How to setup NVIDIA GPU for PyTorch with CUDA and cuDNN on Windows 10/11 | Step by Step

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Are you ready to supercharge your PyTorch projects with GPU acceleration on Windows 10 or 11? Look no further! In this comprehensive tutorial, we'll walk you through the entire process of setting up your NVIDIA GPU for PyTorch using CUDA and cuDNN.
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Here's what you'll learn:

1. Checking GPU compatibility with PyTorch.
2. Installing and Setting up CUDA Toolkit for GPU acceleration.
3. Installing cuDNN for enhanced deep learning performance.
4. Configuring PyTorch to utilize your GPU for faster training and inference.
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Download Links:

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Used Commands:
1: To check the CUDA Version
nvcc --version

2: To check the Python Version
python --version

3: To Verify Pytorch
import torch

print(x)
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Enviroment Variables:
Variable Name
CUDA_PATH C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.1
CUDA_PATH_V11_2 C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.2

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#pytorch
#PyTorchInstallation
#CUDA
#python
#ANACONDA
#deeplearning
#Window
#cuDNN