04a10c9bc2
Co-authored-by: Bingxu Chen <bingxche@amd.com> Co-authored-by: bingxche <Bingxu.Chen@amd.com> Co-authored-by: michaelzhang-ai <michaelzhang.ai@users.noreply.github.com>
57 lines
1.6 KiB
Python
57 lines
1.6 KiB
Python
# Model tests for compressed tensors (FP8)
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import unittest
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from types import SimpleNamespace
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from sglang.srt.utils import is_hip, 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.few_shot_gsm8k import run_eval
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from sglang.test.test_utils import (
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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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popen_launch_server,
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)
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register_cuda_ci(est_time=42, suite="stage-b-test-large-1-gpu")
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register_amd_ci(est_time=42, suite="stage-b-test-small-1-gpu-amd")
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class TestCompressedTensorsLlama3FP8(CustomTestCase):
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@classmethod
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def setUpClass(cls):
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cls.model = "RedHatAI/Meta-Llama-3.1-8B-FP8"
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cls.base_url = DEFAULT_URL_FOR_TEST
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cls.process = popen_launch_server(
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cls.model,
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cls.base_url,
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timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
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other_args=[],
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)
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@classmethod
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def tearDownClass(cls):
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kill_process_tree(cls.process.pid)
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def test_gsm8k(self):
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args = SimpleNamespace(
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num_shots=5,
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data_path=None,
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num_questions=200,
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max_new_tokens=512,
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parallel=128,
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host="http://127.0.0.1",
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port=int(self.base_url.split(":")[-1]),
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)
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metrics = run_eval(args)
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print(f"{metrics=}")
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if is_hip():
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# Lower threshold for AMD because FP8 dtype differs (fp8_fnuz)
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self.assertGreaterEqual(metrics["accuracy"], 0.40)
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else:
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self.assertGreaterEqual(metrics["accuracy"], 0.45)
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if __name__ == "__main__":
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unittest.main()
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