I tried my best to install Pytorch but each and every time I failed to install it.
Conda version: 4.6.14
I have used Preview(Nightly) and LTS versions to install but for both of times I have faced the same error like Solving environment: | Killed .
Preview(Nightly) command: conda install pytorch torchvision torchaudio cudatoolkit=10.2 -c pytorch-nightly
LTS command: conda install pytorch torchvision torchaudio cudatoolkit=10.2 -c pytorch-lts
Faced error is given in the attached file, please check it.
have you tried installing pytorch into a new environment? problems usually arise when you try to install it into your base environment.
conda create -n (NameOfEnviroment) -c pytorch pytorch torchvision
conda update --all
I've been trying to install the Pytorch module for my Ubuntu 16.04 LTS through conda. I used conda install pytorch torchvision cpuonly -c pytorch to install it (non CUDA version). However when I type import torch on the Python shell, this is what I see -
ImportError: /home/student/anaconda2/lib/python2.7/site-packages/torch/_C.so: object file has no loadable segments
I have verified that Pytorch was installed using conda list
I had the same issue on Ubuntu 18.04 for conda env with python 3.8. The problem I think is for the incomplete torch installation. So I did pip install from wheel instead of conda install. You may follow as below (assuming you have cuda11 installed):
create conda env
conda create --name=myenv python=3.8
conda activate myenv
Install torch from wheel
pip install torch==1.7.0+cu110 torchvision==0.8.1+cu110 torchaudio===0.7.0 -f https://download.pytorch.org/whl/torch_stable.html
Please note I had to install torchvision==0.8.1+cu110 as reported here
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
I am very first time using pyTorch. I am trying to install it. In how many ways I can do this?
Please provide the steps for that.
You can install PyTorch in 3 ways.
Using pip
Using conda
From source
1.Intel Optimized Pytorch Installation
Install the stable version (v 1.0) on Linux via Pip for Python 3.6.
pip install https://download.pytorch.org/whl/cpu/torch-1.0.1.post2-cp36-cp36m-linux_x86_64.whl
pip install torchvision
2.Conda Pytorch Installation
conda install pytorch-cpu torchvision-cpu -c pytorch
3.PyTorch Installation from source
Create a new environment:
conda create -n <env_name> python=3.6
export CMAKE_PREFIX_PATH=/home/user/.conda/envs/<env_name>
source activate <env_name>
Install dependencies:
conda install numpy pyyaml mkl mkl-include setuptools cmake cffi typing
conda install -c conda-forge opencv
conda install Pillow
Get the PyTorch source:
git clone --recursive https://github.com/intel/pytorch
cd pytorch
mv caffe2/contrib/cuda-convnet2/ /tmp
# Fix the bug removing the old package out
Install PyTorch:
python setup.py install 2>&1 | tee build.out
Hope this will help you.
I tried to install pybox2d through anaconda navigator with Python 3.7 , but it shows this error, I could not solve
I read all the library documentation!
Error:
(user) user#euser:~$ conda install -c https://conda.anaconda.org/kne pybox2d
Solving environment: failed
UnsatisfiableError: The following specifications were found to be in conflict:
- jeepney
- notebook==5.7.4
- pybox2d
Use "conda info " to see the dependencies for each package.
I had the same problem. My tensorflow and pybox2d where conflicting.
I followed these steps by anuj:
conda create -n stackoverflow_env python=3.7
source activate stackoverflow_env
conda install -c kne pybox2d
and then installed tensorflow from anaconda navigator in this environment.
I created a new conda environment to avoid being influenced by the existing installations and followed the steps given below. After this, Box2D is importing fine for me.
conda create -n stackoverflow_env python=3.7
source activate stackoverflow_env
conda install -c kne pybox2d