guys:
I use conda install tensorflow-gputo install tensorflow 2.0 , and
numpy=1.20.2 would be one of the package installed, and then I use python3 -m pip install SOMEPACKAGE ,this SOMEPACKAGE needs numpy to be installed as well , but pip seems does not check or realize the package numpy has already installed...
I would like to show everything I know so far :
1.I know the packages installed via conda install would go to anaconda3/envs/YOUR_ENV/lib/site-packages
2.I use python3 -m pip install -t anaconda3/envs/YOUR_ENV/lib/site-packages to force the package would be installed to the place where conda install would be.
However,pip still tries to dwonload *.whl file and install package again,I do not want this package installation process happen again ,while it did mention that I can use --upgrade to replace the existed package...
So I would like to know
How does pip and conda install check if the target package has already existed before they actually to through install process?
I think using python3 you are not using interpreter from your current conda environment so it gets installed elsewhere
python -m pip install (or simply pip install) from your activated environment should work and ignore dependencies installed by conda if they satisfy the requirements
I am using a Windows 10 Machine and after re-installing Anaconda and all of the packages I had previously, including torchvision, torch and necessary dependencies, I am still getting this error:
OSError: [WinError 127] The specified procedure could not be found. Error loading "C:\Users\XXX\Anaconda3\envs\XXX\lib\site-packages\torch\lib\caffe2.dll" or one of its dependencies.
I am using python 3.7.9 and:
torchaudio=0.6.0=py37
torchvision=0.7.0=py37_cpu
tornado=6.0.4=py37he774522_1
traitlets=5.0.5=py_0
I've looked into it quite a bit but feel like this should be an easy solve...
I do not have CUDA and have used this:
conda install pytorch torchvision torchaudio cpuonly -c pytorch
as per instructed on the official website of pytorch
After a long time trying many things with Anaconda I decided to use bare python instead and I installed Python 3.8.6 and installed PyTorch from the link you provided and it finally worked even with CUDA support. Make sure to completely remove all Anaconda/Other Python version scripts from your path to ensure only the 3.8.6 version is used by your prompt.
I had the same problem, so I uninstalled the pytorch in my machine using
"conda uninstall pytorch torchvision torchaudio cudatoolkit=10.2 -c pytorch"
Then did a clean installation using the following
"pip install torch===1.7.0 torchvision===0.8.1 torchaudio===0.7.0 -f https://download.pytorch.org/whl/torch_stable.html"
I did not use conda for installation as it was persistently giving me the cpu version of pytorch.
I tried to install PyTorch with Anaconda and had the same error.
For me what solved the issue was to uninstall Pytorch using Pip (even though I installed it with conda) and then installing again with Pip as explains at PyTorch guide.
Uninstall:
pip uninstall torch
pip uninstall torchvision
pip uninstall torchaudio
Install:
pip3 install torch torchvision torchaudio
I have created a conda environnmennt
and then pip installed tensorflow using a pip wheel. numpy was installed by pip at same stage.
When trying to install scipy,
conda wants to install numpy in parallel of pip installed numpy....?
How to make various installed be recognized by conda ?
This is what the new configuration option pip_interop_enabled, introduced in Conda v4.6 is for. It is still considered a "preview" feature, but I've had success using it:
conda config --set pip_interop_enabled true
Until this feature is released in earnest, I think it would be wise to limit its use to a per-env-basis by using the --env flag when running the above.
It should be kept in mind that preferring Conda packages is still best practice. A must read in this regard is "Using Pip in a Conda Environment".
Which one should I use to install keras if I have anaconda?
conda install -c conda-forge keras
&
pip install --upgrade keras
Also, what is conda-forge? Why need to do it this way?
The advantages of using conda rather than pip to install packages in your Anaconda environment(s) are that:
conda should determine what dependencies your requested package has, and install those too in one operation, and
you can then keep the installed packages up to date using the conda update command:
pip, PyPI, and setuptools?
None of this is going to help with updating packages that have been
installed from PyPI via pip, or any packages installed using python
setup.py install. conda list will give you some hints about the
pip-based Python packages you have in an environment, but it won’t do
anything special to update them.
