Fix CI tests (#3132)
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@@ -49,7 +49,7 @@ class TestBenchServing(unittest.TestCase):
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)
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# There is a regression with torch 2.5
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# This number was 950 for torch 2.4
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self.assertGreater(res["output_throughput"], 850)
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self.assertGreater(res["output_throughput"], 1000)
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def test_offline_throughput_without_radix_cache(self):
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res = run_bench_serving(
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@@ -114,7 +114,7 @@ class TestBenchServing(unittest.TestCase):
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f"### test_offline_throughput_default_fp8\n"
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f'Output throughput: {res["output_throughput"]:.2f} token/s\n'
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)
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self.assertGreater(res["output_throughput"], 3850)
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self.assertGreater(res["output_throughput"], 3900)
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def test_online_latency_default(self):
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res = run_bench_serving(
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@@ -129,7 +129,7 @@ class TestBenchServing(unittest.TestCase):
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f"### test_online_latency_default\n"
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f'median_e2e_latency_ms : {res["median_e2e_latency_ms"]:.2f} ms\n'
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)
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self.assertLess(res["median_e2e_latency_ms"], 12000)
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self.assertLess(res["median_e2e_latency_ms"], 11000)
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self.assertLess(res["median_ttft_ms"], 86)
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self.assertLess(res["median_itl_ms"], 10)
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@@ -161,7 +161,7 @@ class TestBenchServing(unittest.TestCase):
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f"### test_online_latency_eagle\n"
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f'median_e2e_latency_ms : {res["median_e2e_latency_ms"]:.2f} ms\n'
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)
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self.assertLess(res["median_e2e_latency_ms"], 10000)
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self.assertLess(res["median_e2e_latency_ms"], 450)
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def test_moe_offline_throughput_default(self):
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res = run_bench_serving(
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@@ -176,7 +176,7 @@ class TestBenchServing(unittest.TestCase):
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f"### test_moe_offline_throughput_default\n"
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f'Output throughput: {res["output_throughput"]:.2f} token/s\n'
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)
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self.assertGreater(res["output_throughput"], 2150)
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self.assertGreater(res["output_throughput"], 2200)
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def test_moe_offline_throughput_without_radix_cache(self):
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res = run_bench_serving(
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@@ -191,7 +191,7 @@ class TestBenchServing(unittest.TestCase):
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f"### test_moe_offline_throughput_without_radix_cache\n"
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f'Output throughput: {res["output_throughput"]:.2f} token/s\n'
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)
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self.assertGreater(res["output_throughput"], 2150)
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self.assertGreater(res["output_throughput"], 2200)
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if __name__ == "__main__":
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