MPS 後端

mps 裝置可在具有 Metal 程式設計框架的 MacOS 裝置上實現高效能的 GPU 訓練。 它引入了一個新的裝置，分別將機器學習計算圖和原語映射到高效的 Metal Performance Shaders Graph 框架和 Metal Performance Shaders 框架提供的調整後的核心。

新的 MPS 後端擴展了 PyTorch 生態系統，並提供了現有的腳本功能來設定並在 GPU 上執行操作。

要開始使用，只需將您的 Tensor 和 Module 移動到 mps 裝置

# Check that MPS is available
if not torch.backends.mps.is_available():
    if not torch.backends.mps.is_built():
        print("MPS not available because the current PyTorch install was not "
              "built with MPS enabled.")
    else:
        print("MPS not available because the current MacOS version is not 12.3+ "
              "and/or you do not have an MPS-enabled device on this machine.")

else:
    mps_device = torch.device("mps")

    # Create a Tensor directly on the mps device
    x = torch.ones(5, device=mps_device)
    # Or
    x = torch.ones(5, device="mps")

    # Any operation happens on the GPU
    y = x * 2

    # Move your model to mps just like any other device
    model = YourFavoriteNet()
    model.to(mps_device)

    # Now every call runs on the GPU
    pred = model(x)