[Bug] 'disaggregation_mode' is missing in warmup function when compile deep_gemm

### Checklist

- [x] 1. I have searched related issues but cannot get the expected help.
- [x] 2. The bug has not been fixed in the latest version.
- [x] 3. Please note that if the bug-related issue you submitted lacks corresponding environment info and a minimal reproducible demo, it will be challenging for us to reproduce and resolve the issue, reducing the likelihood of receiving feedback.
- [x] 4. If the issue you raised is not a bug but a question, please raise a discussion at https://github.com/sgl-project/sglang/discussions/new/choose Otherwise, it will be closed.
- [x] 5. Please use English, otherwise it will be closed.

### Describe the bug

I tried to compile deep_gemm with this command:
```bash
python -m sglang.compile_deep_gemm --model-path /ssd1/models/huggingface.co/deepseek-ai/DeepSeek-R1 --enable-deepep-moe --trust-remote-code --tp-size 8
```

Then the following error occurred:
```bash
[2025-07-31 20:37:23 TP0] Load weight end. type=DeepseekV3ForCausalLM, dtype=torch.bfloat16, avail mem=56.21 GB, mem usage=81.74 GB.
[2025-07-31 20:37:24 TP0] KV Cache is allocated. #tokens: 542023, KV size: 35.47 GB
[2025-07-31 20:37:24 TP7] KV Cache is allocated. #tokens: 542023, KV size: 35.47 GB
[2025-07-31 20:37:24 TP5] KV Cache is allocated. #tokens: 542023, KV size: 35.47 GB
[2025-07-31 20:37:24 TP2] KV Cache is allocated. #tokens: 542023, KV size: 35.47 GB
[2025-07-31 20:37:24 TP4] KV Cache is allocated. #tokens: 542023, KV size: 35.47 GB
[2025-07-31 20:37:24 TP0] Memory pool end. avail mem=19.43 GB
[2025-07-31 20:37:24 TP3] KV Cache is allocated. #tokens: 542023, KV size: 35.47 GB
[2025-07-31 20:37:24 TP1] KV Cache is allocated. #tokens: 542023, KV size: 35.47 GB
[2025-07-31 20:37:25 TP6] KV Cache is allocated. #tokens: 542023, KV size: 35.47 GB
[2025-07-31 20:37:25 TP0] max_total_num_tokens=542023, chunked_prefill_size=8192, max_prefill_tokens=16384, max_running_requests=2048, context_len=163840, available_gpu_mem=19.34 GB
[2025-07-31 20:37:25] INFO:     Started server process [1497]
[2025-07-31 20:37:25] INFO:     Waiting for application startup.
[2025-07-31 20:37:25] Running warmup compile-deep-gemm
[2025-07-31 20:37:25] ERROR:    Traceback (most recent call last):
  File "/root/paddlejob/venv/lib/python3.12/site-packages/starlette/routing.py", line 694, in lifespan
    async with self.lifespan_context(app) as maybe_state:
  File "/usr/lib/python3.12/contextlib.py", line 210, in __aenter__
    return await anext(self.gen)
           ^^^^^^^^^^^^^^^^^^^^^
  File "/tmp/src/python/sglang/srt/entrypoints/http_server.py", line 148, in lifespan
    await execute_warmups(
  File "/tmp/src/python/sglang/srt/warmup.py", line 34, in execute_warmups
    await _warmup_registry[warmup_name](disaggregation_mode, tokenizer_manager)
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: warm_up_compile() takes 1 positional argument but 2 were given

[2025-07-31 20:37:25] ERROR:    Application startup failed. Exiting.
```

Currently, in `compile_deep_gemm.py`, the warmup function is defined as follows, which provided only 1 args.
```python
@warmup("compile-deep-gemm")
async def warm_up_compile(tokenizer_manager: TokenizerManager):
    ...
```
But when it was called in `execute_warmups`, two args was passed, maybe the `disaggregation_mode` is missing?
```python
async def execute_warmups(
    disaggregation_mode: str,
    warmup_names: List[str],
    tokenizer_manager: TokenizerManager,
):
    for warmup_name in warmup_names:
        if warmup_name not in _warmup_registry:
            logger.warning(f"Could not find custom warmup {warmup_name}")
            continue
        logger.info(f"Running warmup {warmup_name}")
        await _warmup_registry[warmup_name](disaggregation_mode, tokenizer_manager)
```

### Reproduction

```bash
python -m sglang.compile_deep_gemm --model-path /ssd1/models/huggingface.co/deepseek-ai/DeepSeek-R1 --enable-deepep-moe --trust-remote-code --tp-size 8
```

