pytorch - 在'with statement'中使用device

Question

有没有办法在特定（GPU）设备的上下文中运行pytorch（无需为每个新张量指定设备，例如.to选项）？

类似于tensorflow with tf.device('/device:GPU:0'):的东西......

似乎默认设备是cpu（除非我做错了）：

with torch.cuda.device('0'):
   a = torch.zeros(1)
   print(a.device)

>>> cpu

Answer 1

不幸的是，在当前的实现中，with-device语句不能以这种方式工作，它只能用于在cuda设备之间切换。

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您仍然必须使用device参数来指定使用哪个设备（或.cuda()将张量移动到指定的GPU），使用以下术语：

# allocates a tensor on GPU 1
a = torch.tensor([1., 2.], device=cuda)

所以访问cuda:1：

cuda = torch.device('cuda')

with torch.cuda.device(1):
    # allocates a tensor on GPU 1
    a = torch.tensor([1., 2.], device=cuda)

并访问cuda:2：

cuda = torch.device('cuda')

with torch.cuda.device(2):
    # allocates a tensor on GPU 2
    a = torch.tensor([1., 2.], device=cuda)

但是，没有device参数的张量仍然是CPU张量：

cuda = torch.device('cuda')

with torch.cuda.device(1):
    # allocates a tensor on CPU
    a = torch.tensor([1., 2.])

把它们加起来：

不 - 遗憾的是，with-device语句的当前实现无法以您在问题中描述的方式使用。

---

以下是来自documentation的更多示例：

cuda = torch.device('cuda')     # Default CUDA device
cuda0 = torch.device('cuda:0')
cuda2 = torch.device('cuda:2')  # GPU 2 (these are 0-indexed)

x = torch.tensor([1., 2.], device=cuda0)
# x.device is device(type='cuda', index=0)
y = torch.tensor([1., 2.]).cuda()
# y.device is device(type='cuda', index=0)

with torch.cuda.device(1):
    # allocates a tensor on GPU 1
    a = torch.tensor([1., 2.], device=cuda)

    # transfers a tensor from CPU to GPU 1
    b = torch.tensor([1., 2.]).cuda()
    # a.device and b.device are device(type='cuda', index=1)

    # You can also use ``Tensor.to`` to transfer a tensor:
    b2 = torch.tensor([1., 2.]).to(device=cuda)
    # b.device and b2.device are device(type='cuda', index=1)

    c = a + b
    # c.device is device(type='cuda', index=1)

    z = x + y
    # z.device is device(type='cuda', index=0)

    # even within a context, you can specify the device
    # (or give a GPU index to the .cuda call)
    d = torch.randn(2, device=cuda2)
    e = torch.randn(2).to(cuda2)
    f = torch.randn(2).cuda(cuda2)
    # d.device, e.device, and f.device are all device(type='cuda', index=2)