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[Bugfix] fix composite weight loading and EAGLE weight loading (#9160)

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Cyrus Leung
2024-10-09 15:36:55 +08:00
committed by GitHub
parent 0b5b5d767e
commit 8bfaa4e31e
15 changed files with 241 additions and 361 deletions
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23
vllm/model_executor/models/llava.py
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@@ -13,7 +13,6 @@ from vllm.inputs import INPUT_REGISTRY, InputContext, LLMInputs
from vllm.model_executor.layers.activation import get_act_fn
from vllm.model_executor.layers.quantization import QuantizationConfig
from vllm.model_executor.layers.sampler import Sampler, SamplerOutput
from vllm.model_executor.model_loader.weight_utils import default_weight_loader
from vllm.model_executor.sampling_metadata import SamplingMetadata
from vllm.multimodal import MULTIMODAL_REGISTRY
from vllm.sequence import IntermediateTensors
@@ -26,8 +25,8 @@ from .interfaces import SupportsMultiModal, SupportsPP
from .siglip import (SiglipVisionModel, dummy_image_for_siglip,
dummy_seq_data_for_siglip, get_max_siglip_image_tokens,
input_processor_for_siglip)
from .utils import (flatten_bn, group_weights_with_prefix,
init_vllm_registered_model, merge_multimodal_embeddings)
from .utils import (AutoWeightsLoader, flatten_bn, init_vllm_registered_model,
merge_multimodal_embeddings)
class LlavaImagePixelInputs(TypedDict):
@@ -406,19 +405,5 @@ class LlavaForConditionalGeneration(nn.Module, SupportsMultiModal, SupportsPP):
return self.language_model.sample(logits, sampling_metadata)
def load_weights(self, weights: Iterable[Tuple[str, torch.Tensor]]):
# prepare weight iterators for components
weights_group = group_weights_with_prefix(weights)
# load vision encoder
self.vision_tower.load_weights(weights_group["vision_tower"])
# load mlp projector
mlp_params_dict = dict(self.multi_modal_projector.named_parameters())
for name, loaded_weight in weights_group["multi_modal_projector"]:
param = mlp_params_dict[name]
weight_loader = getattr(param, "weight_loader",
default_weight_loader)
weight_loader(param, loaded_weight)
# load llm backbone
self.language_model.load_weights(weights_group["language_model"])
loader = AutoWeightsLoader(self)
loader.load_weights(weights)