Enable Eagle3 speculative decoding for Pixtral (LlavaForConditionalGeneration) (#32542)

Signed-off-by: gopalsarda <gopal.sarda@servicenow.com>

vllm/model_executor/models/llava.py

@@ -53,6 +53,7 @@ from vllm.utils.tensor_schema import TensorSchema, TensorShape
 from .clip import CLIPVisionModel
 from .interfaces import (
     MultiModalEmbeddings,
+    SupportsEagle3,
     SupportsLoRA,
     SupportsMultiModal,
     SupportsPP,
@@ -503,7 +504,7 @@ def init_vision_tower_for_llava(
     dummy_inputs=LlavaDummyInputsBuilder,
 )
 class LlavaForConditionalGeneration(
-    nn.Module, SupportsLoRA, SupportsMultiModal, SupportsPP
+    nn.Module, SupportsLoRA, SupportsMultiModal, SupportsPP, SupportsEagle3
 ):
     packed_modules_mapping = {
         "qkv_proj": ["q_proj", "k_proj", "v_proj"],
@@ -527,6 +528,13 @@ class LlavaForConditionalGeneration(
 
         raise ValueError("Only image modality is supported")
 
+    def set_aux_hidden_state_layers(self, layers: tuple[int, ...]) -> None:
+        self.get_language_model().model.aux_hidden_state_layers = layers
+
+    def get_eagle3_aux_hidden_state_layers(self) -> tuple[int, ...]:
+        num_layers = len(self.get_language_model().model.layers)
+        return (2, num_layers // 2, num_layers - 3)
+
     def __init__(self, *, vllm_config: VllmConfig, prefix: str = "") -> None:
         super().__init__()