Comments (180)
I don't understand why you are added support for Mac OS and not Windows. You cannot use normal CUDA GPU on most Macs. It is useless platform for deep learning training
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AGAIN! PLEASE DON'T MAKE USELESS +1 COMMENTS! USE THE GITHUB REACTIONS INSTEAD!
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You can already use TensorFlow on a Windows machine by using Docker.
Details are in this thread.
#42
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I would like to use TensorFlow on Windows without Docker, in order to use GPU compute. Using Docker in this case is not using a Windows container, but a Linux virtual machine on Hyper-V or VirtualBox, and so the GPU will not be passed through.
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The official roadmap of tensorflow :
https://github.com/tensorflow/tensorflow/blob/master/tensorflow/g3doc/resources/roadmap.md
Windows support is part of the near future roadmap that is targeted for the next few months!
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+1
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Can the team tell us please about estimates for native windows support?
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+1
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google, give us windows support , please!
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Would love to use TensorFlow on Windows (native, not in a VM).
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@mrry is actively working on this and can provide more updates on this if you have specific questions.
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Folks, could you please use GitHub reactions rather than writing "+1" in a new message? Right now it produces a lot of spam for people who subscribed to updates in this thread. Thanks!
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Hi team. I'm trying to understand what work needs to be done to be able to use TensorFlow on Windows (10, I guess) with GPU support via CUDA. From what I know so far, that rules out Docker because Docker cannot access the host's GPU, and means that we must use Visual Studio's cl.exe (which is what Bazel for Windows does use).
From that, is it just Bazel for Windows that needs to be progressed? Is that the only unsatisfied dependency here? Happy to be corrected on any point.
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+1
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@umarniz Thanks for the guide. However, I think, what most people here anticipate to see is TensorFlow running natively on Windows because of GPU support. That unfortunately doesn't work with Docker as far as I know nor any other solution using virtualization...
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Guys if you install bash on Windows using the new developer preview tensorflow does install and kinda work. So you can use that to run it on Windows without using docker. (And it would probably improve the bash for Windows because more people are using it.)
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stop +1!!!
I repeat, stop +1 for $%{^¥ sake! Anyone who comments +1 after this is an idiot! :-P Use Github reactions, dammit!
Could someone give me some kind of moderator status? I'd like to clean this issue from useless +1 comments.
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@mrry How can others get involved in this? How can we help to get TensorFlow running on Windows as soon as possible? At least we can help with testing and bug reporting.
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+1
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+1 for GitHub reactions!
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Here is a summary of what I think is happening in this Windows support issue:
Tensorflow requires Bazel to build from source, If I am not mistaken, Bazel is a build system like GNU Make, but not a compiler.
Based on what I saw as I briefly scanned through the code, source code of Tensorflow itself uses mostly standard C++ library for things like threading so it should be no problem to compile on Windows, essential third-party libraries it uses all have Windows support.
Therefore, I think the main problem lies on lack of build method for Windows rather than source code itself. There are works on using CMake to build instead of Bazel but not complete yet. If someone can translate Bazel build rules to CMake's, I think we will be able to build it on Windows.
- https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/makefile
- https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/cmake
Stable Bazel support for Windows still have a long way to go.
Please correct me if I made a mistake here.
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An update on Windows support for Bazel: the initial set of patches to get Bazel working on Windows has been merged (see bazelbuild/bazel#276), and @dslomov has been able to get Bazel to bootstrap itself on Windows.
We are planning to have experimental support for Windows in Bazel 0.3. If you would like to follow our progress, see the issues tagged "Windows" on the Bazel issue tracker.
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We need windows support!!!!
Can the team tell us please about estimates for native windows support?
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FYI Windows support for Bazel is currently one of our top priorities. Stay tuned.
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@umarniz Alright, didn't mean to denigrate your effort. Definitely not! You did a great job writing that up! Thanks again!
By the way, only to mention this... the Deep MNIST example, which is admittedly already not that simple anymore, takes several hours on my CPU whereas my GPU (GTX 980Ti) rushes through it in at most a few seconds. On a native Ubuntu that is. I've one set up on a USB stick. It works, however dual boot can be quite cumbersome and a huge demotivating factor. Even more so since a hibernated Windows on a UEFI system can be pretty picky when it comes to accessing data on NTFS partitions from Linux...
