there is a post How can I run Mozilla TTS/Coqui TTS training with CUDA on a Windows system? answered, by GuyPaddock, but I have RTX a5000 graphic card, running Windows 10. I'm not a programmer, but I think it needs CUDA version 11.x for this card. Will there be someone good who would write step by step what I should install to be able to run it and train models? (kidna RETARD guide) It's best not to mess with the webUI from AUTOMATIC1111, which requires python 3.10.6. Thanks in advance.
Trying to install it from the link above and also from youtube. I am trying to install this on python 3.10.8 because stable diffusion needs python 3.10.6, And version 3.10.8 is from October like CUDA 11.8. If possible, I'd like a step by step explanation of what I need to do to make it work?
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I am trying to run Nvidia rapids on a windows computer but haven't had any luck. I have installed docker desktop for windows and downloaded the rapids image. Cuda 10.0 is installed, and Nvidia-container-toolkit isn't. I haven't been able to make it run. Any thoughts or guidance?
I'm not sure if anyone has given a more definite 'updated' answer to the original question. At this point (August 2020) the answer is "Yes!". You definitely can run RAPIDS in WSL2 on Windows 10 subject to a few conditions:
Requirements
You must use RAPIDS in the Windows Subsystem for Linux version 2 (WSL2);
Windows 10 Version
2004 (OS Build 202001.1000 or later)
You have to sign up to get Windows Insider Preview versions, specifically the Developer Channel. This is required for the WSL2 VM to have GPU access. https://insider.windows.com/en-us/
CUDA version 455.41 in CUDA SDK v11.1
You must be using a special version of the NVIDA CUDA drivers (I'm using )
that you must get by a special download from NVIDIA's site. You must
join the NVIDIA Developer Program to get access to the version
-- then search for 'WSL2 CUDA Driver' and it should lead you to it.
Setup
Install the developer preview version of windows. Make sure to click the check box in 'update' that installs other recommended updates too.
Install the windows CUDA driver from the NVIDIA Developer Program
Enable WSL 2 by enabling the "Virtual Machine Platform" optional feature. You can find more steps here https://learn.microsoft.com/en-us/windows/wsl/install-win10
Install WSL from the Windows Store (Ubuntu-20.04 confirmed working)
Install python on the WSL VM, tested with Anaconda
Install Rapids AI (It's best to install this right now before you have hundreds of other packages for 'conda' to try to self-consistently reconcile with the rapids dependency graphs -- you can always install additional python packages via pip or conda later.)
After doing this, if you launch ipython...
Python 3.8.3 (default, May 19 2020, 18:47:26)
Type 'copyright', 'credits' or 'license' for more information
IPython 7.17.0 -- An enhanced Interactive Python. Type '?' for help.
>>> import cuml
>>> cuml.__version__
'0.15.0'
>>> import cudf
>>> cudf.__version__
'0.15.0'
>>> import dask_cudf
>>> dask_cudf.__version__
'0.15.0'
>>> import cupy
>>> cupy.__version__
'7.8.0'
...and you're good to go with RAPIDS AI.
Update 9/6/20: The answer written by Wesley is accurate with the latest Windows Insider Preview with WSL2. Rather than revising this answer, I've just made the edits to his. https://stackoverflow.com/a/59364773/6779504
No. As it exists now, RAPIDS requires a Linux host. This came up in a recent workshop by NVIDIA. It was also mentioned that RAPIDS won't work with WSL. It may work with WSL version 2, but I haven't tried it nor am aware of someone that as.
The only option would if you could assign a GPU to a Linux VM on the Windows host. This possible but sufficiently complex that dual-booting is a better solution.
I have a problem since few days.
I installed NVIDIA drivers and cuDNN using some step by steph tutoriaI from the Internet.
The installation succeded since tests on CUDA samples passed.
I then installed python 3.7, jupyter and Tensorflow-gpu.
However, Tensorflow don't see my 2 GPUs and see only XLA_GPUs.
I tried recommandations from other posts (such us uninstalling and installing tensorflow) but this did not solve my problem.
Anyone have an idea how to solve this problem ?
It is now Oct 29, 2018
After much googling, I have not found a definitive answer or any examples of people using the latest cuda10 for tensorflow on ubuntu 14.04.
My dilemma is whether to upgrade my OS (currently at 14.04) in order to run cuda9 so I can use the latest tensorflow version or use CUDA10 on my existing 14.04 install.
Note cuda9 does not support 14.04, however, Nvidia has indicated that 14.04 will be supported for cuda10.
So, any examples/experiences of people using tensorflow with cuda10 on ubuntu14.04 are keenly sought after!
Also note cuda10 is not specifically supported by tensorflow...yet...they say "soon". But TF can be built from source with cuda10.
This is a link for cuda10+tensorflow on ubuntu16.04:
https://github.com/tensorflow/tensorflow/issues/22706
The short answer, I realize, is "try building it myself". Before I do that, I thought I'd ask around. Thanks.
I don't know whether CUDA 10 can work well on Ubuntu 14.04, but I was managed to build TensorFlow with CUDA 10 on Ubuntu 18.04 with using NVIDIA released docker image.
You can pull the 'TensorFlow Release 18.09' and try it on your current system.
If the previous step does not work, consider upgrading your OS to 18.04.
I wrote down my installation experience on this page, you could read it for some detail if you need.
I'm running a Windows computer with just a CPU (no GPU). When I run pip install tensorflow -vvv in order to see what pip is doing, it lists a lot of links, but for all of them, it says "Skipping link ... it is not compatible with this Python."
Does tensorflow support Python 3.6.4 on Windows? If so, what binary URL should I use to install it?
(I previously installed with this version due to reading this, but ran into this error without the DLL load failed message, so I'm wondering if there's a better version I should use.)
Also, I'm aware that Tensorflow says they support Python 3.x, but right now it hasn't been working for me.
You have probably installed Python 32bits, you need the 64bits version
The question is,I cannot make my computer work for my tensorflow-gpu on ubuntu system. Because NVIDIA driver cannot be installed on ubuntu.So I run tensorflow-gpu on Windows10,but it doesnot support tensorflow-serving.
I know Docker can help me to do it,and i really installed it,but just tensorflow-cpu.That would be very slowly if I just run tensorflow-cpu version.
In case that,I came up with a thought that I install two tensorflow,one is GPU version and on system,the other is CPU version on Docker.GPU version for training and save a model,then CPU version loading the saved model.
What I want to know is does this way work,and is it time saving?Or put it simply,does it take less time than just run tensorflow-cpu version on Docker?
TensorFlow GPU with NVIDIA GPUs on Ubuntu is supported, and there are drivers available. Check this tutorial.