fix: added dtype and device for torch ones and zeros creation

Author: sbucaille

src/transformers/models/efficientloftr/modeling_efficientloftr.py

@@ -71,10 +71,12 @@ class KeypointMatchingOutput(ModelOutput):
 
 @compile_compatible_method_lru_cache(maxsize=32)
 def compute_embeddings(inv_freq: torch.Tensor, embed_height: int, embed_width: int, hidden_size: int) -> torch.Tensor:
-    i_indices = torch.ones(embed_height, embed_width).cumsum(0).float().unsqueeze(-1)
-    j_indices = torch.ones(embed_height, embed_width).cumsum(1).float().unsqueeze(-1)
+    i_indices = torch.ones(embed_height, embed_width, dtype=inv_freq.dtype, device=inv_freq.device)
+    j_indices = torch.ones(embed_height, embed_width, dtype=inv_freq.dtype, device=inv_freq.device)
+    i_indices = i_indices.cumsum(0).unsqueeze(-1)
+    j_indices = j_indices.cumsum(1).unsqueeze(-1)
 
-    emb = torch.zeros(1, embed_height, embed_width, hidden_size // 2)
+    emb = torch.zeros(1, embed_height, embed_width, hidden_size // 2, dtype=inv_freq.dtype, device=inv_freq.device)
     emb[:, :, :, 0::2] = i_indices * inv_freq
     emb[:, :, :, 1::2] = j_indices * inv_freq