MPS 后端 ¶

mps 该设备为 MacOS 设备上的 GPU 提供了高性能训练，并使用 Metal 编程框架。它引入了一种新的设备，可以将机器学习计算图和原语映射到 Metal Performance Shaders Graph 框架和 Metal Performance Shaders 框架提供的各自优化的内核上。

新的 MPS 后端扩展了 PyTorch 生态系统，并提供了现有脚本的设置和运行 GPU 上操作的能力。

要开始，只需将您的 Tensor 和 Module 移动到 mps 设备上：

# 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)