Enable Eagle3 speculative decoding for Mistral3ForConditionalGeneration to support eagle3 (#33939)

Signed-off-by: Akintunde Oladipo <akintunde.oladipo@servicenow.com>
Signed-off-by: TundeAtSN <akintunde.oladipo@servicenow.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
This commit is contained in:
TundeAtSN
2026-02-07 08:24:52 -05:00
committed by GitHub
parent 81fe69cae5
commit 4df44c16ba

View File

@@ -44,6 +44,7 @@ from vllm.utils.tensor_schema import TensorSchema, TensorShape
from .interfaces import (
MultiModalEmbeddings,
SupportsEagle3,
SupportsLoRA,
SupportsMultiModal,
SupportsPP,
@@ -408,7 +409,7 @@ def init_vision_tower_for_llava(
dummy_inputs=Mistral3DummyInputsBuilder,
)
class Mistral3ForConditionalGeneration(
nn.Module, SupportsLoRA, SupportsMultiModal, SupportsPP
nn.Module, SupportsLoRA, SupportsMultiModal, SupportsPP, SupportsEagle3
):
packed_modules_mapping = {
"qkv_proj": ["q_proj", "k_proj", "v_proj"],
@@ -432,6 +433,13 @@ class Mistral3ForConditionalGeneration(
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__()