pytorch判断是否cuda 判断变量类型方式

inputs = Variable(torch.randn(2,2))
inputs.is_cuda # will return false
inputs = Variable(torch.randn(2,2).cuda())
inputs.is_cuda # returns true

>>> a=torch.Tensor()
>>> len(a)
0
>>> len(a) is 0
True

torch.set_default_dtype(d) #对torch.tensor() 设置默认的浮点类型
 
torch.set_default_tensor_type() # 同上，对torch.tensor()设置默认的tensor类型
>>> torch.tensor([1.2, 3]).dtype   # initial default for floating point is torch.float32
torch.float32
>>> torch.set_default_dtype(torch.float64)
>>> torch.tensor([1.2, 3]).dtype   # a new floating point tensor
torch.float64
>>> torch.set_default_tensor_type(torch.DoubleTensor)
>>> torch.tensor([1.2, 3]).dtype # a new floating point tensor
torch.float64
 
torch.get_default_dtype() #获得当前默认的浮点类型torch.dtype
 
torch.set_printoptions(precision=None, threshold=None, edgeitems=None, linewidth=None, profile=None）#)
## 设置printing的打印参数

import torch
flag = torch.cuda.is_available()
print(flag)

ngpu= 1
# Decide which device we want to run on
device = torch.device("cuda:0" if (torch.cuda.is_available() and ngpu > 0) else "cpu")
print(device)
print(torch.cuda.get_device_name(0))
print(torch.rand(3,3).cuda()) 

True
cuda:0
GeForce GTX 1080
tensor([[0.9530, 0.4746, 0.9819],
  [0.7192, 0.9427, 0.6768],
  [0.8594, 0.9490, 0.6551]], device='cuda:0')