Develop Reference

Is it possible to run tensorflow-gpu on a computer without a GPU or CUDA?

I have two Windows computers, one with and one without a GPU.
I would like to deploy the same python script on both (TensorFlow 1.8 Object Detection), without changing the packaged version of TensorFlow. In other words, I want to run tensorflow-gpu on a CPU.
In the event where my script cannot detect nvcuda.dll, I've tried using a Session config to disable the GPU, like so:
config = tf.ConfigProto(
device_count = {'GPU': 0}
)
and:
with tf.Session(graph=detection_graph, config=config) as sess:
However, this is not sufficient, as TensorFlow still returns the error:
ImportError: Could not find 'nvcuda.dll'. TensorFlow requires that this DLL be installed in a directory that is named in your %PATH% environment variable.
Typically it is installed in 'C:\Windows\System32'. If it is not present, ensure that you have a CUDA-capable GPU with the correct driver installed.
Is there any way to disable checking for a GPU/CUDA entirely and default to CPU?
EDIT: I have read the year-old answer regarding tensorflow-gpu==1.0 on Linux posted here, which suggests this is impossible. I'm interested to know if this is still how tensorflow-gpu is compiled, 9 versions later.

tensorflow GPU based installation

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.

Compiling binary with tensorflow library for cpu: Cannot find cuda library?

In development, I have been using the gpu-accelerated tensorflow
https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.2.1-cp35-cp35m-linux_x86_64.whl
I am attempting to deploy my trained model along with an application binary for my users. I compile using PyInstaller (3.3.dev0+f0df2d2bb) on python 3.5.2 to create my application into a binary for my users.
For deployment, I install the cpu version, https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.2.1-cp35-cp35m-linux_x86_64.whl
However, upon successful compilation, I run my program and receive the infamous tensorflow cuda error:
tensorflow.python.framework.errors_impl.NotFoundError:
tensorflow/contrib/util/tensorflow/contrib/cudnn_rnn/python/ops/_cudnn_rnn_ops.so:
cannot open shared object file: No such file or directory
why is it looking for cuda when I've only got the cpu version installed? (Let alone the fact that I'm still on my development machine with cuda, so it should find it anyway. I can use tensorflow-gpu/cuda fine in uncompiled scripts. But this is irrelevant because deployment machines won't have cuda)
My first thought was that somehow I'm importing the wrong tensorflow, but I've not only used pip uninstall tensorflow-gpu but then I also went to delete the tensorflow-gpu in /usr/local/lib/python3.5/dist-packages/
Any ideas what could be happening? Maybe I need to start using a virtual-env..

undefined symbol: cudnnCreate in ubuntu google cloud vm instance

I'm trying to run a tensorflow python script in a google cloud vm instance with GPU enabled. I have followed the process for installing GPU drivers, cuda, cudnn and tensorflow. However whenever I try to run my program (which runs fine in a super computing cluster) I keep getting:
undefined symbol: cudnnCreate
I have added the next to my ~/.bashrc
export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:/usr/local/cuda-8.0/lib64:/usr/local/cuda-8.0/extras/CUPTI/lib64:/usr/local/cuda-8.0/lib64"
export CUDA_HOME="/usr/local/cuda-8.0"
export PATH="$PATH:/usr/local/cuda-8.0/bin"
but still it does not work and produces the same error

Answering my own question: The issue was not that the library was not installed, the library installed was the wrong version hence it could not find it. In this case it was cudnn 5.0. However even after installing the right version it still didn't work due to incompatibilities between versions of driver, CUDA and cudnn. I solved all this issues by re-installing everything including the driver taking into account tensorflow libraries requisites.

Python pyopencl DLL load failed even with latest drivers

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