Fix top_k_top_p_filtering having unexpected behavior (#17744)

- Fix `top_k_top_p_filtering` not passing `filter_value` to
   `TopPLogitsWarper` causing any top-p filtered logits to be -inf
   instead of specified value

 - Add corresponding test

src/transformers/generation_utils.py

@@ -3347,6 +3347,8 @@ def top_k_top_p_filtering(
         )
 
     if 0 <= top_p <= 1.0:
-        logits = TopPLogitsWarper(top_p=top_p, min_tokens_to_keep=min_tokens_to_keep)(None, logits)
+        logits = TopPLogitsWarper(top_p=top_p, filter_value=filter_value, min_tokens_to_keep=min_tokens_to_keep)(
+            None, logits
+        )
 
     return logits

tests/generation/test_generation_utils.py

@@ -1626,6 +1626,32 @@ class UtilsFunctionsTest(unittest.TestCase):
         self.assertTrue(torch.allclose(non_inf_expected_output, non_inf_output, atol=1e-12))
         self.assertTrue(torch.all(torch.eq(non_inf_expected_idx, non_inf_idx)))
 
+    # tests whether the function uses filter_value instead of default -inf
+    def test_top_k_top_p_filtering_with_filter_value(self):
+        logits = torch.tensor(
+            [
+                [
+                    1,
+                    1,
+                    1,
+                    0.99,  # get filtered by top-p filtering
+                    0.98,  # get filtered by top-k filtering
+                ]
+            ],
+            dtype=torch.float,
+            device=torch_device,
+        )
+
+        expected_output = torch.tensor(
+            [[1, 1, 1, 0, 0]],
+            dtype=torch.float,
+            device=torch_device,
+        )
+
+        output = top_k_top_p_filtering(logits, top_k=4, top_p=0.5, filter_value=0.0)
+
+        self.assertTrue(torch.allclose(expected_output, output, atol=1e-12))
+
 
 @require_torch
 class GenerationIntegrationTests(unittest.TestCase):