The conda-forge channel is where you can find packages that have been built for conda but are not part of the official Anaconda distribution (yet).
See answers to this question for more detail on the two options (although bear in mind some of the answers may be out of date).
when I try to install TensorFlow by cloning from Git, I run into the error "no module named copyreg," so I tried installing using a virtualenv. However, I then run into this error:
pip install https://storage.googleapis.com/tensorflow/mac/tensorflow-0.5.0-py2-none-any.whl
tensorflow-0.5.0-py2-none-any.whl is not a supported wheel on this platform.
I don't see this under the common problems section.
I am using OS X v10.10.5 (Yosemite) and Python 3.4.3, but I also have Python 2.7 (I am unsure if pip differentiates between these or how to switch between them).
I too got the same problem.
I downloaded get-pip.py from https://bootstrap.pypa.io/get-pip.py and then ran python2.7 get-pip.py for installing pip2.7.
And then ran the pip install command with python2.7 as follows.
For Ubuntu/Linux:
python2.7 -m pip install https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.5.0-cp27-none-linux_x86_64.whl
For Mac OS X:
python2.7 -m pip install https://storage.googleapis.com/tensorflow/mac/tensorflow-0.5.0-py2-none-any.whl
This should work just fine as it did for me :)
I followed these instructions from here.
After activating the virtualenv, be sure to upgrade pip to the latest version.
(your_virtual_env)$ pip install --upgrade pip
And now you'll be able to install TensorFlow correctly (for Linux):
(your_virtual_env)$ pip install --upgrade https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.7.0-py2-none-linux_x86_64.whl
I was trying to do the Windows-based install and kept getting this error.
It turns out you have to have Python 3.5.2. Not 2.7, not 3.6.x-- nothing other than 3.5.2.
After installing Python 3.5.2, the pip install worked.
Make sure that the wheel is, well, supported by your platform. Pip uses the wheel's filename to determine compatibility. The format is:
tensorflow-{version}-{python version}-none-{your platform}.whl
I didn't realize that x86_64 refers to x64, I thought it meant either x86 or x64, so I banged my head against this futilely for some time. TensorFlow is not available for 32-bit systems, unless you want to compile it yourself.
It seems that TensorFlow only works on Python 3.5 at the moment. Try to run this command before running the pip install
conda create --name tensorflow python=3.5
After this, run the following lines:
For CPU:
pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow-1.1.0-cp35-cp35m-win_amd64.whl
For GPU:
pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/windows/gpu/tensorflow_gpu-1.1.0-cp35-cp35m-win_amd64.whl
It should work like a charm.
On Windows 10, with Python 3.6.X version I was facing the same. Then after checking deliberately, I noticed I had Python-32 bit installation on my 64-bit machine. Remember TensorFlow is only compatible with a 64-bit installation of Python. Not 32 bit of Python
If we download Python from python.org, the default installation would be 32 bit. So we have to download the 64 bit installer manually to install Python 64 bit. And then add
C:\Users<username>\AppData\Local\Programs\Python\Python36
C:\Users<username>\AppData\Local\Programs\Python\Python36\Scripts
Then run gpupdate /Force on the command prompt. If the Python command doesn’t work for 64 bit, restart your machine.
Then run the Python interpreter on the command prompt. It should show 64 bit
python
Python 3.6.3 (v3.6.3:2c5fed8, Oct 3 2017, 18:11:49) [MSC v.1900 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license" for more information.
Then run the below command to install the TensorFlow CPU version (recommended)
pip3 install --upgrade tensorflow
The pip wheel file contains the Python version in its name (cp34-cp34m). If you download the .whl file and rename it to say py3-none or instead, it should work. Can you try that?
The installation won't work for Anaconda users that choose Python 3 support, because the installation procedure is asking to create a Python 3.5 environment and the file is currently called cp34-cp34m. So renaming it would do the job for now.
sudo pip3 install --upgrade https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.7.0-cp34-cp34m-linux_x86_64.whl
This will produce the exact error message you got above. However, when you will download the file yourself and rename it to "tensorflow-0.7.0-py3-none-linux_x86_64.whl", then execute the command again with the changed filename, it should work fine.
