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[EPLB][Nightly] Refactor UT #6543

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Merged
wangxiyuan merged 1 commit into from
Feb 14, 2026
Merged

[EPLB][Nightly] Refactor UT #6543

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12 changes: 8 additions & 4 deletions tests/e2e/nightly/single_node/models/test_deepseek_r1_0528_w8a8.py
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Original file line number Diff line number Diff line change
Expand Up @@ -63,10 +63,7 @@
}]


@pytest.mark.asyncio
@pytest.mark.parametrize("model", MODELS)
@pytest.mark.parametrize("mode", MODES)
async def test_models(model: str, mode: str) -> None:
def config():
port = get_open_port()
env_dict = {
"OMP_NUM_THREADS": "10",
Expand All @@ -85,6 +82,13 @@ async def test_models(model: str, mode: str) -> None:
"--speculative-config",
json.dumps(speculative_config)
]
return port, env_dict, additional_config, server_args

@pytest.mark.asyncio
@pytest.mark.parametrize("model", MODELS)
@pytest.mark.parametrize("mode", MODES)
async def test_models(model: str, mode: str) -> None:
port, env_dict, additional_config, server_args = config()
if mode == "single":
server_args.append("--enforce-eager")
server_args.extend(["--additional-config", json.dumps(additional_config)])
Expand Down
69 changes: 18 additions & 51 deletions tests/e2e/nightly/single_node/models/test_deepseek_r1_0528_w8a8_eplb.py
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Original file line number Diff line number Diff line change
Expand Up @@ -23,18 +23,7 @@

from tests.e2e.conftest import RemoteOpenAIServer
from tools.aisbench import run_aisbench_cases

MODELS = [
"vllm-ascend/DeepSeek-R1-0528-W8A8",
]

prompts = [
"San Francisco is a",
]

api_keyword_args = {
"max_tokens": 10,
}
from .test_deepseek_r1_0528_w8a8 import *

aisbench_cases = [{
"case_type": "accuracy",
Expand All @@ -50,46 +39,23 @@

@pytest.mark.asyncio
@pytest.mark.parametrize("model", MODELS)
async def test_models(model: str) -> None:
port = get_open_port()
env_dict = {
"OMP_NUM_THREADS": "100",
"OMP_PROC_BIND": "false",
"HCCL_BUFFSIZE": "200",
"VLLM_RPC_TIMEOUT": "3600000",
"VLLM_EXECUTE_MODEL_TIMEOUT_SECONDS": "3600000",
"DISABLE_L2_CACHE": "1",
"DYNAMIC_EPLB": "true",
}
speculative_config = {"num_speculative_tokens": 1, "method": "mtp"}
compilation_config = {
"cudagraph_capture_sizes": [24],
"cudagraph_mode": "FULL_DECODE_ONLY"
}
additional_config: dict[str, Any] = {
"enable_shared_expert_dp": False,
"multistream_overlap_shared_expert": False,
"eplb_config": {
"dynamic_eplb": True,
"expert_heat_collection_interval": 512,
"algorithm_execution_interval": 100,
"num_redundant_experts": 0
async def test_models_eplb(model: str) -> None:
port, env_dict, additional_config, server_args = config()
additional_config.update(
{
"eplb_config": {
"dynamic_eplb": "true",
"expert_heat_collection_interval": 1000,
"algorithm_execution_interval": 50,
"eplb_policy_type": 3,
}
}
}
server_args = [
"--quantization", "ascend", "--seed", "1024",
"--no-enable-prefix-caching", "--data-parallel-size", "4",
"--tensor-parallel-size", "4", "--enable-expert-parallel", "--port",
str(port), "--max-model-len", "40000", "--max-num-batched-tokens",
"4096", "--max-num-seqs", "12", "--trust-remote-code",
"--gpu-memory-utilization", "0.92"
]
server_args.extend(
["--speculative-config",
json.dumps(speculative_config)])
server_args.extend(
["--compilation-config",
json.dumps(compilation_config)])
)
env_dict.update(
{
"DYNAMIC_EPLB": "true",
}
)
server_args.extend(["--additional-config", json.dumps(additional_config)])
request_keyword_args: dict[str, Any] = {
**api_keyword_args,
Expand All @@ -113,3 +79,4 @@ async def test_models(model: str) -> None:
port,
aisbench_cases,
server_args=server_args)

62 changes: 14 additions & 48 deletions tests/e2e/nightly/single_node/models/test_qwen3_235b_a22b_w8a8_eplb.py
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Original file line number Diff line number Diff line change
Expand Up @@ -23,64 +23,30 @@

from tests.e2e.conftest import RemoteOpenAIServer
from tools.aisbench import run_aisbench_cases

