[Bugfix] Resolve MTP > 1 issue when lm head tp > 1

Previously, the dummy run executed compute_logits only once, regardless of num_speculative_tokens. This caused execute_model to hang on compute_logits when lm head tensor parallelism exceeded 1. The fix ensures compute_logits executes correctly during dummy run, matching num_speculative_tokens.

Signed-off-by: Jade Zheng <[email protected]>

Author: jianzs

vllm_ascend/spec_decode/eagle_proposer.py

@@ -136,7 +136,8 @@ def dummy_run(self,
                   num_reqs: int = 0,
                   num_tokens_across_dp: Optional[torch.Tensor] = None,
                   aclgraph_runtime_mode: CUDAGraphMode = CUDAGraphMode.NONE,
-                  batch_descriptor=None):
+                  batch_descriptor=None,
+                  dummy_compute_logits=lambda hidden_states: None):
         moe_comm_type = self.runner._select_moe_comm_method(
             num_tokens, with_prefill)
         with set_ascend_forward_context(None,
@@ -148,6 +149,7 @@ def dummy_run(self,
                 positions=self.positions[:num_tokens],
                 hidden_states=self.hidden_states[:num_tokens],
             )
+            dummy_compute_logits(self.hidden_states)
 
     def generate_token_ids(self,
                            valid_sampled_token_ids: list[list[int]],

vllm_ascend/spec_decode/mtp_proposer.py

@@ -232,7 +232,8 @@ def dummy_run(self,
                   num_reqs: int = 0,
                   num_tokens_across_dp=None,
                   aclgraph_runtime_mode: CUDAGraphMode = CUDAGraphMode.NONE,
-                  batch_descriptor=None) -> None:
+                  batch_descriptor=None,
+                  dummy_compute_logits=lambda hidden_states: None) -> None:
 
         (
             num_tokens,
@@ -316,6 +317,7 @@ def dummy_run(self,
                             self.update_stream, forward_context,
                             positions.shape[0],
                             self.vllm_config.speculative_config)
+                dummy_compute_logits(previous_hidden_states)
             if with_prefill:
                 break
 
@@ -775,6 +777,7 @@ def _propose(
             logits = self.model.compute_logits(sample_hidden_states)
             if lmhead_tp_enable() and num_indices < logits.shape[0]:
                 logits = logits[:num_indices]
+                last_token_indices = last_token_indices[:num_indices]
             draft_token_ids = logits.argmax(dim=-1)
 
             if self.num_speculative_tokens == 1:
@@ -840,7 +843,7 @@ def _propose(
             # For the requests that exceed the max model length, we set the
             # sequence length to 1 to minimize their overheads in attention.
             exceeds_max_model_len_cpu = exceeds_max_model_len.to(
-                attn_metadata_i.seq_lens.device, non_blocking=True)
+                attn_metadata_i.seq_lens.device, non_blocking=False)
             attn_metadata_i.seq_lens[:batch_size].masked_fill_(
                 exceeds_max_model_len_cpu, 1)
             # Mask out the slot mappings that exceed the max model length.

vllm_ascend/worker/model_runner_v1.py

@@ -3086,6 +3086,14 @@ def dummy_compute_logits(hidden_states):
                     return self.model.compute_logits(
                         hidden_states[dummy_indices])
 
+                def dummy_drafter_compute_logits(hidden_states):
+                    return self.drafter.compute_logits(
+                        hidden_states[dummy_indices])
+
+            else:
+                dummy_compute_logits = lambda hidden_states: None
+                dummy_drafter_compute_logits = lambda hidden_states: None
+
             with set_ascend_forward_context(
                     attn_metadata,
                     self.vllm_config,
@@ -3105,8 +3113,7 @@ def dummy_compute_logits(hidden_states):
                     with_prefill, is_torchair_compile, input_ids, positions,
                     attn_metadata, num_tokens, intermediate_tensors,
                     inputs_embeds)
-                if need_dummy_logits:
-                    dummy_compute_logits(hidden_states)
+                dummy_compute_logits(hidden_states)
 
             if self.drafter:
                 self.drafter.dummy_run(
@@ -3115,10 +3122,8 @@ def dummy_compute_logits(hidden_states):
                     num_reqs=num_reqs,
                     num_tokens_across_dp=num_tokens_across_dp,
                     aclgraph_runtime_mode=aclgraph_runtime_mode,
-                    batch_descriptor=batch_descriptor)
-                if need_dummy_logits:
-                    self.drafter.model.compute_logits(
-                        hidden_states[dummy_indices])
+                    batch_descriptor=batch_descriptor,
+                    dummy_compute_logits=dummy_drafter_compute_logits)
             if self.in_profile_run and self.dynamic_eplb:
                 self.model.clear_all_moe_loads()
             if not self.in_profile_run and self.dynamic_eplb: