I trained a UNET model using data loaders now I want to use the trained model to get predictions for a new random image of the size (256x256) single channel. How do I do that?

I tried:

```
model.eval()
predb = model(torch.from_numpy(img).float().cuda())
```

But getting:

```
v.py:459, in Conv2d._conv_forward(self, input, weight, bias)
455 if self.padding_mode != 'zeros':
456 return F.conv2d(F.pad(input, self._reversed_padding_repeated_twice, mode=self.padding_mode),
457 weight, bias, self.stride,
458 _pair(0), self.dilation, self.groups)
--> 459 return F.conv2d(input, weight, bias, self.stride,
460 self.padding, self.dilation, self.groups)
RuntimeError: GET was unable to find an engine to execute this computation
```