For Windows 10 64 bit:
I have tried all the suggestions here, but finally I got it running as follows:
Uninstall all current versions of Python
Remove all Python references in the PATH system and user environment variables
Download the latest 64-bit version of Python 3.8: Python 3.8.7 currently, not the latest 3.9.x version which is the one I was using, and not 32 bit.
Install with all options selected, including pip, and including the PATH environment variable
pip install tensorflow (in an administrator CMD prompt)
Upgrade pip if prompted (optional)
Actually, you can use Python 3.5.*.
I successfully solved this problem with Python 3.5.3. Modify the Python version to 3.5.* in Conda. See Managing Python.
Then go to https://www.tensorflow.org/install/install_windows, and repeat from "Create a Conda environment named tensorflow by invoking the following command" bla, bla...
Maybe you are installing the wrong pre-build binary?
Check on https://github.com/lakshayg/tensorflow-build
For my Coffee Lake processor on Ubuntu 18.04 (Bionic Beaver) the download URL was:
https://github.com/lakshayg/tensorflow-build/releases/download/tf1.12.0-ubuntu18.04-py2-py3/tensorflow-1.12.0-cp36-cp36m-linux_x86_64.whl
pip install --ignore-installed --upgrade <PATH>
resolved the issue for me.
I was trying to install from source and got that error. (Why would a wheel built on this machine not be compatible with it?)
For me, the tag --ignore-installed made all the difference.
pip install --ignore-installed /tmp/tensorflow_pkg/tensorflow-1.8.0-cp36-cp36m-linux_x86_64.whl
worked, while
pip install /tmp/tensorflow_pkg/tensorflow-1.8.0-cp36-cp36m-linux_x86_64.whl
threw the abovementioned error.
Context: Conda environment; it might have been a problem specific to this
I was trying to install CPU TensorFlow on Ubuntu 18.04 (Bionic Beaver), and the best way (for me...) I found for it was using it on top of Conda, for that:
To create a Conda ‘tensorflow’ environment. Follow How to Install Anaconda on Ubuntu 18.04
After all is installed, see Getting started with conda. And use it according to Managing environments
conda create --name tensorflow
source activate tensorflow
pip install --upgrade pip
pip uninstall tensorflow
For CPU: pip install tensorflow-cpu, for GPU: pip install tensorflow
pip install --ignore-installed --upgrade tensorflow
Test TF E.g. on 'Where' with:
python
import tensorflow as tf
>>> tf.where([[True, False], [False, True]])
Expected result:
<tf.Tensor: shape=(2, 2), dtype=int64, numpy=
array([[0, 0],
[1, 1]])>
After the Conda upgrade, I got:
DeprecationWarning: 'source deactivate' is deprecated. Use 'conda deactivate'.
So you should use:
‘conda activate tensorflow’ / ‘conda deactivate’
I faced the same issue and tried all the solutions that folks suggested here and other links (like Platform not supported for TensorFlow on Ubuntu 14.04.2).
It was so frustrating because using print(wheel.pep425tags.get_supported()) I could see that my Ubuntu supported ('cp37', 'cp37m', 'linux_x86_64') and that was exactly what I was trying to install (from https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.14.0-cp37-cp37m-linux_x86_64.whl).
What at the end fixed it was to simply download the package first and then
pip install tensorflow-1.14.0-cp37-cp37m-linux_x86_64.whl
It means that the version of your default Python interpreter (python -V) and the version of your default pip (pip -V) do not match. You have built TensorFlow with your default Python interpreter and trying to use a different pip version to install it.
In Mac, delete /usr/local/bin/pip and rename (copy) pipx.y (whatever x.y version that matches your Python version) to pip in that folder.
This worked for me.
system requirement Python 3.7–3.10
macOS 10.12.6 (Sierra) or later (no GPU support)
pip install tensorflow-macos