Installing Latest TensorFlow version with CUDA, cudNN and GPU support - Step by step tutorial 2021

In this video I show you the freakishly difficult task of setting up the latest tensorflow version with GPU support on Windows 10 :)

GO HERE FIRST:
https://www.tensorflow.org/install/source#gpu

1. Microsoft Visual Studio

• https://visualstudio.microsoft.com/vs/community/

2. the NVIDIA CUDA Toolkit

• https://developer.nvidia.com/cuda-toolkit-archive

3. NVIDIA cuDNN

• https://developer.nvidia.com/cudnn

4. Python (check compatible version from first link)
   conda create --name tf_2.4 python==3.8

5. Tensorflow (with GPU support)
   pip install tensorflow

#tensorflow #deep-learning #developer #programming

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Installing Latest TensorFlow version with CUDA, cudNN and GPU support - Step by step tutorial 2021

In this video I show you the freakishly difficult task of setting up the latest tensorflow version with GPU support on Windows 10 :)

GO HERE FIRST:
https://www.tensorflow.org/install/source#gpu

1. Microsoft Visual Studio

• https://visualstudio.microsoft.com/vs/community/

2. the NVIDIA CUDA Toolkit

• https://developer.nvidia.com/cuda-toolkit-archive

3. NVIDIA cuDNN

• https://developer.nvidia.com/cudnn

4. Python (check compatible version from first link)
   conda create --name tf_2.4 python==3.8

5. Tensorflow (with GPU support)
   pip install tensorflow

#tensorflow #deep-learning #developer #programming

Installing Tensorflow GPU on Anaconda

So, I was trying to use my GPU for the running a tensorflow code, but everytime it would run on CPU. I updated my Nvidia drivers, CUDA Toolkit and my tensorflow without any luck.

After a lot web search and trials i was finally able to get codes to run on GPU instead of CPU. I had to try many different codes and tricks from various sources. It took me more than a month to get the right codes and process. So i thought of putting it all in a single page so that someone new doesn’t has to struggle.

I have a Nvidia GeForce 940M graphics card, and I have Python 3.7 version and Anaconda 4.8.3. Assuming that you already have or know how to install Anaconda and Python, lets get started with installing Tensorflow-GPU. First you need to check if your graphics card supports CUDA. This can be checked on the Nvidia website link: https://developer.nvidia.com/cuda-gpus

#tensorflow #installation #cudnn #gpu #cuda

Step-By-Step Guide to Setup GPU with TensorFlow on Windows Laptop.

The very first and important step is to check which GPU card your laptop is using, based on the GPU card you need to select the correct version of CUDA, cuDNN, MSVC, Tensorflow etc. To check the GPU card on your windows 10 laptop follow below simple steps:

• Right Click on your Desktop
• Open Nvidia Control Panel
• Goto Help -> System Information

#cudnn #cuda #tensorflow #gpu #geforce-gtx-1650

The Easy-Peasy Tensorflow-GPU Installation(Tensorflow 2.1) on Windows 10

Installing Tensorflow for GPU is an immensely complicated task that will drive you crazy. There are n-number of tutorials online that claims their way of doing things is the most efficient one. Despite their presence, I had a hard time getting stuff done as installing Tensorflow 2.1.0 is a bit different than its predecessor(Tensorflow 1). A minor difference in code will trigger AttributeError. So once I have succeeded, the very thought was to share my experience as a blog elaborating on the process.

The Easy Ways of Installation

The below-mentioned steps will definitely make your life easy:

• To start with, it is advisable to verify your GPU as a CUDA compatible one. You can verify it here.
• If Python is not yet installed, you may download it here.
• Once GPU is found to be compatible, you are required to download the CUDA toolkit from the NVIDIA website. It’s mandatory to restart the OS(Windows 10) after installing the toolkit.
• Open the Environment Variables by typing the term ‘environment variables’ in Windows 10 search bar in the taskbar, and select ‘Edit the system environment variables’. After installing the CUDA toolkit, I have to manually enter the CUDA_HOME variable. The other two variables-CUDA_PATH and CUDA_PATH_V11_0 were already present in the System variables list. Note that the three variables viz. CUDA_HOME, CUDA_PATH, and CUDA_PATH_V11_0 have the same variable value(C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.0). If properly installed the System variables will have the three variables(paths) as highlighted by the red stroke as shown below

#gpu #python3 #tensorflow #cudnn #cuda #python

Installing TensorFlow GPU (Updated)

Good News!!..…TensorFlow providing in-built GPU.

Great, but how to install it ?? Don’t worry we will crack this in 2 Steps.

Note: This could be done only if the system has Nvidia Graphics Card (Must and should)

Come on let’s jump into it.

Why GPU’s ?

Using GPU’s we could run our neural network problems so comfortably not wasting time on unusual things (I mean sitting all the day to train them by watching epoch by epoch).

So, in this blog we would like to know the installation process very easily (Trust me) in 2 steps.

Steps :

1. CUDA installation
2. TensorFlow installation

#data-science #tensorflow #gpu-computing #ai #tensorflow-gpu #cuda