7. Standard Tools

• 7.1. Using IPUs from Jupyter Notebooks
  • Preparing your environment
  • Starting Jupyter with IPU support
    • Installing Jupyter
    • Starting a Jupyter Server
    • Connect your local machine to the Jupyter Server
    • Open the Jupyter notebook in the browser
  • Troubleshooting
    • Installing additional python packages from a notebook
    • Encountering ImportErrors
    • Can’t connect to server
    • Login page
• 7.2. Using VS Code with the Poplar SDK and IPUs
  • Goals
  • Terminology
  • Installing extensions
  • Python development
    • Easily creating an .env file
    • Choosing VS Code’s Python interpreter
    • Using the .env file to access IPUs
    • Debugging code which requires IPUs
  • Debugging C++ libraries and custom ops
    • Difficulty
    • Outline
    • 0. Choose the C++ code to debug
    • 1. Set up launch.json for C++ debugging
    • 2. Set up your Python program to make debugging easy
    • 3. Attach gdbserver to your running process using the PID
    • 4. Connect VS Code to gdbserver
  • Troubleshooting
    • ImportError and ModuleNotFoundError for PopTorch, PopART or TensorFlow
      • Symptoms
      • Solution
    • launch.json config settings are being ignored
  • Features of the Python extension for VS Code