### Environment

```bash
Python: 3.12.3 (main, May 26 2025, 18:50:19) [GCC 13.3.0]
CUDA available: True
GPU 0,1,2,3,4,5,6,7: NVIDIA H800
GPU 0,1,2,3,4,5,6,7 Compute Capability: 9.0
CUDA_HOME: /usr/local/cuda
NVCC: Cuda compilation tools, release 12.6, V12.6.85
CUDA Driver Version: 550.127.08
PyTorch: 2.7.1+cu126
sglang: 0.4.9.post6
sgl_kernel: 0.2.7
flashinfer_python: 0.2.7
triton: 3.3.1
transformers: 4.53.0
torchao: 0.9.0
numpy: 2.3.2
aiohttp: 3.12.15
fastapi: 0.116.1
hf_transfer: 0.1.9
huggingface_hub: 0.34.3
interegular: 0.3.3
modelscope: 1.28.1
orjson: 3.11.1
outlines: 0.1.11
packaging: 25.0
psutil: 7.0.0
pydantic: 2.11.7
python-multipart: 0.0.20
pyzmq: 27.0.0
uvicorn: 0.35.0
uvloop: 0.21.0
vllm: Module Not Found
xgrammar: 0.1.19
openai: Module Not Found
tiktoken: 0.9.0
anthropic: Module Not Found
litellm: Module Not Found
decord: Module Not Found
NVIDIA Topology:
	GPU0	GPU1	GPU2	GPU3	GPU4	GPU5	GPU6	GPU7	NIC0	NIC1	NIC2	NIC3	NIC4	NIC5	NIC6	NIC7	NIC8	CPU Affinity	NUMA Affinity	GPU NUMA ID
GPU0	 X 	NV18	NV18	NV18	NV18	NV18	NV18	NV18	PIX	NODE	NODE	NODE	SYS	SYS	SYS	SYS	NODE	0-47,96-143	0		N/A
GPU1	NV18	 X 	NV18	NV18	NV18	NV18	NV18	NV18	NODE	PIX	NODE	NODE	SYS	SYS	SYS	SYS	NODE	0-47,96-143	0		N/A
GPU2	NV18	NV18	 X 	NV18	NV18	NV18	NV18	NV18	NODE	NODE	PIX	NODE	SYS	SYS	SYS	SYS	NODE	0-47,96-143	0		N/A
GPU3	NV18	NV18	NV18	 X 	NV18	NV18	NV18	NV18	NODE	NODE	NODE	PIX	SYS	SYS	SYS	SYS	NODE	0-47,96-143	0		N/A
GPU4	NV18	NV18	NV18	NV18	 X 	NV18	NV18	NV18	SYS	SYS	SYS	SYS	PIX	NODE	NODE	NODE	SYS	48-95,144-191	1		N/A
GPU5	NV18	NV18	NV18	NV18	NV18	 X 	NV18	NV18	SYS	SYS	SYS	SYS	NODE	PIX	NODE	NODE	SYS	48-95,144-191	1		N/A
GPU6	NV18	NV18	NV18	NV18	NV18	NV18	 X 	NV18	SYS	SYS	SYS	SYS	NODE	NODE	PIX	NODE	SYS	48-95,144-191	1		N/A
GPU7	NV18	NV18	NV18	NV18	NV18	NV18	NV18	 X 	SYS	SYS	SYS	SYS	NODE	NODE	NODE	PIX	SYS	48-95,144-191	1		N/A
NIC0	PIX	NODE	NODE	NODE	SYS	SYS	SYS	SYS	 X 	NODE	NODE	NODE	SYS	SYS	SYS	SYS	NODE
NIC1	NODE	PIX	NODE	NODE	SYS	SYS	SYS	SYS	NODE	 X 	NODE	NODE	SYS	SYS	SYS	SYS	NODE
NIC2	NODE	NODE	PIX	NODE	SYS	SYS	SYS	SYS	NODE	NODE	 X 	NODE	SYS	SYS	SYS	SYS	NODE
NIC3	NODE	NODE	NODE	PIX	SYS	SYS	SYS	SYS	NODE	NODE	NODE	 X 	SYS	SYS	SYS	SYS	NODE
NIC4	SYS	SYS	SYS	SYS	PIX	NODE	NODE	NODE	SYS	SYS	SYS	SYS	 X 	NODE	NODE	NODE	SYS
NIC5	SYS	SYS	SYS	SYS	NODE	PIX	NODE	NODE	SYS	SYS	SYS	SYS	NODE	 X 	NODE	NODE	SYS
NIC6	SYS	SYS	SYS	SYS	NODE	NODE	PIX	NODE	SYS	SYS	SYS	SYS	NODE	NODE	 X 	NODE	SYS
NIC7	SYS	SYS	SYS	SYS	NODE	NODE	NODE	PIX	SYS	SYS	SYS	SYS	NODE	NODE	NODE	 X 	SYS
NIC8	NODE	NODE	NODE	NODE	SYS	SYS	SYS	SYS	NODE	NODE	NODE	NODE	SYS	SYS	SYS	SYS	 X

Legend:

  X    = Self
  SYS  = Connection traversing PCIe as well as the SMP interconnect between NUMA nodes (e.g., QPI/UPI)
  NODE = Connection traversing PCIe as well as the interconnect between PCIe Host Bridges within a NUMA node
  PHB  = Connection traversing PCIe as well as a PCIe Host Bridge (typically the CPU)
  PXB  = Connection traversing multiple PCIe bridges (without traversing the PCIe Host Bridge)
  PIX  = Connection traversing at most a single PCIe bridge
  NV#  = Connection traversing a bonded set of # NVLinks

NIC Legend:

  NIC0: mlx5_0
  NIC1: mlx5_3
  NIC2: mlx5_4
  NIC3: mlx5_5
  NIC4: mlx5_6
  NIC5: mlx5_7
  NIC6: mlx5_8
  NIC7: mlx5_9
  NIC8: mlx5_bond_0


ulimit soft: 1048576
```

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

[Bug] 'disaggregation_mode' is missing in warmup function when compile deep_gemm #8617

Checklist

Describe the bug

Reproduction

Environment

Metadata

Assignees

Labels

Type

Projects

Milestone

Relationships

Development

[Bug] 'disaggregation_mode' is missing in warmup function when compile deep_gemm #8617

Description

Checklist

Describe the bug

Reproduction

Environment

Metadata

Metadata

Assignees

Labels

Type

Projects

Milestone

Relationships

Development

Issue actions