[Optimization][DeepSeekV3.2]Reducing slot_mapping compute frequency from twice per layer to a single pre-processing step. (#7367)

tests/distributed/chunked_moe.py

@@ -85,6 +85,7 @@ class MockFDConfig:
         name = "default"
         splitwise_role = "mixed"
         max_num_seqs = 2
+        max_num_batched_tokens = 2048
 
     parallel_config = ParallelConfig()
     scheduler_config = SchedulerConfig()

tests/operators/test_get_position_ids_and_mask_encoder_batch.py

@@ -33,24 +33,17 @@ class TestGetPositionIdsAndMaskEncoderBatch(unittest.TestCase):
 
         total_len = int(seq_lens_encoder.numpy().sum() + seq_lens_this_time.numpy().sum())
         position_ids = paddle.zeros([total_len], dtype="int32")
-        mask_encoder_batch = paddle.zeros([total_len], dtype="int32")
 
         # Call the custom operator
-        get_position_ids_and_mask_encoder_batch(
-            seq_lens_encoder, seq_lens_decoder, seq_lens_this_time, position_ids, mask_encoder_batch
-        )
+        get_position_ids_and_mask_encoder_batch(seq_lens_encoder, seq_lens_decoder, seq_lens_this_time, position_ids)
 
         expected_position_ids = np.array([0, 1, 2, 1, 0, 1, 2, 3], dtype=np.int32)
 
-        expected_mask = np.array([1, 1, 1, 0, 1, 1, 0, 0], dtype=np.int32)
-
         # Convert to numpy for comparison
         position_ids_np = position_ids.numpy()
-        mask_encoder_batch_np = mask_encoder_batch.numpy()
 
         # Assert equality
         np.testing.assert_array_equal(position_ids_np, expected_position_ids)
-        np.testing.assert_array_equal(mask_encoder_batch_np, expected_mask)
 
     def test_empty_decoder(self):
         # Test case where decoder length is 0
@@ -59,17 +52,12 @@ class TestGetPositionIdsAndMaskEncoderBatch(unittest.TestCase):
         seq_lens_this_time = paddle.to_tensor([0], dtype="int32")
 
         position_ids = paddle.zeros([2], dtype="int32")
-        mask_encoder_batch = paddle.zeros([2], dtype="int32")
 
-        get_position_ids_and_mask_encoder_batch(
-            seq_lens_encoder, seq_lens_decoder, seq_lens_this_time, position_ids, mask_encoder_batch
-        )
+        get_position_ids_and_mask_encoder_batch(seq_lens_encoder, seq_lens_decoder, seq_lens_this_time, position_ids)
 
         expected_position_ids = np.array([0, 1], dtype=np.int32)
-        expected_mask = np.array([1, 1], dtype=np.int32)
 
         np.testing.assert_array_equal(position_ids.numpy(), expected_position_ids)
-        np.testing.assert_array_equal(mask_encoder_batch.numpy(), expected_mask)
 
 
 if __name__ == "__main__":

tests/worker/test_reorder_split_prefill_and_decode.py

@@ -59,6 +59,7 @@ def create_mock_config():
 
     scheduler_config = Mock(spec=SchedulerConfig)
     scheduler_config.max_num_seqs = 10
+    scheduler_config.max_num_batched_tokens = 2048
 
     speculative_config = Mock(spec=SpeculativeConfig)
     speculative_config.method = None