[BugFix][Spec Decode] Fix hidden size mismatch between target and eagle head (#17740)

Signed-off-by: Woosuk Kwon <woosuk.kwon@berkeley.edu>

vllm/v1/spec_decode/eagle.py

@@ -28,23 +28,25 @@ class EagleProposer:
         device: torch.device,
     ):
         self.vllm_config = vllm_config
-        self.method = self.vllm_config.speculative_config.method
-        self.num_speculative_tokens = (
-            vllm_config.speculative_config.num_speculative_tokens)
-        self.max_model_len = vllm_config.model_config.max_model_len
-        self.block_size = vllm_config.cache_config.block_size
+        self.speculative_config = vllm_config.speculative_config
+        self.draft_model_config = self.speculative_config.draft_model_config
+        self.method = self.speculative_config.method
 
         self.dtype = vllm_config.model_config.dtype
-
-        self.max_num_tokens = vllm_config.scheduler_config \
-            .max_num_batched_tokens
-
-        self.hidden_size = vllm_config.model_config.get_hidden_size()
+        self.max_model_len = vllm_config.model_config.max_model_len
+        self.block_size = vllm_config.cache_config.block_size
+        self.num_speculative_tokens = (
+            self.speculative_config.num_speculative_tokens)
+        self.max_num_tokens = (
+            vllm_config.scheduler_config.max_num_batched_tokens)
+        # We need to get the hidden size from the draft model config because
+        # the draft model's hidden size can be different from the target model's
+        # hidden size (e.g., Llama 3.3 70B).
+        self.hidden_size = self.draft_model_config.get_hidden_size()
 
         self.use_cuda_graph = (self.vllm_config.compilation_config.level
                                == CompilationLevel.PIECEWISE and
                                not self.vllm_config.model_config.enforce_eager)
-
         self.cudagraph_batch_sizes = list(
             reversed(
                 self.vllm_config.compilation_config.cudagraph_capture_sizes))
@@ -56,7 +58,6 @@ class EagleProposer:
         self.positions = torch.zeros(self.max_num_tokens,
                                      dtype=torch.int64,
                                      device=device)
-
         self.hidden_states = torch.zeros(
             (self.max_num_tokens, self.hidden_size),
             dtype=self.dtype,
@@ -131,7 +132,6 @@ class EagleProposer:
             num_input_tokens = num_tokens
         # copy inputs to buffer for cudagraph
         self.positions[:num_tokens] = target_positions
-
         self.hidden_states[:num_tokens] = target_hidden_states
 
         with set_forward_context(attn_metadata,
@@ -209,7 +209,6 @@ class EagleProposer:
             # copy inputs to buffer for cudagraph
             self.input_ids[:batch_size] = input_ids
             self.positions[:batch_size] = clamped_positions
-
             self.hidden_states[:batch_size] = hidden_states
 
             # Run the model.