[Bug] [Spec Decode] Fix model_initialization test and mismatch in aux_hidden_layers

[wwl2755]

1. Fix the bug of model_initialization. The model should be initializated by a target model which is different from the speculative_model.

2. After changing to the correct target model, I faced another error which is because of the dfferent shape in hidden_states + residual

Root cause is the num_layers is initialized to 1 in the test (https://github.com/vllm-project/vllm/blob/v0.10.2rc1/tests/models/utils.py#L387). However, the aux_hidden_layer is determine as (2, num_layers // 2, num_layers - 3). (https://github.com/vllm-project/vllm/blob/v0.10.2rc1/tests/models/utils.py#L387)

# In the test: 
DEBUG: self.aux_hidden_state_layers: (2, 0, -2)

# It is supposed to be:
DEBUG: self.aux_hidden_state_layers: (2, 20, 37)

So, before this PR, it will treat the layer-0 as the aux-layer and entering the code path of hidden_states + residual (where hidden_states is a tensor and residual is None).

Solution: we set some of the eagle3 models to have the original number of layers.

cc: @DarkLight1337 @WoosukKwon @LiuXiaoxuanPKU @22quinn @benchislett

Tests

All passed.

VLLM_WORKER_MULTIPROC_METHOD=spawn pytest -v -s models/test_initialization.py::test_can_initialize[EagleLlamaForCausalLM]
VLLM_WORKER_MULTIPROC_METHOD=spawn pytest -v -s models/test_initialization.py::test_can_initialize[Eagle3LlamaForCausalLM]
VLLM_WORKER_MULTIPROC_METHOD=spawn pytest -v -s models/test_initialization.py::test_can_initialize[LlamaForCausalLMEagle3]

python $HOME/vllm/examples/offline_inference/spec_decode.py --method eagle3 --num-prompts 10 --model-dir Qwen/Qwen3-14B --eagle-dir AngelSlim/Qwen3-14B_eagle3

[gemini-code-assist]

Code Review

This pull request effectively addresses two bugs related to speculative decoding tests. First, it corrects the model initialization to use the proper target model instead of the speculative model. Second, it resolves a shape mismatch for aux_hidden_layers by introducing a mechanism to use the original number of layers from the model config during testing. The changes are logical and well-implemented. I have one suggestion to improve the robustness of how the layer count is determined in the test utilities.

[gemini-code-assist]

This logic for determining num_layers and num_hidden_layers can be fragile. If a model config only defines num_hidden_layers (which is common for many models like Llama and Qwen), num_layers will default to 1. This could lead to issues if other parts of the code rely on config.num_layers. A more robust approach would be to fetch the layer count from either attribute and ensure both num_layers and num_hidden_layers are consistent.

Suggested change

	num_layers = getattr(text_config, 'num_layers', 1)
	num_hidden_layers = getattr(text_config, 'num_hidden_layers', 1)
	num_layers = getattr(text_config, "num_hidden_layers", getattr(text_config, "num_layers", 1))
	num_hidden_layers = num_layers

[ywang96]

@wwl2755 If I understand correctly - this is just to fix our CI setup right?

[ywang96]

I turned on ready label to see if it fixes the issue.

[wwl2755]

@wwl2755 If I understand correctly - this is just to fix our CI setup right?

Yes. It enables some tests to used the original num_layers instead of 1.

All the modification is under /tests. And there will be no any new commit coming unless requested in comment.