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[Model] Officially support Emu3 with Transformers backend (#21319)

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Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
This commit is contained in:
Harry Mellor
2025-07-24 11:22:12 +01:00
committed by GitHub
parent 61b8cea3b4
commit 13abd0eaf9
5 changed files with 29 additions and 14 deletions
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17
tests/models/multimodal/test_mapping.py
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@@ -23,18 +23,14 @@ def create_repo_dummy_weights(repo: str) -> Iterable[tuple[str, torch.Tensor]]:
return ((name, torch.empty(0)) for name in weight_names)
def create_model_dummy_weights(
repo: str,
model_arch: str,
) -> Iterable[tuple[str, torch.Tensor]]:
def create_dummy_model(repo: str, model_arch: str) -> PreTrainedModel:
"""
Create weights from a dummy meta deserialized hf model with name conversion
"""
model_cls: PreTrainedModel = getattr(transformers, model_arch)
config = AutoConfig.from_pretrained(repo)
with torch.device("meta"):
model: PreTrainedModel = model_cls._from_config(config)
return model.named_parameters()
return model_cls._from_config(config)
def model_architectures_for_test() -> list[str]:
@@ -70,14 +66,21 @@ def test_hf_model_weights_mapper(model_arch: str):
model_cls = MULTIMODAL_REGISTRY._get_model_cls(model_config)
original_weights = create_repo_dummy_weights(model_id)
hf_converted_weights = create_model_dummy_weights(model_id, model_arch)
hf_dummy_model = create_dummy_model(model_id, model_arch)
hf_converted_weights = hf_dummy_model.named_parameters()
hf_converted_buffers = hf_dummy_model.named_buffers()
mapper: WeightsMapper = model_cls.hf_to_vllm_mapper
mapped_original_weights = mapper.apply(original_weights)
mapped_hf_converted_weights = mapper.apply(hf_converted_weights)
mapped_hf_converted_buffers = mapper.apply(hf_converted_buffers)
ref_weight_names = set(map(lambda x: x[0], mapped_original_weights))
weight_names = set(map(lambda x: x[0], mapped_hf_converted_weights))
buffer_names = set(map(lambda x: x[0], mapped_hf_converted_buffers))
# Some checkpoints may have buffers, we ignore them for this test
ref_weight_names -= buffer_names
weights_missing = ref_weight_names - weight_names
weights_unmapped = weight_names - ref_weight_names