Purpose

• Fix compile pass unit test CI stability by making the ModelConfig used in these tests explicit and hermetic.
• failure CI: buildkite/ci/pytorch-compilation-passes-unit-tests
  • https://buildkite.com/vllm/ci/builds/65291/canvas?jid=019e0a61-eb13-45e8-a45f-e2334f989865&tab=output

Error message

[2026-05-09T02:23:49Z] FAILED compile/passes/test_qk_norm_rope_fusion.py::test_qk_norm_rope_fusion[dtype0-True-True-True-1e-06-False] - pydantic_core._pydantic_core.ValidationError: 1 validation error for ModelConfig
[2026-05-09T02:23:49Z]   Value error, Unrecognized model in Qwen/Qwen3-0.6B. Should have a `model_type` key in its config.json. [type=value_error, input_value=ArgsKwargs((), {'dtype': torch.bfloat16}), input_type=ArgsKwargs]
[2026-05-09T02:23:49Z]     For further information visit https://errors.pydantic.dev/2.12/v/value_error

Root Cause

Some compile pass tests only need model metadata for hand-written test modules, but ModelConfig(dtype=dtype) silently falls back to the default Hugging Face model (Qwen/Qwen3-0.6B). That makes the tests depend on implicit HF config / tokenizer behavior even though they are not testing model loading.

Code Change

• Add local compile-test model metadata fixtures for Qwen3 and Llama.
• Use the Qwen3 fixture for non-distributed compile tests that only need generic
  ModelConfig metadata.
• Use the Llama fixture for distributed compile tests that previously used
  RedHatAI/Llama-3.2-1B-Instruct-FP8 only as fake metadata.
• Skip tokenizer initialization so these tests do not depend on HF downloads,
  tokenizer files, or ModelConfig defaults.

Test Plan

python -m pytest -q \
  tests/compile/passes/test_qk_norm_rope_fusion.py \
  tests/compile/passes/test_functionalization.py \
  tests/compile/passes/test_fusion.py \
  tests/compile/passes/test_pass_manager.py \
  tests/compile/test_rotary_embedding_compile.py \
  --tb=short --disable-warnings

Test Result