Fix: unfinished_sequences with correct device (#22184)

Fix: unfinished_sequences with correct device 

The original code was causing errors when running torch.jit.trace due to the tensor options being incorrect. I fixed this by using torch.ones to create a tensor with the correct device and dtype. This should resolve the issue with running torch.jit.trace.

src/transformers/generation/utils.py

@@ -1805,7 +1805,7 @@ class GenerationMixin:
             )
 
         # keep track of which sequences are already finished
-        unfinished_sequences = input_ids.new(input_ids.shape[0]).fill_(1)
+        unfinished_sequences = torch.ones(input_ids.shape[0], dtype=torch.long, device=input_ids.device)
 
         this_peer_finished = False  # used by synced_gpus only
         batch_size = input_ids.shape[0]
@@ -2180,7 +2180,7 @@ class GenerationMixin:
             )
 
         # keep track of which sequences are already finished
-        unfinished_sequences = input_ids.new(input_ids.shape[0]).fill_(1)
+        unfinished_sequences = torch.ones(input_ids.shape[0], dtype=torch.long, device=input_ids.device)
 
         this_peer_finished = False  # used by synced_gpus only
         while True:
@@ -2446,7 +2446,7 @@ class GenerationMixin:
             )
 
         # keep track of which sequences are already finished
-        unfinished_sequences = input_ids.new(input_ids.shape[0]).fill_(1)
+        unfinished_sequences = torch.ones(input_ids.shape[0], dtype=torch.long, device=input_ids.device)
 
         this_peer_finished = False  # used by synced_gpus only
         # auto-regressive generation