MPS 后端¶
mps
设备支持在使用 Metal 编程框架的 MacOS 设备上进行高性能训练。它引入了一种新设备,可以将机器学习计算图和原语分别映射到高效的 Metal Performance Shaders Graph 框架和 Metal Performance Shaders 框架提供的优化内核上。
新的 MPS 后端扩展了 PyTorch 生态系统,并为现有脚本提供了在 GPU 上设置和运行操作的功能。
要开始使用,只需将您的张量和模块移动到 mps
设备
# 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)