 10.1, but I was getting this error when running import torch in Jupyter Lab and suspected it had something to do with CUDA support.
I fixed this problem by downloading and installing the CUDA Toolkit directly from NVIDIA. It installed all required Visual Studio components. When I returned to Jupyter Lab, import torch ran without error.
Make sure you installed the right version of pytorch for your enviroment. I had the same problem I was using pytorch on windows but I had the default package installed which was meant for cuda 8. So I reinstalled the pytorch package for cpu which was what I needed.
I had the same issue with running torch installed with pure pip and solved it by switching to conda.
Following steps:
uninstall python 3.6 from python.org (if exists)
install miniconda
install torch in conda ("conda install pytorch -c pytorch")
Issue with pip installation:
import torch
File "C:\Program Files\Python35\lib\site-packages\torch\__init__.py", line 78, in <module>
from torch._C import *
ImportError: DLL load failed: The specified module could not be found.
After switching to conda it works fine. I believe the issue was resolved by conda through installing the vs_redist 2017
vs2017_runtime 15.4.27004.2010 peterjc123
But I have tried it w/o conda and it did not help. Could not find how to check (and tweak) Python's vs_redist.
Windows10 Solution(This worked for my system):
I was having the same issue in my system. Previously I was using Python 3.5 and I created a virtual environment named pytorch_test using the virtualenv module because I didn't want to mess up my tensorflow installation(which took me a lot of time). I followed every instruction but it didn't seem to work. I installed python 3.6.7 added it to the path. Then I created the virtual environment using:
virtualenv --python=3.6 pytorch_test
Then go to the destination folder
cd D:\pytorch_test
and activate the virtual environment entering the command in cmd:
.\Scripts\activate
After you do this the command prompt will show:
(pytorch_test) D:\pytorch_test>
Update pip if you have not done it before using:
(pytorch_test) D:\pytorch_test>python -m pip install --upgrade pip
Then go for installing numpy+mkl from the site:
https://www.lfd.uci.edu/~gohlke/pythonlibs/#numpy
Choose the correct version from the list if you have python 3.6.7 go with the wheel file:
numpy‑1.15.4+mkl‑cp36‑cp36m‑win_amd64.whl (For 64 bit)
(Note if the whole thing doesnot work just go with simple numpy installation and mkl installation separately)
Then go for installing openmp using:
(pytorch_test) D:\pytorch_test>pip install intel-openmp
Now you are done with the prerequisites. To install pytorch go to the previous versions site:
https://pytorch.org/get-started/previous-versions/
Here select the suitable version from the list of Windows Binaries. For example I am having CUDA 9.0 installed in my system with python 3.6.7 so I went with the gpu version:
cu90/torch-1.0.0-cp36-cp36m-win_amd64.whl
(There are two available versions 0.4.0 and 1.0.0 for pytorch, I went with 1.0.0)
After downloading the file install it using pip(assuming the whl file is in D:).You have to do this from the virtual environment pytorch_test itself:
(pytorch_test) D:\pytorch_test>pip install D:\torch-1.0.0-cp36-cp36m-win_amd64.whl
Prerequisites like six, pillow will be installed automatically.
Then once everything is done, install the models using torchvision.
Simply type :
(pytorch_test) D:\pytorch_test>pip install torchvision
To check everything is working fine try the following script:
import torch
test = torch.rand(4, 7)
print(test)
If everything was good then it wont be an issue. Whenever there is an issue like this it is related to version mismatch of one or more dependencies. This also occurred during tensorflow installation.
Deactivate the following virtual environment using the command deactivate in the cmd:
(pytorch_test) D:\pytorch_test>deactivate
This is the output of pip list in my system:
Package Version
------------ -----------
intel-openmp 2019.0
mkl 2019.0
numpy 1.16.2
Pillow 6.0.0
pip 19.0.3
setuptools 41.0.0
six 1.12.0
torch 1.0.0
torchvision 0.2.2.post3
wheel 0.33.1
Hope this helps. This is my first answer in this community, hope you all find it helpful. I setup pytorch today in the afternoon after trying all sorts of combinations. The same import problem occurred to me while installing CNTK and tensorflow. Anyway I kept them separate in different virtual environments so that I can use them anytime.
I use sudo pip install tensorflow-1.7.0rc0-cp27-cp27mu-manylinux1_x86_64.whl in centos7,python version is 2.7.14
I get successfully installed tensorflow,but when I run import tensorflow as tf,I get a error:No module named tensorflow
what should I do? thanks!
As mentioned in the comments you best method for installing pyhton packages is to use a virtual environment. For a simple way to do this you can install Minicaonda for linux x86 using the following command:
wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh
bash ./Miniconda3-latest-Linux-x86_64.sh
Then it is worth reading the instructions on using conda, to set up a virtual environment called tensorflow. But the basic command should be:
conda create -n tensorflow python=3.6 tensorflow
provided you want to use tensorflow with python3.6. Then activate your tensorflow conda environment:
source activate tensorflow
and you should be able to import tensorflow without issue.
(tensorflow) user#machine:~$ python
Python 3.6.5 |Anaconda, Inc.| (default, Apr 29 2018, 16:14:56)
[GCC 7.2.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow as tf
>>>