[CI] Reduce CUDA graph mode test overhead (#58749)

Misha Goin committed Sep 26, 2026 at 11:22 UTC 79ac28c5bd363d243ff2dea39306b568f59d4153
1 file changed +10 -6
tests/v1/cudagraph/test_cudagraph_mode.py
+10 -6
@@ -54,13 +54,16 @@ def test_backend_and_cudagraph_mode_combo(backend_name, cudagraph_mode, supporte
54
55 llm = LLM(
56 model="Qwen/Qwen2-1.5B-Instruct",
57 - max_num_seqs=256,
57 + max_num_seqs=16,
58 + max_num_batched_tokens=128,
59 trust_remote_code=True,
60 gpu_memory_utilization=0.45,
61 max_model_len=1024,
62 attention_config=attention_config,
63 compilation_config=CompilationConfig(
63 - mode=CompilationMode.VLLM_COMPILE, cudagraph_mode=cudagraph_mode
64 + mode=CompilationMode.VLLM_COMPILE,
65 + cudagraph_mode=cudagraph_mode,
66 + cudagraph_capture_sizes=[1, 2, 4, 8, 16, 64, 128],
67 ),
68 )
69 llm.generate(["Hello, my name is"] * 10)
@@ -72,11 +75,9 @@ attn_backend = "RocmAttn" if current_platform.is_rocm() else "FA2"
75
76 combo_cases_2 = [
77 (attn_backend, "FULL", CompilationMode.NONE, True),
75 - (attn_backend, "FULL", CompilationMode.VLLM_COMPILE, True),
78 (attn_backend, "PIECEWISE", CompilationMode.NONE, True),
79 (attn_backend, "PIECEWISE", CompilationMode.VLLM_COMPILE, True),
80 (attn_backend, "FULL_AND_PIECEWISE", CompilationMode.NONE, True),
79 - (attn_backend, "FULL_AND_PIECEWISE", CompilationMode.VLLM_COMPILE, True),
81 (attn_backend, "FULL_DECODE_ONLY", CompilationMode.NONE, True),
82 (attn_backend, "FULL_DECODE_ONLY", CompilationMode.VLLM_COMPILE, True),
83 (attn_backend, "NONE", CompilationMode.NONE, True),
@@ -100,13 +101,16 @@ def test_cudagraph_compilation_combo(
101
102 llm = LLM(
103 model="Qwen/Qwen2-1.5B-Instruct",
103 - max_num_seqs=256,
104 + max_num_seqs=16,
105 + max_num_batched_tokens=128,
106 trust_remote_code=True,
107 gpu_memory_utilization=0.45,
108 max_model_len=1024,
109 attention_config=attention_config,
110 compilation_config=CompilationConfig(
109 - mode=compilation_mode, cudagraph_mode=cudagraph_mode
111 + mode=compilation_mode,
112 + cudagraph_mode=cudagraph_mode,
113 + cudagraph_capture_sizes=[1, 2, 4, 8, 16, 64, 128],
114 ),
115 )
116 llm.generate(["Hello, my name is"] * 10)