# SPDX-License-Identifier: Apache-2.0 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project """Fuser detection for the Transformers modeling backend. `get_fuser` traces a module class once (see `fx_utils`) and matches it against each concrete fuser in `fusers`; `Fusers` caches the result per class for a whole model. `base.recursive_replace` then applies the matched fuser per instance. RMSNorm-shaped modules the tracer cannot match are warned about. """ from collections import UserDict from typing import TYPE_CHECKING from cachetools import cached from torch import nn from vllm.logger import init_logger from vllm.model_executor.models.transformers.fusers import ( BaseFuser, GLUFuser, MLAFuser, PackedQKVFuser, QKVFuser, RewriteFuser, RMSNormFuser, ) from vllm.model_executor.models.transformers.fx_utils import trace if TYPE_CHECKING: from vllm.config import VllmConfig logger = init_logger(__name__) def key(module: nn.Module) -> tuple: """Cache key for `get_fuser`. Considers module type and its immediate children.""" return (type(module), tuple(name for name, _ in module.named_children())) @cached(cache={}, key=key) def get_fuser(module: nn.Module) -> BaseFuser | None: """The fuser for `module`'s class and shape (cached), or `None` if no match.""" # Projection fusions need >=2 sibling linears; the RMSNorm fusion needs a # leaf module (raw tensor math, no submodules). Nothing else can match, and # tracing is skipped for it. n_linear = sum(isinstance(c, nn.Linear) for c in module.children()) is_leaf = next(module.children(), None) is None if n_linear < 2 and not is_leaf: return None if (graph := trace(module)) is None: return None for fuser_cls in (MLAFuser, GLUFuser, QKVFuser, PackedQKVFuser, RMSNormFuser): if (fuser := fuser_cls.match(graph, module)) is not None: if isinstance(fuser, RewriteFuser): try: fuser.update_forward(module) except Exception as exc: logger.debug( "Attempted to fuse %s using %s but failed " "to update its forward method: %s", type(module), fuser_cls.__name__, exc, ) continue return fuser # A norm we could not match structurally is left unfused; flag likely misses. if module.__class__.__name__.endswith("RMSNorm"): logger.warning_once( "%s looks like an RMSNorm but its computation did not match the " "expected pattern, so it was left unfused.", module.__class__.__name__, ) return None class Fusers(UserDict): """Mapping from module class and shape to fuser, for all fusable modules.""" def __init__(self, model: nn.Module, vllm_config: "VllmConfig"): self.vllm_config = vllm_config super().__init__({key(m): get_fuser(m) for m in model.modules()}) def __getitem__(self, m: nn.Module) -> BaseFuser | None: fuser = self.data.get(key(m)) if fuser is not None and fuser.validate(m, self.vllm_config): return fuser return None