my windows10 has subsystem for linux of 14.04. I tried to install pytorch on the preinstalled python2 but couldn't work.The error is: torch-0.2.0.post1-cp27-cp27m-manylinux1_x86_64.whl is not a supported wheel on this platform. I tried to install python3.6 then install pytorch with it, but still couldn't work.The error is missing module 'apt_pkg'. Anyone has idea on this?
According to this it should be working now via anaconda's package manager conda.
If you look in the whl filename, there are two bits to pay attention to. Firstly, the cp27 and secondly the x86_64 bit.
That first one tells you that you need python 2.7 which is the default for the WSL, so that's fine.
The second one tells you that the whl has been compiled for a 32 bit computer. If you have a 64 bit computer, it will fail.
Related
I’m currently trying to work with open3d ML and Pytorch. I followed the installation guide given in the Open3D-ML github. However when I try to import open3d.ml.torch it sends me the following error : Exception: Open3D was not built with PyTorch support!
I’m working with
python 3.8
open3d 0.12.0
pytorch 1.6.0
cuda 10.1
Windows 10
Do you have any idea of where that error comes from ?
It does not support for Windows at the moment. You can install Ubuntu on WSL (Window Subsystem for Linux) on Windows OS, and install open3d-ml on ubuntu.
Can you check if the output of the following commands on Windows Terminal (or PowerShell) is:
wsl cat /proc/version
Linux version 5.10.16.3-microsoft-standard-WSL2
wsl --list
Ubuntu-20.04 (Standard)
wsl -l -v
Ubuntu-20.04 Running 2
In my experience, Open3D-ML with CUDA only works if you are a Windows Insider, updated the WSL kernel correctly, and you are using Ubuntu in WSL.
Also, check if the folder /usr/lib/wsl/lib exists. If not, then CUDA won't work in WSL.
Background
I've just got a new M1 mac mini dev machine, and migrated from my old x86 mac using apple's migration assistant.
Doing that also copied over all my conda environments to the new machine (they were all in my home directory)
I installed the latest version of anaconda and anaconda plus all my python code and environments seem to work fine (this includes a bunch of wheel modules, notably numpy/scipy).
I did a bunch of googling for my questions below, but couldn't find any good answers anywhere - so I thought I'd ask SO as this seems like a quite common situation others will run into
Questions
Does anyone know the status of M1 native versions of python/numpy/scipy etc provided by conda forge?
I presume that all the binaries in my environments for python/numpy etc all still the old x86 versions, as they were all in environments in my home directory, and running via emulation. So, how do you go about changing/updating those to a M1 arm native
version if/when available?
A quick update as of July 2021.
TLDR
The conda-forge group have a M1 native conda installer here.
Installation is simple - run the installer, and you have conda up and running.
This will install an M1 native conda, and that conda's default environment will by default install M1 native python versions and M1 native versions of modules (if available).
There seem to be native osx M1 native wheels for most common modules now available on the conda-forge channel.
Current status
It seems Anaconda still do not have a native M1 version, nor does Miniconda. ...I can't figure out why it's taken so long and neither still seem to have native M1 support, but that's a separate issue.
Alternative
However, as steff above mentioned, conda-forge (as in the group responsible for maintaining the conda-forge channel) do have a installer for their version of conda that is itself both native M1, and also sets up your environment to pull M1 native wheels where available. This they call Miniforge.
Their github is here.
Various installers for their Miniforge (via direct download, curl or homebrew) can be found on their github page (above) - the direct link to the ARM native miniforge installer is here.
A quick search on conda-forge show's almost all common modules do now have native M1 wheels available. (look for supporting platform 'osx-arm64` eg numpy)
Caveats
I've not tested this too extensively yet, and I'm not sure exactly what happens if a non-M1 wheel is available (I believe it will default to downloading a no-arch version).
I'm also not sure/haven't tested whether you can mix and match M1 wheels with x86 mac wheels. (I'm guessing this would work, but haven't tried).
I also have only done minimal testing using the conda's pip, and how well it recognizes/tries to download/resolves M1 vs x86 pip packages.
The answer here is going to evolve over time, so here is the most up-to-date knowledge I have as of 27 Jan 2021.
Installing conda in emulation mode works completely fine. All you need to do is to install it in a Terminal run in emulation mode, or else install it using a Terminal emulator that has not been ported over yet.
