[DP Attn] Fix crash for no token all-gather case

python/sglang/srt/layers/logits_processor.py

@@ -309,10 +309,15 @@ class LogitsMetadata:
 
     @classmethod
     def from_forward_batch(cls, forward_batch: ForwardBatch):
+        # MLP-sync may turn an idle rank into a dummy EXTEND for DP prefill
+        # graphs. It still has no real request whose last token needs logits.
+        forward_mode = forward_batch.forward_mode
+        if forward_batch._original_forward_mode == ForwardMode.IDLE:
+            forward_mode = ForwardMode.IDLE
         if (
-            forward_batch.forward_mode.is_extend()
+            forward_mode.is_extend()
             and forward_batch.return_logprob
-            and not forward_batch.forward_mode.is_target_verify()
+            and not forward_mode.is_target_verify()
         ):
             extend_return_top_logprob = any(
                 x > 0 for x in forward_batch.top_logprobs_nums
@@ -340,7 +345,7 @@ def from_forward_batch(cls, forward_batch: ForwardBatch):
             draft_extend_select_index = None
 
         return cls(
-            forward_mode=forward_batch.forward_mode,
+            forward_mode=forward_mode,
             capture_hidden_mode=forward_batch.capture_hidden_mode,
             next_token_logits_buffer=forward_batch.next_token_logits_buffer,
             extend_return_logprob=extend_return_logprob,

test/registered/unit/model_executor/test_mlp_sync_pad_unpad.py

@@ -15,6 +15,7 @@
 
 import torch
 
+from sglang.srt.layers.logits_processor import LogitsMetadata, LogitsProcessor
 from sglang.srt.model_executor.forward_batch_info import ForwardBatch, ForwardMode
 from sglang.srt.model_executor.runner.decode_cuda_graph_runner import (
     DecodeCudaGraphRunner,
@@ -40,6 +41,31 @@ def _logits_output(num_rows: int) -> SimpleNamespace:
 
 
 class TestMlpSyncPadUnpad(CustomTestCase):
+    def test_idle_rank_does_not_index_dummy_last_token(self):
+        # MLP-sync turns an idle rank into a dummy zero-token EXTEND batch.
+        empty = torch.empty(0, dtype=torch.int64)
+        batch = ForwardBatch(
+            forward_mode=ForwardMode.EXTEND,
+            batch_size=1,
+            input_ids=empty,
+            req_pool_indices=torch.tensor([0]),
+            seq_lens=torch.tensor([0]),
+            out_cache_loc=empty,
+            seq_lens_sum=0,
+            positions=empty,
+            extend_seq_lens=torch.tensor([0]),
+            extend_seq_lens_cpu=[0],
+            _original_forward_mode=ForwardMode.IDLE,
+            _original_batch_size=0,
+        )
+        hidden = torch.empty(0, 4)
+        pruned, *_ = LogitsProcessor._get_pruned_states(
+            None, hidden, None, None, LogitsMetadata.from_forward_batch(batch)
+        )
+        self.assertEqual(pruned.shape, (0, 4))
+        # Attention and MLP execution still use the padded mode.
+        self.assertEqual(batch.forward_mode, ForwardMode.EXTEND)
+
     def test_init_mlp_sync_metadata_scales_speculative_request_width(self):
         spec_info = SimpleNamespace(
             num_tokens_per_req=4,