I was trying to this project for my school https://www.youtube.com/watch?v=COlbP62-B-U
Everything worked smooth till i encountered that pip install tensorflow doesn't work.
then I tried this for install tensorflow TensorFlow not found using pip. I could successfully install tensorflow but still tensorflow-gpu couldn't be install.
Any idea how can I do that.
Updated for tensorflow 2:
Tensorflow 2.x
There is no separate installation for tensorflow GPU in 2.x, it's a unified installation for both CPU and GPU. The package will be built with GPU support if and only if a compatible GPU is available. To verify, use the command:
tf.test.is_built_with_cuda() after installing.
Source
Note that you still need a compatible GPU first.
Tensorflow 1.x:
No, you need a compatible GPU to install tensorflow-GPU.
From the docs.
Hardware requirements: NVIDIA® GPU card with CUDA® Compute Capability
3.5 or higher.
No you cannot, its like installing a soul without body.
But if you are a curious learner and want to try something amazing with DL try buying GPU-compute instances on Cloud or try out Google Colab.
No, but you can use Google Colab (https://colab.research.google.com), which has the option of using GPUs in the notebooks.
No, you Can not install Tensorflow gpu without nvidia graphic card.
Related
I have a computer with the windows operating system with an amd gpu (rx 5600 xt), and I want to run tensorflow on the gpu.
I found "tensorflow-directml" which allows me to run tensorflow on my gpu, but it uses tensorflow 1.14.0.
Is there another version of "tensorflow-directml" that uses tensorflow v2, or is there another way to run tensorflow in my gpu?
Thanks, and sorry if I wrote something wrong or inaccurate
Microsoft has announced DirectML-plugin for tensorflow 2 in June this year. Check it out at this link: https://learn.microsoft.com/en-us/windows/ai/directml/gpu-tensorflow-plugin. However I believe for your particular GPU model DirectML-plugin may not be compatible as of yet.
Is there another version of "tensorflow-directml" that uses tensorflow
v2
No, According to pypi, latest release (i.e. on Sep 12, 2020) tensorflow-directml 1.15.3.dev200911 is available for public. For more details please refer this.
To run Tensorflow in GPU on windows
For TensorFlow 1.x (i.e. for releases 1.15 and older, CPU and GPU packages are separate)
pip install tensorflow-gpu==1.15 # GPU
For Tensorflow 2.x (i.e. V2) onwards, pip package includes GPU support for CUDA enabled cards
pip install tensorflow
For more information please refer this.
I want to do some ML on my computer with Python, I'm facing problem with the installation of tensorflow and I found that tensorflow could work with GPU, which is CUDA enabled. I've got a GPU Geforce gtx 1650, will tensorflow work on that.
If yes, then, how could I do so?
After opening the command prompt in administrator mode,the installation command for Tensorflow with GPU support is as follows:
pip3 install --upgrade tensorflow-gpu
To check if tensorflow has been successfully installed use command:
import tensorflow as tf
To test CUDA support for your Tensorflow installation, you can run the following command in the shell:
tf.test.is_built_with_cuda()
[Warning: if a non-GPU version of the package is installed, the function would also return False. Use this command to validate if TensorFlow was build with CUDA support.]
Finally, to confirm that the GPU is available to Tensorflow, you can test using a built-in utility function in TensorFlow as shown below:
tf.test.is_gpu_available(cuda_only=False, min_cuda_compute_capability=None)
Install tensorflow-gpu to do computations on GPU. You can use the code below to check whether your GPU is being used by tensorflow.
tf.test.is_gpu_available(
cuda_only=False,
min_cuda_compute_capability=None
)
Here are the steps for installation of tensorflow:
Download and install the Visual Studio.
Install CUDA 10.1
Add lib, include and extras/lib64 directory to the PATH variable.
Install cuDNN
Install tensorflow by pip install tensorflow
I don't think if you can.
https://www.tensorflow.org/install/gpu
Tensorflow clearly mentions the list of supported architectures and the 1650 sadly doesn't belong to the list. Check the "cuda enabled gpu cards" link on the website above.
I got a new pc recently with a windows 10 and an RTX 2070. I installed anaconda in order to use python and the deep learning frameworks available as keras. I install with anaconda navigator the keras-gpu package. It seems that installing this package will install a "cuda-toolkit 10" and "cudnn" package on anaconda.
I was wondering if my gpu will be used in a optimize way during the training on keras. In fact, in the past, when I installed keras gpu , I had to install microsoft community 2015 and cuda toolkit 9.0/Cudnn on my own in order to make keras gpu working. So, it seems a bit weird that I had no error.
Thank for the help !
It depends on what backends your keras is using.
e.g. If you are using tensorflow, the following statement will give you the answer.
print(tf.test.is_gpu_available())
I recently found an article that indicates that the conventional methods for downloading python machine learning modules such as tensorflow and keras are not optimized for computers with a cpu. How can I configure tensorflow and keras to make it most compatible with my processor on MacOSX in python 2.7?
If it helps, I use pycharm to download most of my libraries and for my coding interface.
For any environment if you want to install tensorflow, you can simply run this command :
pip install tensorflow (for CPU, python2.7)
pip3 install tensorflow (for CPU, python3)
You need to mention externally if you want to install tensorflow with GPU like this:-
pip install --upgrade tensorflow-gpu
but for GPU you will need CUDA (NVDIA graphics) to run.
and very same way, you can install keras Where you dont have to pass keras-gpu externally while using command:-
pip install keras
I think what you read meant that tensorflow programs work much faster if your computer has a GPU. You need a Nvidia GPU in your computer to install tensorflow with GPU support on your Mac and as far as I know, after version 1.2 tensorflow no longer provides GPU support for MacOS
This question already has an answer here:
tensorflow on GPU doesn't work
(1 answer)
Closed 2 years ago.
I've installed tensorflow CPU version. I'm using Windows 10 and I have AMD Radeon 8600M as my GPU. Can I install GPU version of tensorflow now? Will there be any problem? If not, where can I get instructions to install GPU version?
Your graphics card do not support CUDA drivers without which you cannot use tensorflow on GPU. Your system will run tensorflow but only on CPU.
However you can use pytorch it is another way to similar task. PyTorch has another version called CLTorch which runs on OpenCL which runs on your graphics card.
Please follow this link for more details.
https://github.com/hughperkins/cltorch
First of all, if you want to see a performance gain, you should have a better GPU, and second of all, Tensorflow uses CUDA, which is only for NVidia GPUs which have CUDA Capability of 3.0 or higher. I recommend you use some cloud service such as AWS or Google Cloud if you really want to do deep learning.
If you want to use an AMD GPU with TensorFlow, you can follow the instructions here.
However:
The GPU you are using is not that powerful and unlikely to give you much of a performance boost
You will need to use Linux with these instructions, although there is a Windows version of ComputeCpp it has not been tested with TensorFlow yet.
It depends on your graphic card, it has to be nvidia, and you have to install cuda version corresponding on your system and SO. Then, you have install cuDNN corresponding on the CUDA version you had installed
Steps:
Install NVIDIA 367 driver
Install CUDA 8.0
Install cuDNN 5.0
Reboot
Install tensorflow from source with bazel using the above configuration