Sure, I totally agree that Linux (Ubuntu) is the best OS for ML tasks because it's the one most people use, and not without reason. But it still has its disadvantages for enthusiast people like me who not only do ML for a living but also as hobbyists, and who have other hobbies in parallel that rely on Windows... like gaming for example.
I guess that's some first world problems that I'd absolutely love to see solved nevertheless.
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+1
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+1
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If I want to turn on the Bash on Windows, I need to check the Windows Subsystem for Linux (Beta) right? But I can't find this menu in the Windows Features dialog. I'm following the guide here and here.
Do I need to tick Hyper-V check box in the Windows Features dialog?
I've also turned on the Developer mode in the settings already.
It seems like I need to desert these Windows beta bash features and unwillingly use Docker?
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Hello,
For Tensorflow Windows support, are we going to be able to build out Windows Binaries that are not msys2 binaries? This makes sense since it would be a possible to do actual deployment on most user's machines.
If this is not possible, can we have a way to just deploy a stripped down version of the prediction pass/forward pass of the library for this purpose? I can train on Linux just fine but for the actual prediction process, I will like to be able to deploy on a regular Windows box without msys2. Is this on the roadmap?
If you look at what CNTK is doing:
https://github.com/Microsoft/CNTK/wiki/Native-Evaluation-Interface
They have a much easier way to do evaluation/prediction using a stripped down DLL. Can we have something like this in Tensorflow as well for Windows ( and other platforms I can imagine will find it very useful).
Thanks!
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I think its a great suggestion!
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+1 native support on windows should be available
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I have no knowledge of that but we should ask the Windows team about that.
People have gotten GUI programs to work through windows but it uses CPU not
GPU so I'm thinking it does not currently have access
On Apr 19, 2016 5:37 PM, "hayder78" [email protected] wrote:
That's fantastic.
Using bash on Windows was my biggest hope to use tensorflow on Windows.The biggest question is whether you can use the GPU drivers?
That's the main reason people asking for a native tensorflow installation
in windows. Otherwise cpu support is just fine through docker or Linux
virtual machine—
You are receiving this because you commented.
Reply to this email directly or view it on GitHub
#17 (comment)
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Yeah. I read that GUI programs run through bash in windows will use a generic GPU driver. Which means does not use the nvidia drivers.
Let's pray that Google is working on a tensorflow on Windows under the hood.
I think bash for Windows needs time to be mature enough and bug free. In the meantime probably VM and docker will be a better choice.
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@off99555 You're Windows 10 should have the latest preview release (Fast Ring). Check your build, if it is lower than ~14000, then you don't have this feature yet. (This update will be GA August 2nd)
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I'll take a look into whether Continuum can provide a conda package for tensorflow.
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or maybe we could port it to a more reasonable build system. perhaps cmake.
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+1 for Windows native support, including GPU.
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The link to follow Bazel's Windows issues provided by @davidzchen isn't working, the correct one is https://github.com/bazelbuild/bazel/labels/category%3A%20windows
(I know everyone is hoping for Windows native support + GPU, I am waiting too, but we have to wait until Bazel for Windows gets stable, helping in testing and contributing to Bazel will probably speed up the process)
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One interesting piece of news: @shanselman wrote a blog post about running TensorFlow on Bash for Windows.
We still intend to provide first-class Windows support, but adventurous users might find this a good way to get started in the mean time.
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@aselle Thanks for the useful update, much appreciated!
@mrry Hello, how are the specifics of the Windows implementation going to be rolled out?
-
Will we have (ideally) a VS2015 solution that we can build with our apps/tools? A cmake method that generates the VS solution works too.
-
Is this going to be a statically linked or dynamically linked library?
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Will there be a lightweight forward pass/evaluation module/library that we can use for deployment with our tools/apps?
