[v1] Fix device mesh, fix lora for reward model and fix sp (#10555)

tests_v1/core/utils/test_batching.py

@@ -32,6 +32,7 @@ def _make_model_input(length: int, start: int = 0):
         "attention_mask": [1] * length,
         "labels": input_ids.copy(),
         "loss_weights": [1.0] * length,
+        "position_ids": list(range(1, length + 1)),
     }
 
 
@@ -62,7 +63,7 @@ def test_padding_free():
     assert len(batch) == 1
     assert batch[0]["input_ids"].shape == (1, 5)
     assert batch[0]["input_ids"].tolist() == [[0, 1, 10, 11, 12]]
-    assert batch[0]["attention_mask"].tolist() == [[1, 1, 1, 1, 1]]
+    assert batch[0]["attention_mask"] is None
     assert batch[0]["position_ids"].tolist() == [[0, 1, 0, 1, 2]]
     assert batch[0]["labels"].tolist() == [[0, 1, IGNORE_INDEX, 11, 12]]
     assert batch[0]["loss_weights"].tolist() == [[1.0, 1.0, 0.0, 1.0, 1.0]]
@@ -115,6 +116,8 @@ def test_dynamic_batching():
     assert len(batch) == 1
     assert batch[0]["input_ids"].shape == (3, 6)
     assert batch[0]["input_ids"].tolist()[0] == [0, 1, 2, 0, 0, 0]
+    assert batch[0]["position_ids"].shape == (3, 6)
+    assert batch[0]["position_ids"].tolist()[0] == [1, 2, 3, 0, 0, 0]
     assert len(buffer) == 3
 
 
@@ -201,6 +204,7 @@ def test_normal_batching():
     batch = next(iter(batch_generator))
     assert len(batch) == 2
     assert batch[0]["input_ids"].shape == (4, 10)
+    assert batch[0]["position_ids"].shape == (4, 10)
 
 
 def test_dynamic_padding_free():
@@ -280,8 +284,8 @@ def test_dynamic_padding_free():
         ]  # Sample 3
     ]
 
-    # Verify attention_mask
-    assert packed_batch["attention_mask"].tolist() == [[1] * 15]
+    # Verify attention_mask: padding-free relies on reset-style position_ids instead of a dense mask.
+    assert packed_batch["attention_mask"] is None
 
     # Verify position_ids
     assert packed_batch["position_ids"].tolist() == [