I've installed the latest CUDA and driver for my GPU. I'm using Python 2.7.10 on Win7 64bit.
I tried installing pyopencl from:
a. the unofficial windows binaries at http://www.lfd.uci.edu/~gohlke/pythonlibs/#pyopencl
b. by compiling my own after getting the sources from https://pypi.python.org/pypi/pyopencl
The installation was successful on both cases but I get the same error message once I try to import it:
>>> import pyopencl
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "C:\Python27\lib\site-packages\pyopencl-2015.1-py2.7-win-amd64.egg\pyope
cl\__init__.py", line 30, in <module>
import pyopencl._cl as _cl
ImportError: DLL load failed: The specified procedure could not be found.
>>>
I have Visual C++ Redistributable for Visual Studio 2015 installed from https://www.microsoft.com/en-us/download/details.aspx?id=48145 .
I also tried with 2 different versions of the GPU driver (including latest). Same thing.
A lot of people seem to get the same error and on some forums I read that by updating the GPU drivers to latest, it works fine. But not for me.
Anyone knows how to fix this?
I'm affraid there isn't one right answer to this problem. Each case is different. It depends on what is installed in the OS.
To track down such problems I normally use Dependency Walker.
In this specific case I would open _cl.pyd (usually in C:\Python27\Lib\site-packages\pyopencl) in Dependency Walker to check if there aren't any missing dependencies or if for example OpenCL.dll is actually the one which should be used. OpenCL.dll may be installed by other programs and their path added to PATH. Also OpenCL.dll in System32 may be too old. Basically trial and error renaming all but one OpenCL.dll into OpenCL.dll.bak and/or removing paths from PATH may get you there.
I had this same problem and discovered it was caused by AMD OpenCL.dll not having a function introduced in OpenCL 2.1. The Gohlke site only has OpenCL 2.1 and 1.2, while AMD drivers support 2.0.
Because I wanted 2.0, the easy fix was to manually replace the AMD System32/OpenCL.dll with the one from Intel SDK with experimental 2.1 support.
I had the same problem here, the way I resolved it was:
Make sure you have downloaded and installed the right OpenCL SDK. For example
Intel
NVIDIA
Open the Windows Command Prompt cmd and set the LIB and INCLUDE environment variables. For example
Intel:
set INCLUDE=C:\Program Files (x86)\IntelSWTools\system_studio_2020\OpenCL\sdk\include
set LIB=C:\Program Files (x86)\IntelSWTools\system_studio_2020\OpenCL\sdk\lib\x64
NVIDIA:
set LIB=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v3.2\lib\x64
set INCLUDE=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v3.2\include
now run pip install pyopencl --no-cache-dir
open Python and test import pyopencl
there might be a way to install PyOpenCL via pipwin or by using the --global-option to set the include and library folders. But I haven't succeeded so far.
P.S. The above mentioned NVIDIA OpenCL SDK (i.e., CUDA toolkit) turns out to be very outdated. please don't use it. If you have that installed, please uninstall and install the newer versions.
Try both the versions 1.2 and 2.1 I was trying with later and got this issue. Switched the whl and it works but used the Intel GPU. NVidia OpenCL.dll is 2.0 and that is not working still.
Just checked the cl.get_platforms array and found them
0. Intel
1. NVidia
pyopencl.Platform Intel(R) OpenCL & pyopencl.Device Intel(R) Core(TM) ... Intel(R) OpenCL
pyopencl.Platform NVIDIA CUDA & pyopencl.Device Quadro ... NVIDIA CUDA
I had the same problem in my Lenovo yoga 720. It has NVidia Geforce GTX1050 and intel i7 630 CPU/GPU.
I installed a long time ago update drivers and SDK for Nvidia CUDA. But now I what to run python OpenGL and I install intel SDK also. Pip install pyopencl without problems but import pyopengl give me dll load failure.
Solution was to change Windows\system32\opencl.dll to a new one. The old one was NVidia signed (you can see it in properties of file opencl.dll). The new one is Microsoft signed version 2.1.1.0 Khronos OpenCL ICD
I hope this is useful for you. Solution arrived after a long time trying a lot of things... but nothing worked except the new opencl.dll file
Related
So im trying to do some machine learning, and i want to make use of my gpu.
Im on tensorflow version 2.6.0(i also tried tensorflow-gpu).I installed CUDA 11.2 and cuDNN 8.1. Added everything to PATH like it says here https://www.tensorflow.org/install/gpu. However i still get the error that it cant find the cudart64_110.dll. The file even is in the 'NVIDIA GPU Computing Toolkit\CUDA\v11.2\bin' directory. Anyone got an idea?
I got the same error today. In previous version of tf, I need to install a Nvidia toolkit to get the file.
Here is the right toolkit for the cudart64_110.dll file: https://developer.nvidia.com/cuda-11.3.0-download-archive
Then just follow the installation guide. If you need more help or it doesnt work, just write it.
This error is most likely due to three issues:
You haven't installed CUDA and CUDNN from Nvidia.
You don't have an NVIDIA graphics card on your computer (integrated or external )
having an outdated Microsoft Visual C++ Redistributable for Visual Studio if you are using a Windows.
go ahead to https://learn.microsoft.com/en-us/cpp/windows/latest-supported-vc-redist?view=msvc-170 and install an updated version of Microsoft Visual C++ Redistributable that fits your system.
If you checklist all the above , you won't have any error messages like that.