The current resource I could find regarding deploying tensorflow with a C++ standalone app is here:
https://medium.com/jim-fleming/loading-a-tensorflow-graph-with-the-c-api-4caaff88463f#.7ejb8h7zk
My main concern is what is stated here:
"The build is huge, coming in at 103MB, even for this simple example. Much of this is for TensorFlow, CUDA support and numerous dependencies we never use. This is especially true since the C++ API doesn’t support much functionality right now, as a large portion of the TensorFlow API is Python-only. There is probably a better way of linking to TensorFlow (e.g. shared library) but I haven’t gotten it working yet."
If there is a better way to get around linking a large static library that will be great, especially for the purposes of a forward pass/evaluation which does not really need GPU support.
Thanks!
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Same, I was kind of disappointed to see no mention of Windows in the download and install page.
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Anyone have an idea of what the major incompatibilities/accommodations are? Is it it mostly issues with file paths, etc?
It's built with Bazel, which only supports linux/mac, but the good news is that windows support for bazel seems will be out by the end of this year.
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👍
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👍
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+1/0.0
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+1
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Yeah, windows support would be super nice.
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+1
+1
+1
yes please
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Judging by the use of bazel across the documentation, I assume its a matter of waiting for bazel to support windows. Is there anything specific to Tensorflow that would need to be addressed for windows to be supported, or is just bazel?
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One question I have is when Bazel support is actually arriving on Windows. Looking at the Bazel repository it says they are planning to support Android in Windows, but I didn't see any reference to building (what I assume are) native packages.
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Here is the bug we are using to track Bazel support for Windows: bazelbuild/bazel#276. A month ago, @dslomov was able to get Bazel to bootstrap itself on Windows. The plan is to finish Windows support by end of this year.
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@davidzchen I was actually working with that repo earlier this afternoon to try and give it a go without much luck, I might play around with it some more to see if I can get it to successfully bootstrap itself.
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+1
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@ahmadia do you have any tips on how to install tensorflow using conda?
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Right now we're in the same boat as everybody else because there is no port of TensorFlow to Windows. If somebody can put together a Windows port I'm happy to help with the binary build/deployment. Somebody has already put together a recipe for OS X/Linux available with conda install -c memex tensorflow
.
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+1 for this
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+1
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+1
also cmake support would be great
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I put together an article with instructions and screenshots for getting TensorFlow to work on a Windows machine using Docker here using the tips from issue 42 if it's helpful for anyone.
Although I'm still not sure how I can take advantage of my GPU though if TensorFlow is running in a VM on my Windows machine.
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+1 native windows support would be extremely helpful
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+1
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I want have a version of TensorFlow for Windows 7,if you have,Please send my email.
My email address: [email protected].
Thanks!
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+1
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Windows support is a bit of a dramatic effort. Maybe supporting Windows only for a truly standard compiler (gcc / tdm-gcc / mingwpy) and on a modern Python (3.4?) would be a much more easy target ?
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Perhaps using Clang frontend with VC++ CodeGen would be a fastest pathway to get working Windows builds -> Clang with Microsoft CodeGen in VS 2015 Update 1. Project was designed to provide consistently working toolchain for cross platform builds of code primarily targeting windows, nonetheless scenario in which *nix code is compiled on windows could be equally interesting. MSFT C++ team states that code they write is contributed back to LLVM project so it should allow for fast and joint work on getting good cross platform support.
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+1
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+1
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+1
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+1
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+1
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+1
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+1
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+1 . This is the first Python package I recall not working on Windows. It seems odd to me, as my understanding is that NVIDIA's drivers have always been better on Windows than Linux, and I have a GTX 970 that's feeling bored these days.
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I have ported most of the tensorflow c++ to a windows build use vc 2013. so far most code compile and linked use my own sources file. the biggest challenge for me to work around is that: it use static variable to register op and kernel. I build them as static library and app link to it will skip those static variable. I have to use a stub.cpp in app folder to include used ops and kernels.
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@yuanhua8 any chance you push your changes to a github repo? BTW, I solved the static registration thing in caffe by using dumpin to generate a header that forces symbol liking. See BVLC/caffe#2816 and https://github.com/willyd/caffe/tree/msvc for details.
