# glm53-dflash-01-aux-hidden-states.patch — give the GLM trunk the EAGLE3 / DFlash2 # auxiliary-hidden-state interface. # # STATUS: WIP, and INDEPENDENT of the compile changelist (01-05). It patches the same # file as glm53-compile-01-model-decorator.patch, so if both are ever applied, apply 01 # first. Not part of the deployed shape. # # WHY. `--speculative-config '{"method":"dflash","model":"/path/to/drafter", ...}'` with # incoai/GLM-5.3-Flash-DFlash2 is accepted -- the config parses, the drafter loads -- and # then the worker dies at init with: # # RuntimeError: Model does not support EAGLE3 interface # # raised by v1/worker/gpu/spec_decode/eagle/eagle3_utils.py:20 through # `supports_eagle3(model)` == `isinstance(model, SupportsEagle3)` (a runtime-checkable # Protocol). Nothing about the drafter, the method name or the payload is wrong: # `glm5next` implements neither half of the contract. # # THE CONTRACT (read out of this image, not assumed): # * interfaces.py:1663 -- `supports_eagle3: ClassVar[Literal[True]] = True`. THE FLAG # IS A REQUIRED MEMBER FOR `isinstance`: satisfying the Protocol with methods alone # still raises the same RuntimeError -- v1 of this patch did exactly that and the boot # failed identically. INHERIT the Protocol instead. That is the idiom in this image # (LagunaForCausalLM, MiMoV2FlashForCausalLM and DFlashLagunaForCausalLM all list # SupportsEagle3 among their bases) and it brings the flag, SupportsEagleBase's # has_own_lm_head/has_own_embed_tokens, AND working non-stub defaults for both methods. # * interfaces.py:1673-1719 -- the inherited defaults unwrap # `holder = getattr(parent_ref, "model", parent_ref)`, assert # `isinstance(holder, EagleModelMixin)`, set `holder._set_aux_hidden_state_layers`, and # default to (2, L // 2, L - 3). So the INNER trunk must inherit EagleModelMixin, # which supplies `aux_hidden_state_layers` and the slot helpers. # * eagle3_utils.py:26-31 -- layers come from the spec config when it carries them # (this drafter ships target_layer_ids [5, 14, 24, 33, 42]), else from the default. # * deepseek_v2.py:1551-1585 and v1/worker/gpu/cudagraph_utils.py:621 -- the trunk # appends one tensor per aux layer while looping and returns the TUPLE # (hidden_states, aux_hidden_states) only when that list is non-empty. # # WHAT IT ADDS for GLM: the mixin on Glm5NextModel; aux capture in the layer loop, where # the aux state is the single-stream `hidden_states` ENTERING that layer (GLM's loop # carries the already-summed single-stream state -- its non-mHC branch re-splits # `residual = hidden_states` inside the layer -- so this is the equivalent of # deepseek_v2's `hidden_states + residual`); the conditional tuple return; and # SupportsEagle3 among Glm5NextForCausalLM's bases. # # HONEST SCOPE: this makes the interface PRESENT, which is exactly what the engine # checks -- it does not make drafts GOOD, and per the measured profile it is not a # decode-speed fix (a verification pass pays pointwise cost proportional to its token # count, which is why MTP4 measured flat). It is the prerequisite for driving DFlash2 # on this endpoint at all. # # TARGET: vllm/models/glm5next/common/model.py (inside the pinned image) # base sha256 008eeaa2a07e091465319f86900b5a321d921238723ccbe22e6b9e971e1d2b28 # patched sha256 5eea89c51d4ab37ef823526286b5103e39996802ca08aa1934f6373fc4728062 # # APPLY: `patch -p1` from the vllm package root, or bind-mount the patched file over # site-packages (which is what a scratch-launcher DFLASH_PATCH=1 does). --- a/vllm/models/glm5next/common/model.py +++ b/vllm/models/glm5next/common/model.py @@ -95,6 +95,12 @@ logger = init_logger(__name__) +from vllm.model_executor.models.interfaces import ( + EagleModelMixin, + SupportsEagle3, +) + + class Glm5NextMLP(nn.Module): def __init__( self, @@ -623,7 +629,7 @@ ) -class Glm5NextModel(nn.Module): +class Glm5NextModel(nn.Module, EagleModelMixin): def __init__(self, *, vllm_config: VllmConfig, prefix: str = ""): super().__init__() @@ -730,7 +736,14 @@ if self.is_sequence_parallel: hidden_states = sp_shard(hidden_states) - for layer in self._active_layers: + aux_hidden_states: list[torch.Tensor] = [] + for local_idx, layer in enumerate(self._active_layers): + if (getattr(self, "start_layer", 0) + local_idx) in self.aux_hidden_state_layers: + # Auxiliary hidden state for EAGLE-3 / DFlash2 drafts: the + # single-stream state ENTERING this layer, before its input norm -- + # the same semantic deepseek_v2 implements by appending + # hidden_states + residual at this point in its loop. + aux_hidden_states.append(hidden_states) hidden_states, residual, post, comb = layer( positions, hidden_states, residual, post, comb ) @@ -749,6 +762,8 @@ hidden_states = sp_all_gather(hidden_states)[:full_num_tokens] hidden_states = self.norm(hidden_states) + if len(aux_hidden_states) > 0: + return hidden_states, aux_hidden_states return hidden_states def load_weights(self, weights: Iterable[tuple[str, torch.Tensor]]) -> set[str]: @@ -935,7 +950,12 @@ class Glm5NextForCausalLM( - nn.Module, HasInnerState, SupportsPP, MixtureOfExperts, IsHybrid + nn.Module, + HasInnerState, + SupportsPP, + MixtureOfExperts, + IsHybrid, + SupportsEagle3, ): def __init__(self, *, vllm_config: VllmConfig, prefix: str = ""): super().__init__()