# Motivation
fixes #153022
The root cause is that the XPU backend registers the convolution op using `m.impl`, which bypasses the device guard logic typically added by the code generation system. This can lead to unexpected behavior if the current device isn't explicitly set.

# Additional Context
run the following script
```python
import torch
import torchvision.models as models

torch.manual_seed(0)

model = models.resnet50(weights="ResNet50_Weights.DEFAULT")
model.eval()
data = torch.rand(1, 3, 224, 224)

device = torch.device('xpu:1')  # 'xpu:0'
model = model.to(device=device, dtype=torch.float16)
data = data.to(device, dtype=torch.float16)

with torch.no_grad():
    ret = model(data)
    print(ret)

print("Execution finished")
```
The output is
```bash
         -9.2102e-02, -7.7588e-01, -1.4111e+00, -9.2383e-01,  6.4551e-01,
         -6.0730e-03, -7.8271e-01, -1.1904e+00, -4.1602e-01,  3.2715e-02,
         -4.9854e-01, -6.3623e-01, -8.5107e-01, -6.8555e-01, -9.4434e-01,
         -8.8672e-01, -6.7969e-01, -6.9824e-01, -2.8882e-01,  2.0312e+00]],
       device='xpu:1', dtype=torch.float16)
Execution finished

```

Pull Request resolved: #153067
Approved by: https://github.com/albanD, https://github.com/EikanWang

(cherry picked from commit e06a080)