MODELS = [
"vllm-ascend/Qwen3-235B-A22B-W8A8",
]

prompts = [
"San Francisco is a",
]

api_keyword_args = {
"max_tokens": 10,
}

aisbench_cases = [{
"case_type": "accuracy",
"dataset_path": "vllm-ascend/gsm8k-lite",
"request_conf": "vllm_api_general_chat",
"dataset_conf": "gsm8k/gsm8k_gen_0_shot_cot_chat_prompt",
"max_out_len": 32768,
"batch_size": 32,
"top_k": 20,
"baseline": 95,
"threshold": 5
}]
from .test_qwen3_235b_w8a8 import *


@pytest.mark.asyncio
@pytest.mark.parametrize("model", MODELS)
async def test_models(model: str) -> None:
port = get_open_port()
env_dict = {
"OMP_NUM_THREADS": "10",
"OMP_PROC_BIND": "false",
"HCCL_BUFFSIZE": "1024",
"PYTORCH_NPU_ALLOC_CONF": "expandable_segments:True",
"VLLM_ASCEND_ENABLE_FLASHCOMM1": "1"
}
async def test_models_eplb(model: str) -> None:
port, aisbench_cases, env_dict, compilation_config, server_args = config()
env_dict.update(
{
"DYNAMIC_EPLB": "true",
}
)
additional_config: dict[str, Any] = {}
compilation_config = {"cudagraph_mode": "FULL_DECODE_ONLY"}
server_args = [
"--quantization", "ascend", "--async-scheduling",
"--data-parallel-size", "4", "--tensor-parallel-size", "4",
"--enable-expert-parallel", "--port",
str(port), "--max-model-len", "40960", "--max-num-batched-tokens",
"8192", "--max-num-seqs", "12", "--trust-remote-code",
"--gpu-memory-utilization", "0.9"
]
env_dict["DYNAMIC_EPLB"] = "true"
additional_config["eplb_config"] = {
"dynamic_eplb": True,
"expert_heat_collection_interval": 512,
"algorithm_execution_interval": 100,
"num_redundant_experts": 0
"dynamic_eplb": "true",
"expert_heat_collection_interval": 600,
"algorithm_execution_interval": 50,
"num_redundant_experts": 16,
"eplb_policy_type": 2,
}
server_args.extend(["--additional-config", json.dumps(additional_config)])
server_args.extend(
["--compilation-config",
json.dumps(compilation_config)])
server_args.extend(["--additional-config", json.dumps(additional_config)])
request_keyword_args: dict[str, Any] = {
**api_keyword_args,
}
Expand Down
39 changes: 21 additions & 18 deletions tests/e2e/nightly/single_node/models/test_qwen3_235b_w8a8.py
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Original file line number Diff line number Diff line change
Expand Up @@ -38,24 +38,19 @@
"max_tokens": 10,
}

aisbench_cases = [{
"case_type": "accuracy",
"dataset_path": "vllm-ascend/gsm8k-lite",
"request_conf": "vllm_api_general_chat",
"dataset_conf": "gsm8k/gsm8k_gen_0_shot_cot_chat_prompt",
"max_out_len": 32768,
"batch_size": 32,
"top_k": 20,
"baseline": 95,
"threshold": 5
}]


@pytest.mark.asyncio
@pytest.mark.parametrize("model", MODELS)
@pytest.mark.parametrize("mode", MODES)
async def test_models(model: str, mode: str) -> None:
def config():
port = get_open_port()
aisbench_cases = [{
"case_type": "accuracy",
"dataset_path": "vllm-ascend/gsm8k-lite",
"request_conf": "vllm_api_general_chat",
"dataset_conf": "gsm8k/gsm8k_gen_0_shot_cot_chat_prompt",
"max_out_len": 32768,
"batch_size": 32,
"top_k": 20,
"baseline": 95,
"threshold": 5
}]
env_dict = {
"OMP_NUM_THREADS": "10",
"OMP_PROC_BIND": "false",
Expand All @@ -72,11 +67,19 @@ async def test_models(model: str, mode: str) -> None:
"8192", "--max-num-seqs", "12", "--trust-remote-code",
"--gpu-memory-utilization", "0.9"
]
return port, aisbench_cases, env_dict, compilation_config, server_args


@pytest.mark.asyncio
@pytest.mark.parametrize("model", MODELS)
@pytest.mark.parametrize("mode", MODES)
async def test_models(model: str, mode: str) -> None:
port, aisbench_cases, env_dict, compilation_config, server_args = config()
if mode == "piecewise":
compilation_config["cudagraph_mode"] = "PIECEWISE"
server_args.extend(
["--compilation-config",
json.dumps(compilation_config)])
json.dumps(compilation_config)])
request_keyword_args: dict[str, Any] = {
**api_keyword_args,
}
Expand Down