pytorch check gpu

In [1]: import torch

In [2]: torch.cuda.current_device()
Out[2]: 0

In [3]: torch.cuda.device(0)
Out[3]: <torch.cuda.device at 0x7efce0b03be0>

In [4]: torch.cuda.device_count()
Out[4]: 1

In [5]: torch.cuda.get_device_name(0)
Out[5]: 'GeForce GTX 950M'

In [6]: torch.cuda.is_available()
Out[6]: True

0
0
Andy Gondzer 110 points

                                    import torch
import torch.nn as nn
dev = torch.device(&quot;cuda&quot;) if torch.cuda.is_available() else torch.device(&quot;cpu&quot;)
t1 = torch.randn(1,2)
t2 = torch.randn(1,2).to(dev)
print(t1)  # tensor([[-0.2678,  1.9252]])
print(t2)  # tensor([[ 0.5117, -3.6247]], device='cuda:0')
t1.to(dev) 
print(t1)  # tensor([[-0.2678,  1.9252]]) 
print(t1.is_cuda) # False
t1 = t1.to(dev)
print(t1)  # tensor([[-0.2678,  1.9252]], device='cuda:0') 
print(t1.is_cuda) # True

class M(nn.Module):
    def __init__(self):        
        super().__init__()        
        self.l1 = nn.Linear(1,2)

    def forward(self, x):                      
        x = self.l1(x)
        return x
model = M()   # not on cuda
model.to(dev) # is on cuda (all parameters)
print(next(model.parameters()).is_cuda) # True

0
0
4.2
10

                                    device = torch.device(&quot;cuda:0&quot; if torch.cuda.is_available() else &quot;cpu&quot;)
#或device = torch.device(&quot;cuda:0&quot;)
device1 = torch.device(&quot;cuda:1&quot;)&nbsp;&nbsp;
for batch_idx, (img, label) in enumerate(train_loader):
&nbsp;&nbsp;&nbsp;&nbsp;img=img.to(device)
&nbsp;&nbsp;&nbsp;&nbsp;label=label.to(device)

4.2 (10 Votes)
0
3.6
12
Koji 90 points

                                    torch.cuda.device_count()

3.6 (10 Votes)
0
4.25
4
ELLIOTTCABLE 130 points

                                    import torch

torch.cuda.is_available()
&gt;&gt;&gt; True

torch.cuda.current_device()
&gt;&gt;&gt; 0

torch.cuda.device(0)
&gt;&gt;&gt; &lt;torch.cuda.device at 0x7efce0b03be0&gt;

torch.cuda.device_count()
&gt;&gt;&gt; 1

torch.cuda.get_device_name(0)
&gt;&gt;&gt; 'GeForce GTX 950M'

4.25 (4 Votes)
0
3.89
9
Rainbow 90 points

                                    torch.version.cuda

3.89 (9 Votes)
0
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