How to choose the PyTorch version on CentOS

Installing PyTorch on CentOS system requires careful selection of the appropriate version and consider the following key factors:

1. System environment compatibility:

1. Operating system: CentOS 7 or higher is recommended.

2. CUDA and cuDNN: The PyTorch version is closely related to the CUDA version. For example, PyTorch 1.9.0 requires CUDA 11.1, while PyTorch 2.0.1 requires CUDA 11.3. The cuDNN version must also match the CUDA version. Before selecting the PyTorch version, be sure to confirm that compatible CUDA and cuDNN versions have been installed.

3. Python version: PyTorch officially supports Python versions 3.6 to 3.9, but the compatibility of different PyTorch versions for Python versions is slightly different. Python 3.7 or 3.8 is recommended for best compatibility and performance.

4. GPU acceleration: If you need to use NVIDIA GPU acceleration computing, you must install the PyTorch version that supports CUDA and ensure that the GPU driver and CUDA version are correctly installed and compatible.

2. Installation steps:

1. Create a virtual environment (recommended): Use conda to create a separate virtual environment to avoid conflicts with other Python environments in the system.

    conda create -n pytorch_env python=3.8 # It is recommended to use Python 3.8
   conda activate pytorch_env

2. Install PyTorch:

   • CPU version: If GPU acceleration is not required, install the CPU version of PyTorch:

      pip install torch torchvision torchaudio

   • GPU version: If GPU acceleration is required, select the corresponding installation command according to your CUDA version. For example, CUDA version 11.3:

      pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu113

     Please replace cu113 with the CUDA version number you actually installed.

3. Verify the installation: After the installation is complete, run the following code to verify that PyTorch is installed successfully and that the GPU is available:

    import torch
   print(torch.__version__)
   print(torch.cuda.is_available()) # True Indicates that the GPU is available

3. Things to note:

• Driver: Before installing PyTorch, make sure that the NVIDIA graphics card driver is installed that is compatible with the CUDA version.
• System resources: Different PyTorch versions have different requirements for system resources (memory, etc.). Please check whether the system resources are sufficient before installation.

After completing the above steps, you can successfully use PyTorch for deep learning development on the CentOS system. Remember, choosing the correct CUDA version is the key to successful installation of the GPU version PyTorch.

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