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Hope native Tensorflow for Windows will be ready soon, might have to wait until bazel for Windows is stable, thrilled to try Deep Learning course by Google and Udacity!
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Same here, i begun the deep learning course offered by Google and here i am stuck because i am running Windows.
When should we expect support for Windows ?
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I noticed lot of people facing a problem running this under Windows so did a quick write up on how to set it under Windows using Vagrant and Docker:
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@SeveQ I completely agree and I personally prefer using Linux for all my ML experiments due to the ease of setting up multiple unique programming environments. This guide was meant to run the course material from Google as the training sets and examples they have are for beginners with smaller data sets which should be able to run in a CPU only environment too.
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@SeveQ I didn't take it that way either :)
I agree with dual boot being a pain, I had to completely move to Ubuntu for a few months otherwise it becomes quite cumbersome to switch but I love the power that bash shell gives for working with large data sets.
I think i'll see what I can do to help add Windows support for TensorFlow myself.
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+1
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@umarniz Sounds good. I don't have the time right now to also dedicate myself to this, unfortunately. Other priorities like graduating... Windows support for TensorFlow would be a great help though in this matter. I'm graduating as MSc., systems engineer, specializing in, who would have thought, machine learning...
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any update on this
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I make a port of the c++ code into our internal branch. Sorry can not publish back since it take dependency of our code branch. Find some gap btw c++ and Python. But the core engine work for me in our windows/Vc environment.
H y
Sent from my iPhone
On Jan 30, 2016, at 2:46 AM, datashinobi [email protected] wrote:
any update on this
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For all those who want to use Tensorflow and can surrender GPU support here is an Blogpost about installing Tensorflow with jupyter notebook support for Windows with Docker.
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C:\Users\Desktop>docker run -it b.gcr.io/tensorflow/tensorflow
Unable to find image 'b.gcr.io/tensorflow/tensorflow:latest' locally
docker: Error response from daemon: unable to ping registry endpoint https://b.g
cr.io/v0/
v2 ping attempt failed with error: Get https://b.gcr.io/v2/: dial tcp 64.233.188
.82:443: i/o timeout
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Any news regarding being able to use TensorFlow in Windows, without Docker?
How hard would it be to offer a CMake build process that works both for Linux and Windows (creating a MVS project)?
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I wrote instructions for installing tensorflow on a CentOS virtual machine. If you're having trouble working with Docker, this might be your solution.
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That's fantastic.
Using bash on Windows was my biggest hope to use tensorflow on Windows.
The biggest question is whether you can use the GPU drivers?
That's the main reason people asking for a native tensorflow installation in windows. Otherwise cpu support is just fine through docker or Linux virtual machine
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I am now making a choice between tensorflow and CNTK.
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another +1 for windows with GPU support. Although TF seemed a better option, I had to switch to Theano as a result for lack of GPU support on windows. It will be nice if there is a mention on TF's roadmap as to whether support is going to be available in future releases, as it will help with loads of researchers decision making.
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@mrry Hi Derek Murray,
I am glad to hear from you - as a Google software engineer - that you intend to provide a native windows support for tensorflow. Are you part of the tensorflow developer team at Google?
At least I have a hope now.
Any rough estimate when will be a beta release?
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Another +1, very interested to see this happen. If and when Bazel actually runs on Windows, will TF actually compile on the platform? Or are there other portability issues as well e.g. network, file system calls?
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Well bazel seems to work most of the time on windows now, aside from a few name errors (illegal characters or very long commands). There definitely are issues to getting a working windows tensorflow other than just having a working bazel. All the errors I have got so far are of the type:
ERROR: C:/tensorflow-orig/tensorflow/contrib/metrics/BUILD:16:1: in linkshared attribute of cc_binary rule //tensorflow/contrib/metrics:python/ops/_set_ops.so: 'linkshared' used in non-shared library. Since this rule was created by the macro 'tf_custom_op_library', the error might have been caused by the macro implementation in C:/tensorflow-orig/tensorflow/tensorflow.bzl:599:31.
So I am guessing build rules need to be updated for windows first.
