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

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

The Easy-Peasy Tensorflow-GPU Installation(Tensorflow 2.1, CUDA 11.0, and cuDNN) on Windows 10. The simplest way to install Tensorflow GPU 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

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