Repository: pytorch
Issue:  Issue with Vulkan Device for nn.Conv2d Operation
Labels: triaged,module: vulkan

### 🐛 Describe the bug

## 🐛 Bug

I encountered an issue when attempting to move a simple model with an `nn.Conv2d` layer to a Vulkan device. Despite ensuring that my environment supports Vulkan and that my PyTorch installation is up-to-date, executing the model on a Vulkan device results in a RuntimeError, indicating that the tensor does not have a device assigned.



### To Reproduce

Here's a simplified version of the code that reproduces the error:

```python
import torch
import torch.nn as nn

class EmptyModel(nn.Module):
    def __init__(self, frame_depth, img_size):
        super(EmptyModel, self).__init__()
        self.motion_conv1 = nn.Conv2d(3, 3, kernel_size=3, stride=1, padding=1, bias=False)

    def forward(self, x):
        y = self.motion_conv1(x)
        return x

device = torch.device('vulkan')

model = EmptyModel(frame_depth=10, img_size=72)
model.to(device, dtype=torch.float32)

input_tensor = torch.rand(1, 3, 72, 72)
input_tensor = input_tensor.to(device, dtype=torch.float32)

with torch.no_grad():
    output = model(input_tensor)
    print(output.shape)

```

here is the error log 
``` python

---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
File /home/ldd/projects/Test/t2.py:25
     22 input = input.to(device, dtype=torch.float32)
     24 with torch.no_grad():
---> 25     output = model(input)
     26     print(output.shape)

File ~/anaconda3/envs/vulkan/lib/python3.12/site-packages/torch/nn/modules/module.py:1532, in Module._wrapped_call_impl(self, *args, **kwargs)
   1530     return self._compiled_call_impl(*args, **kwargs)  # type: ignore[misc]
   1531 else:
-> 1532     return self._call_impl(*args, **kwargs)

File ~/anaconda3/envs/vulkan/lib/python3.12/site-packages/torch/nn/modules/module.py:1541, in Module._call_impl(self, *args, **kwargs)
   1536 # If we don't have any hooks, we want to skip the rest of the logic in
   1537 # this function, and just call forward.
   1538 if not (self._backward_hooks or self._backward_pre_hooks or self._forward_hooks or self._forward_pre_hooks
   1539         or _global_backward_pre_hooks or _global_backward_hooks
   1540         or _global_forward_hooks or _global_forward_pre_hooks):
-> 1541     return forward_call(*args, **kwargs)
   1543 try:
   1544     result = None

File /home/ldd/projects/Test/t2.py:12
     11 def forward(self, x):
---> 12     y = self.motion_conv1(x)
     13     return x

File ~/anaconda3/envs/vulkan/lib/python3.12/site-packages/torch/nn/modules/module.py:1532, in Module._wrapped_call_impl(self, *args, **kwargs)
   1530     return self._compiled_call_impl(*args, **kwargs)  # type: ignore[misc]
   1531 else:
-> 1532     return self._call_impl(*args, **kwargs)

File ~/anaconda3/envs/vulkan/lib/python3.12/site-packages/torch/nn/modules/module.py:1541, in Module._call_impl(self, *args, **kwargs)
   1536 # If we don't have any hooks, we want to skip the rest of the logic in
   1537 # this function, and just call forward.
   1538 if not (self._backward_hooks or self._backward_pre_hooks or self._forward_hooks or self._forward_pre_hooks
   1539         or _global_backward_pre_hooks or _global_backward_hooks
   1540         or _global_forward_hooks or _global_forward_pre_hooks):
-> 1541     return forward_call(*args, **kwargs)
   1543 try:
   1544     result = None

File ~/anaconda3/envs/vulkan/lib/python3.12/site-packages/torch/nn/modules/conv.py:460, in Conv2d.forward(self, input)
    459 def forward(self, input: Tensor) -> Tensor:
--> 460     return self._conv_forward(input, self.weight, self.bias)

File ~/anaconda3/envs/vulkan/lib/python3.12/site-packages/torch/nn/modules/conv.py:456, in Conv2d._conv_forward(self, input, weight, bias)
    452 if self.padding_mode != 'zeros':
    453     return F.conv2d(F.pad(input, self._reversed_padding_repeated_twice, mode=self.padding_mode),
    454                     weight, bias, self.stride,
    455                     _pair(0), self.dilation, self.groups)
--> 456 return F.conv2d(input, weight, bias, self.stride,
    457                 self.padding, self.dilation, self.groups)

RuntimeError: tensor does not have a device

```

### Versions

```
pytorch version ： 2.4.0a0+git239abb2
OS : Ubuntu : 22.04
```