[CI] fix DS3.2 single node cudagraph_sizes config (#6241)
# What this PR does / why we need it?
This PR fixes the single-node nightly test for DeepSeek V3.2 (W8A8)
model to ensure CI stability. The changes include:
1. Simplified nightly test matrix (nightly_test_a3.yaml):
- Temporarily reduced to only run deepseek3_2-w8a8 test case for
debugging
- Changed trigger from schedule/workflow_dispatch to support
push/pull_request for faster iteration
2. Updated DeepSeek V3.2 test configuration
(test_deepseek_v3_2_w8a8.py):
- Adjusted cudagraph_capture_sizes from [3, 6, 9, 12] to [8, 16, 24, 32]
for better performance
- Increased max-num-seqs from 4 to 8
- Increased gpu-memory-utilization from 0.92 to 0.98
- Increased num_speculative_tokens from 2 to 3
3. Added PR checkout step (_e2e_nightly_single_node.yaml):
- Added ability to checkout a specific PR (#6241) for testing
# Does this PR introduce any user-facing change?
No. This PR only affects CI/CD test configurations and does not
introduce any user-facing changes.
# How was this patch tested?
Mock nightly test has passed, see
[here](https://github.com/vllm-project/vllm-ascend/actions/runs/21574655952/job/62159656622?pr=6241).
<img width="1053" height="714" alt="a2f2ee359febb13e1f6330b1bd3c116b"
src="https://github.com/user-attachments/assets/3262ad0f-adec-4c71-871f-d9cf2db06fbc"
/>
- vLLM version: v0.14.1
- vLLM main:
d68209402d
---------
Signed-off-by: guozr <guozr1997@hotmail.com>
Co-authored-by: guozr <guozr1997@hotmail.com>
This commit is contained in:
@@ -54,7 +54,7 @@ aisbench_cases = [{
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"max_out_len": 1500,
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"batch_size": 4,
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"request_rate": 11.2,
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"baseline": 134,
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"baseline": 110.5681,
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"threshold": 0.97
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}]
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@@ -80,13 +80,12 @@ async def test_models(model: str, tp_size: int, dp_size: int) -> None:
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str(tp_size), "--data-parallel-size",
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str(dp_size), "--port",
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str(port), "--max-model-len", "8192", "--max-num-batched-tokens",
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"8192", "--max-num-seqs", "4", "--trust-remote-code", "--quantization",
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"ascend", "--gpu-memory-utilization", "0.92", "--compilation-config",
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'{"cudagraph_capture_sizes":[3, 6, 9, 12], "cudagraph_mode":"FULL_DECODE_ONLY"}',
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"8192", "--max-num-seqs", "8", "--trust-remote-code", "--quantization",
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"ascend", "--gpu-memory-utilization", "0.98", "--compilation-config",
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'{"cudagraph_capture_sizes":[8, 16, 24, 32], "cudagraph_mode":"FULL_DECODE_ONLY"}',
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"--speculative-config",
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'{"num_speculative_tokens": 2, "method":"deepseek_mtp"}',
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"--additional-config",
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'{"layer_sharding": ["q_b_proj", "o_proj"]}',
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'{"num_speculative_tokens": 3, "method":"deepseek_mtp"}',
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"--additional-config", '{"layer_sharding": ["q_b_proj", "o_proj"]}',
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"--reasoning-parser", "deepseek_v3", "--tokenizer_mode", "deepseek_v32"
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]
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request_keyword_args: dict[str, Any] = {
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