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Title: Installing PyTorch and torchvision using Conda: A Step-by-Step Tutorial
PyTorch is a popular open-source machine learning library that provides a flexible and dynamic computational graph, making it a preferred choice for researchers and developers. torchvision is an extension of PyTorch that includes utility functions for working with computer vision tasks. In this tutorial, we will guide you through the process of installing PyTorch and torchvision using the Conda package manager.
Before you begin, make sure you have Conda installed on your system. If not, you can download and install Miniconda or Anaconda from the official website: Conda Installation
Open a terminal or command prompt and create a new Conda environment for your PyTorch project. You can choose a name for your environment; for example, "my_pytorch_env."
Activate the environment:
Decide on the PyTorch version you want to install. You can check the available versions on the official PyTorch website: PyTorch Download
For example, to install PyTorch 1.10.0 with CUDA 11.1 support, use the following command:
Replace the version numbers and CUDA toolkit version with your desired configuration.
Once the installation is complete, you can verify that PyTorch and torchvision are installed correctly by opening a Python interpreter within your Conda environment:
In the Python interpreter, import PyTorch and torchvision:
If the installation was successful, you should see the PyTorch and torchvision version numbers printed.
Congratulations! You have successfully installed PyTorch and torchvision using Conda. You can now start developing machine learning and computer vision applications with the power of PyTorch.
Remember to activate your Conda environment every time you work on your PyTorch project:
Happy coding!
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