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[https://nvbugs/5453727][fix] Fix bug of how GPT-OSS setup the parameters in CI (#7151)

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Signed-off-by: bhsueh <11360707+byshiue@users.noreply.github.com>
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bhsueh_NV 2025-08-27 15:26:10 +08:00 committed by GitHub
parent e08c7cf17b
commit f167b1fd99
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1 changed files with 18 additions and 16 deletions
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34
tests/integration/defs/accuracy/test_llm_api_pytorch.py
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@ -2699,22 +2699,21 @@ class TestPhi4MM(LlmapiAccuracyTestHarness):
class TestGPTOSS(LlmapiAccuracyTestHarness):
kv_cache_config = KvCacheConfig(free_gpu_memory_fraction=0.5)
extra_evaluator_kwargs = {
"fewshot_as_multiturn": True,
"apply_chat_template": True,
"scores_filter": "exact_match,flexible-extract",
"MAX_OUTPUT_LEN": 8192
}
MODEL_PATH = f"{llm_models_root()}/gpt_oss/gpt-oss-120b"
def update_task_kwargs(self, task):
task.EVALUATOR_KWARGS["fewshot_as_multiturn"] = True
task.EVALUATOR_KWARGS["apply_chat_template"] = True
task.EVALUATE_KWARGS["scores_filter"] = "exact_match,flexible-extract"
task.MAX_OUTPUT_LEN = 8192
return task
@pytest.mark.parametrize("moe_backend", ["CUTLASS", "TRTLLM", "TRITON"],
ids=["cutlass", "trtllm", "triton"])
@pytest.mark.parametrize("cuda_graph,overlap_scheduler", [
(True, True),
])
def test_w4_1gpu(self, moe_backend, cuda_graph, overlap_scheduler):
def test_w4_1gpu(self, moe_backend, cuda_graph, overlap_scheduler, mocker):
if moe_backend == "TRITON" and not IS_TRITON_KERNELS_AVAILABLE:
pytest.skip("Triton kernels are not available")
@ -2732,9 +2731,10 @@ class TestGPTOSS(LlmapiAccuracyTestHarness):
with llm:
model_name = "GPT-OSS/MXFP4"
mocker.patch.object(GSM8K, {"MAX_OUTPUT_LEN": 8192})
task = GSM8K(model_name)
task = self.update_task_kwargs(task)
task.evaluate(llm)
task.evaluate(llm,
extra_evaluator_kwargs=self.extra_evaluator_kwargs)
@pytest.mark.skip_less_device(4)
@pytest.mark.parametrize("moe_backend", ["CUTLASS", "TRTLLM", "TRITON"])
@ -2746,7 +2746,7 @@ class TestGPTOSS(LlmapiAccuracyTestHarness):
],
ids=["tp4", "ep4", "dp4"])
def test_w4_4gpus(self, moe_backend, tp_size, pp_size, ep_size,
attention_dp, cuda_graph, overlap_scheduler):
attention_dp, cuda_graph, overlap_scheduler, mocker):
if moe_backend == "TRITON":
if not IS_TRITON_KERNELS_AVAILABLE:
pytest.skip("Triton kernels are not available")
@ -2767,8 +2767,9 @@ class TestGPTOSS(LlmapiAccuracyTestHarness):
with llm:
model_name = "GPT-OSS/MXFP4"
task = GSM8K(model_name)
task = self.update_task_kwargs(task)
task.evaluate(llm)
mocker.patch.object(GSM8K, {"MAX_OUTPUT_LEN": 8192})
task.evaluate(llm,
extra_evaluator_kwargs=self.extra_evaluator_kwargs)
@pytest.mark.skip_less_device(4)
@pytest.mark.parametrize(
@ -2777,7 +2778,7 @@ class TestGPTOSS(LlmapiAccuracyTestHarness):
],
ids=["dp4"])
def test_w4a16(self, tp_size, pp_size, ep_size, attention_dp, cuda_graph,
overlap_scheduler, monkeypatch):
overlap_scheduler, monkeypatch, mocker):
if not IS_TRITON_KERNELS_AVAILABLE:
pytest.skip("Triton kernels are not available")
monkeypatch.setenv("OVERRIDE_QUANT_ALGO", "W4A16_MXFP4")
@ -2797,8 +2798,9 @@ class TestGPTOSS(LlmapiAccuracyTestHarness):
with llm:
model_name = "GPT-OSS/BF16"
task = GSM8K(model_name)
task = self.update_task_kwargs(task)
task.evaluate(llm)
mocker.patch.object(GSM8K, {"MAX_OUTPUT_LEN": 8192})
task.evaluate(llm,
extra_evaluator_kwargs=self.extra_evaluator_kwargs)
class TestEXAONE4(LlmapiAccuracyTestHarness):