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@Sabrewarrior I tried to build the tensorflow on windows using bazel, but the configure file just give some errors. I wondering if you changed or added some parts on that file to be supported on windows
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@Fhrozen https://github.com/Sabrewarrior/tensorflow/blob/test/tf_win_env.txt
These are my installed packages when I ran configure without any changes. I am running this on msys2 with python 2.7 on a Windows 10 machine.
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@Sabrewarrior thanks for the answer. I checked it, was the spaces in the folder name my problem.
Now i got this error on the cuda version.
`Please specify which gcc nvcc should use as the host compiler. [Default is /mingw64/bin/gcc]:
Please specify the Cuda SDK version you want to use, e.g. 7.0. [Leave empty to use system default]: 7.5
Please specify the location where CUDA 7.5 toolkit is installed. Refer to README.md for more details. [Default is /usr/local/cuda]: C:/CUDA/v7.5
Please specify the Cudnn version you want to use. [Leave empty to use system default]: 4.0.7
Please specify the location where cuDNN 4.0.7 library is installed. Refer to README.md for more details. [Default is C:/CUDA/v7.5]: cuda/
Please specify a list of comma-separated Cuda compute capabilities you want to build with.
You can find the compute capability of your device at: https://developer.nvidia.com/cuda-gpus.
Please note that each additional compute capability significantly increases your build time and binary size.
Setting up Cuda include
Setting up Cuda
ln: fallo al crear el enlace simbólico '../../../third_party/gpus/cuda/extras/visual_studio_integration/MSBuildExtensions/CUDA': No such file or directory
ln: fallo al crear el enlace simbólico '../../../third_party/gpus/cuda/extras/visual_studio_integration/MSBuildExtensions/7.5.props': No such file or directory
ln: fallo al crear el enlace simbólico '../../../third_party/gpus/cuda/extras/visual_studio_integration/MSBuildExtensions/CUDA': No such file or directory
ln: fallo al crear el enlace simbólico '../../../third_party/gpus/cuda/extras/visual_studio_integration/MSBuildExtensions/7.5.targets': No such file or directory
ln: fallo al crear el enlace simbólico '../../../third_party/gpus/cuda/extras/visual_studio_integration/MSBuildExtensions/CUDA': No such file or directory
ln: fallo al crear el enlace simbólico '../../../third_party/gpus/cuda/extras/visual_studio_integration/MSBuildExtensions/7.5.xml': No such file or directory
xargs: bash: finish with status 255; aborting
`
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@Fhrozen AFAIK you can't use gcc as a compiler for CUDA on Windows. Only Visual C++ Compiler is supported by CUDA on Windows (see here).
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Any updates on windows? whats needed to get it run natively having GPU available as well?
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No windows? why? at least CPU only versions?
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Related Issues (20)
- tf.raw_ops.ResourceApplyGradientDescent: Aborted (core dumped)
- tf.raw_ops.ResourceApplyMomentum: Aborted (core dumped)
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- A check fail can be triggered in tf.raw_ops.ResourceSparseApplyKerasMomentum
- A check fail can be triggered in tf.raw_ops.StatefulPartitionedCall
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- Error: numpy.core._exceptions._ArrayMemoryError: Unable to allocate 115. TiB for an array with shape (3983360, 3983360) and data type float64
- Unable to retrieve BLAS factory in Tensorflow 2.16.1 HOT 2
- TypeError: Exception encountered when calling layer "custom_crop_layer_2" " f"(type CustomCropLayer). HOT 2
- TensorFlow 2.16 / Keras 3 have undocumented breaking API changes HOT 3
- im getting this error in jupyter- Exception encountered when calling Lambda.call() in this line- attention_context = Lambda(lambda x: tf.einsum('ijk,ijl->ikl', x[0], x[1]))([attention_scores, se3]) HOT 1
- Predict crashes if last batch is smaller then batch_size HOT 2
- Comment in detection_postprocess.cc is incorrect and misleading. HOT 2
- tf.keras.layers.PReLU outputs NaN on positive input HOT 3
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- TPU Colab Issue HOT 1
- TensorFlow 2.16 API docs not available online HOT 3
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