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[Bugfix][Model] Fix DualChunkRotaryEmbedding hard-coded cuda device crash - #52116

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[Bugfix][Model] Fix DualChunkRotaryEmbedding hard-coded cuda device crash#52116
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@danziheng1024 danziheng1024 commented Aug 13, 2026

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Purpose

DualChunkRotaryEmbedding.__init__ hard-codes self.device = torch.device(f"cuda:{device_idx}") alongside the portable torch.accelerator.current_device_index(). On any non-CUDA backend the subsequent .to(device=self.device) inside _compute_cos_sin_cache triggers CUDA lazy-init and crashes model loading with "Torch not compiled with CUDA enabled" for every Dual Chunk Attention model (e.g. Qwen2.5-*-1M).

Reproduced on Ascend NPU when serving Qwen2.5-7B-Instruct-1M:

(EngineCore) Starting to load model .../Qwen2.5-7B-Instruct-1M...
(EngineCore) EngineCore failed to start.
Traceback (most recent call last):
  File ".../vllm/v1/engine/core.py", line 1200, in run_engine_core
    engine_core = EngineCoreProc(*args, engine_index=dp_rank, **kwargs)
  File ".../vllm/v1/engine/core.py", line 123, in __init__
    self.model_executor = executor_class(vllm_config)
  File ".../vllm/v1/executor/uniproc_executor.py", line 68, in _init_executor
    self.driver_worker.load_model()
  File ".../vllm/model_executor/model_loader/__init__.py", line 140, in get_model
    return loader.load_model(...)
  File ".../vllm/model_executor/model_loader/utils.py", line 63, in initialize_model
    model = model_class(vllm_config=vllm_config, prefix=prefix)
  File ".../vllm/model_executor/models/qwen2.py", line 458, in __init__
    self.model = Qwen2Model(...)
  File ".../vllm/model_executor/models/qwen2.py", line 375, in __init__
    self.start_layer, self.end_layer, self.layers = make_layers(...)
  File ".../vllm/model_executor/models/utils.py", line 711, in make_layers
    + get_offloader().wrap_modules(...)
  File ".../vllm/model_executor/offloader/base.py", line 104, in wrap_modules
    return list(modules_generator)
  File ".../vllm/model_executor/models/qwen2.py", line 263, in __init__
    self.self_attn = Qwen2Attention(...)
  File ".../vllm/model_executor/models/qwen2.py", line 178, in __init__
    self.rotary_emb = get_rope(...)
  File ".../vllm/model_executor/layers/rotary_embedding/__init__.py", line 92, in get_rope
    rotary_emb = DualChunkRotaryEmbedding(...)
  File ".../vllm/model_executor/layers/rotary_embedding/dual_chunk_rope.py", line 42, in __init__
    self._compute_cos_sin_cache()
  File ".../vllm/model_executor/layers/rotary_embedding/dual_chunk_rope.py", line 105, in _compute_cos_sin_cache
    q_cache = torch.cat((q_cos, q_sin), dim=-1).to(...)
  File ".../torch/cuda/__init__.py", line 417, in _lazy_init
    raise AssertionError("Torch not compiled with CUDA enabled")
AssertionError: Torch not compiled with CUDA enabled

Fix: use current_platform.device_type instead of the "cuda" literal - the same portable pattern already used across vllm (config, compilation passes, other layers). The device index still comes from torch.accelerator.current_device_index(). No cache values change; only the device the cos/sin caches are placed on.

Test Plan

  • New unit test tests/model_executor/layers/test_dual_chunk_rope.py: 
    python -m pytest tests/model_executor/layers/test_dual_chunk_rope.py -v
  • E2E: vllm serve a Dual Chunk Attention model (e.g. Qwen2.5-7B-Instruct-1M) on a non-CUDA backend (Ascend NPU).

Test Result

Before (Ascend NPU): vllm serve Qwen2.5-7B-Instruct-1M crashes during model loading (traceback above), AssertionError: Torch not compiled with CUDA enabled.

After:

  • UT: 
    tests/model_executor/layers/test_dual_chunk_rope.py::test_device_follows_platform_type PASSED
tests/model_executor/layers/test_dual_chunk_rope.py::test_device_matches_real_platform PASSED
  • vllm serve Qwen2.5-7B-Instruct-1M on Ascend NPU starts and serves normally.
Essential Elements of an Effective PR Description Checklist
  • The purpose of the PR, such as "Fix some issue (link existing issues this PR will resolve)".
  • The test plan, such as providing test command.
  • The test results, such as pasting the results comparison before and after, or e2e results
  • (Optional) The necessary documentation update, such as updating supported_models.md and examples for a new model.

claude[bot]
claude Bot reviewed Aug 13, 2026
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This pull request is from a fork — automated review is disabled. A repository maintainer can comment @claude review to run a one-time review.

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@mergify mergify Bot added nvidia bug Something isn't working labels Aug 13, 2026
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