You can’t concatenate both tensors in their current shape together so would need to flatten them in another way.
Assuming that dim0 is the batch size and you are dealing with 7 samples, you could flatten the tensors in their “feature dimension” and concatenate them afterwards:
pos = torch.randn(7, 2)
pixel_values = torch.randn(7, 1080, 1920, 3)
pixel_values = pixel_values.view(pixel_values.size(0), -1)
x = torch.cat([pos, pixel_values], dim=1)

However, while this works technically, you would have to check if this concatenation and reshaping makes sense in your use case.