Once your conda environments are up and running, everything else looks and feels like it did on x86 Macs.
If you'd like a bit more detail, I blogged about my experience. Hopefully it helps you here.
I got my M1 about 2 weeks ago and managed to install absolutely everything I need natively from conda-forge and pip. The installer you can download here.
As of 5Feb Homebrew is also officially supported on osx-arm64.
2022/03/02 answers
Native M1 installations are pretty simple now. Here are a few options for Miniforge and Miniconda.
(1) Using Apple's instructions for Tensorflow with Miniforge
This uses the same Miniforge solution mentioned above but includes an M1-optimized Tensorflow install, meaning TF has access to the M1 GPU cores.
Look for the "arm64: Apple Silicon" section at:
https://developer.apple.com/metal/tensorflow-plugin/
(2) Running native M1 with Miniforge and Rosetta with Miniconda side-by-side (Jeff Heaton's tutorial from 2021/11)
Jeff basically uses Apple's solution above for the native Miniforge install.
https://www.youtube.com/watch?v=w2qlou7n7MA
(3) Using native M1 Miniconda
There was a native M1 Miniconda installer published in 2021/11: Miniconda3 macOS Apple M1 64-bit bash (Py38 conda 4.10.1 2021-11-08)
https://docs.conda.io/en/latest/miniconda.html
My Experiences
I successfully ran the side-by-side installation from Jeff's tutorial with a few changes. It was very easy and I verified that in the native M1 Miniforge environment that Numpy is using the optimized BLAS/LAPACK linear algebra libraries and that Tensorflow has GPU access. I will update here after I run the Miniconda native M1 installer.
I installed the native version of python3 through miniforge (Apple version) and Spyder (Intel version) through homebrew and everything is working just fine for me with one exception, I've observed one strange behaviour when setting the "graphics backend" option to "automatic" instead of "inline".
Spyder >>> Prefernces >>> IPython Console >>> Graphics >>> Graphics Backend >>> inline, or automatic
When I start Spyder with the "inline" option and switch to "automatic", the opened kernels function just as expected. However, if I open new consoles they don't work at all. The issue also persists after restarting Spyder. The only way I manage to plot graphics in a separate window is to start Spyder with IPython console "graphics backend" set to "inline" and then change it to "automatic".
If I run python3 through terminal, plotting graphics works just fine as well.
My installation commands were:
brew install --cask miniforge
conda init zsh
conda activate
brew install --cask spyder
brew install PyQt#5
pip3 install matplotlib
You can check out this anouncement by Anaconda. You can now use Anaconda on your M1 MAC direclty.
"The 2022.05 release of Anaconda Distribution features native compiling for Apple M1’s ARM64 architecture (boasting 20% faster compute), Anaconda Navigator 2.1.4, conda 4.12.0, as well as several new and updated packages. 2022.05 is also the last release that will support win32."
I am trying to install pycocotools on Windows 10. I used this command:
pip install git+https://github.com/philferriere/cocoapi.git#egg=pycocotools^&subdirectory=PythonAPI
You can see the error output in the following picture:
Any ideas on how to fix that?
Windows building of some COCO tools gave me a bit of a headache too, I finnaly translated decode mask function for the Windows version of my code.
https://github.com/armengot/COCO_decode_mask/tree/main/python
In Linux any problems.
I need to run a program which use VTK5 on my Archlinux PC, but I found it really hard to install VTK5, there is only VTK6(not compatible with VTK5) in official repo, and when I try to install it from AUR, it returns "Makepg was unable to build vtk5", then I try to install through source code, the result is that I was unable to install the VTK Python module...
Is there anybody who has any experience or idea about it?
I have not installed on Archlinux specifically, but on different linux machines. If you compile from source and are interested in python, remember to select the option python wrapping when running cmake. Btw, once built, you will have to update both the pythonpath and the ldlibrarypath.
You can also have a try at enthought canopy, which distributes a complete installation with numpy, scipy, vtk http://docs.enthought.com/canopy/quick-start/install_linux.html
I can see installation files for windows 64bit and 32bit, but the tar.gz file for linux doesn't say whether it is 64 or 32bit.
The tar.gz is likely a source package, you have to compile it yourself.
And yes, matplotlib works fine as 64-bit.
The only Linux I'm familiar with is Ubuntu. There, apt-get is your friend. You do not need to compile. However, there are a few steps involved, depending on what you already have on your machine.