[Speculators][Speculative Decoding] Add Qwen Eagle3 Support (#21835)

Signed-off-by: Dipika Sikka <dipikasikka1@gmail.com>

vllm/model_executor/models/qwen2.py

@@ -330,6 +330,8 @@ class Qwen2Model(nn.Module):
         else:
             self.norm = PPMissingLayer()
 
+        self.aux_hidden_state_layers: tuple[int] = tuple()
+
     def get_input_embeddings(self, input_ids: torch.Tensor) -> torch.Tensor:
         return self.embed_tokens(input_ids)
 
@@ -350,18 +352,25 @@ class Qwen2Model(nn.Module):
             assert intermediate_tensors is not None
             hidden_states = intermediate_tensors["hidden_states"]
             residual = intermediate_tensors["residual"]
-        for layer in self.layers[self.start_layer:self.end_layer]:
-            hidden_states, residual = layer(
-                positions,
-                hidden_states,
-                residual,
-            )
+
+        aux_hidden_states = []
+        for idx, layer in enumerate(
+                self.layers[self.start_layer:self.end_layer]):
+            if idx in self.aux_hidden_state_layers:
+                aux_hidden_states.append(hidden_states + residual)
+            hidden_states, residual = layer(positions, hidden_states, residual)
+
         if not get_pp_group().is_last_rank:
             return IntermediateTensors({
                 "hidden_states": hidden_states,
                 "residual": residual
             })
+
         hidden_states, _ = self.norm(hidden_states, residual)
+
+        if len(aux_hidden_states) > 0:
+            return hidden_states, aux_hidden_states
+
         return hidden_states
 
     def load_weights(self, weights: Iterable[tuple[str,