3f3c201243
Co-authored-by: kkHuang-amd <wunhuang@amd.com> Co-authored-by: YC Tseng <yctseng@amd.com>
72 lines
2.0 KiB
Python
72 lines
2.0 KiB
Python
"""
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Usage:
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python3 -m unittest test_triton_attention_backend.TestTritonAttnBackend.test_mmlu
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"""
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import unittest
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from types import SimpleNamespace
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from sglang.srt.utils import kill_process_tree
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from sglang.test.ci.ci_register import register_amd_ci, register_cuda_ci
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from sglang.test.run_eval import run_eval
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from sglang.test.test_utils import (
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DEFAULT_MODEL_NAME_FOR_TEST,
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DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
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DEFAULT_URL_FOR_TEST,
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CustomTestCase,
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is_in_ci,
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popen_launch_server,
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run_bench_offline_throughput,
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)
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# Triton attention backend integration test with latency benchmark and MMLU eval
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register_cuda_ci(est_time=200, suite="stage-b-test-large-1-gpu")
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register_amd_ci(est_time=1400, suite="stage-b-test-small-1-gpu-amd")
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class TestTritonAttnBackend(CustomTestCase):
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def test_latency(self):
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output_throughput = run_bench_offline_throughput(
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DEFAULT_MODEL_NAME_FOR_TEST,
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[
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"--attention-backend",
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"triton",
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"--enable-torch-compile",
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"--cuda-graph-max-bs",
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4,
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],
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)
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print(f"{output_throughput=}")
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if is_in_ci():
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self.assertGreater(output_throughput, 153)
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def test_mmlu(self):
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model = DEFAULT_MODEL_NAME_FOR_TEST
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base_url = DEFAULT_URL_FOR_TEST
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process = popen_launch_server(
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model,
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base_url,
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timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
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other_args=["--attention-backend", "triton"],
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)
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try:
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args = SimpleNamespace(
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base_url=base_url,
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model=model,
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eval_name="mmlu",
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num_examples=64,
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num_threads=32,
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)
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metrics = run_eval(args)
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self.assertGreaterEqual(metrics["score"], 0.65)
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finally:
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kill_process_tree(process.pid)
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if __name__ == "__main__":
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unittest.main()
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