pytorch installation with GeForce RTX 3050 Ti

 1. Install CUDA toolkit 11.8

    ※ WARNING : Please except for "Nsight VSE" to avoid Installation fail.    

2. Download cuDNN (https://developer.nvidia.com/rdp/cudnn-archive)

3. Check your System Environment Variables

4. Copy cuDNN to CUDA Directory

5. Install python package for pytorch(python version 3.10)

CMD : conda install pytorch torchvision torchaudio pytorch-cuda=11.8 -c pytorch -c nvidia

6. Check pytorch works fine.

import subprocess

import torch

def check_torch_cuda():

    print("Checking PyTorch CUDA support...")

    if torch.cuda.is_available():

        print(f"CUDA is available in PyTorch. Device count: {torch.cuda.device_count()}")

        print(f"CUDA version: {torch.version.cuda}")

        print(f"PyTorch is running on device: {torch.cuda.get_device_name(0)}")

    else:

        print("CUDA is not available in PyTorch. Make sure the CUDA toolkit and drivers are properly installed.")

def check_nvidia_smi():

    print("\nChecking NVIDIA System Management Interface (nvidia-smi)...")

    try:

        result = subprocess.run(["nvidia-smi"], stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True)

        if result.returncode == 0:

            print("nvidia-smi output:\n")

            print(result.stdout)

        else:

            print("nvidia-smi could not be executed. Error:\n")

            print(result.stderr)

    except FileNotFoundError:

        print("nvidia-smi command not found. Ensure the NVIDIA drivers are installed and added to the system PATH.")

def main():

    print("CUDA Installation Check")

    print("========================\n")

    check_torch_cuda()

    check_nvidia_smi()

if __name__ == "__main__":

    main()