I'm in trouble. I did my best and I'm still having problems with Tensorflow. I just wanted to use something, but I can't, and that makes me extremely frustrated. Who knows when I'll be able... Anyway, I'll tell you what happened, maybe some blessed soul will clear my doubts once and for all.
I have a Windows 7 notebook, my CPU apparently doesn't support AVX, and I don't have GPU. I tried to install two versions of tensorflow that don't require AVX. Obviously, one at a time, I didn't try to install both at the same time haha.
With python 3.6: tensorflow-1.5.0-cp36-cp36m-win_amd64.whl
When using this, an error appears: ImportError: DLL load failed with error code -1073741795.
Failed to load the native TensorFlow runtime
With python 3.7: tensorflow-1.11.0-cp37-cp37m-win_amd64.whl
When using this, an error appears: ImportError: DLL load failed with error code 3221225501.
Failed to load the native TensorFlow runtime.
That is, nothing worked.
Some settings on my PC:
Microsoft Windows 7 Professional,
Processor: Intel(R) Celeron(R) CPU 847 # 1.10GHz, 1100 Mhz, 2 Cores, 2 Logic Processors,
System Type: x64-based PC,
Physical Memory (RAM): 4.00GB,
Please help me.
Try using Tensorflow cpu
pip install tensorflow-cpu
https://pypi.org/project/tensorflow-cpu/
If it doesn't work you can try this repo https://github.com/fo40225/tensorflow-windows-wheel, it provides Legacy & low-end CPU (without AVX) support.
I have a python file which uses tensorflow GPU in it. It uses GPU when i run the file from console using python MyFile.py.
However, when i convert it into exe using pyinstaller, it converts and runs successfully, But it does not use GPU anymore when i run the exe. This happens on a system which was not used for developing MyFile.py. Checking on the same system which was used in development, it uses just 40-50% GPU, which was 90% if i run the python script.
My application even has a small UI made using tkinter.
Though application runs fine on CPU, It is incredibly slow. (I am not using --one-file flag in pyinstaller.) Although having GPU, The application is not using it.
My questions are:
How do I overcome this issue? Do I need to install any CUDA or CuDnn toolkits in my Destination computer?
(Once the main question is solved) Can i use 1050ti in development and 2080ti in destination computer, if the CuDnn and CUDA versions are the same?
Tensorflow Version : 1.14.0 (I know 2.x is out there, but this works perfectly fine for me.)
GPU : GeForce GTX 1050 ti ( In development as well as deployment.)
CUDA Toolkit : 10.0
CuDnn : v7.6.2 for cuda 10.0
pyinstaller version : 3.5
Python version : 3.6.5
As I asnwered also here, according to the GitHub issues in the official repository (here and here for example) CUDA libraries are usually dynamically loaded at run-time and not at link-time, so they are typically not included in the final exe file (or folder) with the result that the generated exe file won't work on a machine without CUDA installed. The solution (please refer to the linked issues too) is to put the DLLs necessary to run the exe in its dist folder (if generated without the --onefile option) or install the CUDA runtime on the target machine.
My system is ubuntu 16.04 version my laptop is dell Inspiron-5521 and it has intel graphic card but tensorflow needs nvidia graphics for cuda support.
Is there any way where i can run tensorflow with GPU(with CPU is working) on intel graphics.
During installation of tensorflow-gpu i have no error when i import i get
"
Failed to load the native TensorFlow runtime
."
Did some digging then found to install cuda downloaded the "cuda_9.1.85_387.26_linux.run" file but faces issues while running it
"Detected 4 CPUs online; setting concurrency level to 4.
The file '/tmp/.X0-lock' exists and appears to contain the process ID
'1033' of a runnning X server.
It appears that an X server is running. Please exit X before
installation. If you're sure that X is not running, but are getting
this error, please delete any X lock files in /tmp."
Deleted files from tmp folder and tried still same issue.
To run tensorflow-gpu you need nvidia card. You'll need to stick to running normal tensorflow on CPU.
Is Intel based graphic card compatible with tensorflow/GPU?
Tensorflow does not support OpenCL API that you can use with Intel or AMD, only CUDA. CUDA is a proprietary NVidia technology that only works with NVidia GPUs.
You may like to search for machine learning frameworks that utilise OpenCL, but I only find some niche projects at the moment.
I had to switch from AMD to NVidia to be able to run Tensorflow calculations on GPU.
I was setting up python and theano for use with gpu on;
ubuntu 14.04,
GeForce GTX 1080
already installed NVIDIA driver (367.27) and CUDA toolkit (7.5) successfully for the system,
but on testing with theano gpu implementation I get the above error (for example; when importing theano with gpu enabled)
I have tried to look for possible solutions but didn't succeed.
I'm a little new to ubuntu and gpu programming, so I would appreciate any insight into how I can solve this problem.
Thanks
As Robert Crovella said, SM 6.1 (sm_61) is only supported in CUDA 8.0 and above, and thus you should download CUDA 8.0 Release Candidate from https://developer.nvidia.com/cuda-toolkit
Ubuntu 14.04 is supported, and the instructions on the website on how to setup should be straightforward (copy and paste lines to the console).
I would also recommend downloading CUDA 8.0 when it comes out, since the RC is not the final version.
I was able to find a solution to this problem (since I still want to use CUDA 7.5) by including the following line in the .theanorc file
flags = -arch=sm_52
no more nvcc fatal error