sgl-project--sglang
94057c3d3e
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356 行
11 KiB
Python
356 行
11 KiB
Python
"""
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Usage:
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python3 -m unittest test_pp_single_node_extra.TestQwenVLPPAccuracy.test_gsm8k
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python3 -m unittest test_pp_single_node_extra.TestQwenPPAccuracy.test_pp_consistency
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python3 -m unittest test_pp_single_node_extra.TestQwenPPTieWeightsAccuracy.test_pp_consistency
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python3 -m unittest test_pp_single_node_extra.TestQwenMoePPAccuracy.test_pp_consistency
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python3 -m unittest test_pp_single_node_extra.TestQwen35PPAccuracy.test_pp_consistency
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python3 -m unittest test_pp_single_node_extra.TestGLM41VPPAccuracy.test_mmmu
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"""
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import time
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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_GLM_41V_PP,
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DEFAULT_MODEL_NAME_FOR_TEST_VL_PP,
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DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
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DEFAULT_URL_FOR_TEST,
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is_in_amd_ci,
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is_in_ci,
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popen_launch_server,
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)
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register_cuda_ci(est_time=350, stage="extra-b", runner_config="4-gpu-h100")
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register_amd_ci(est_time=350, suite="stage-c-test-4-gpu-amd")
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@unittest.skipIf(
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is_in_amd_ci(),
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"VLM PP accuracy too low on AMD (0.48-0.50 with both aiter and triton)",
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)
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class TestQwenVLPPAccuracy(unittest.TestCase):
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@classmethod
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def setUpClass(cls):
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cls.model = DEFAULT_MODEL_NAME_FOR_TEST_VL_PP
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cls.base_url = "http://127.0.0.1:23333"
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cls.process = popen_launch_server(
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DEFAULT_MODEL_NAME_FOR_TEST_VL_PP,
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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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"--tp-size",
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1,
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"--pp-size",
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4,
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"--chunked-prefill-size",
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8192,
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"--enable-multimodal",
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],
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)
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def test_gsm8k(self):
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args = SimpleNamespace(
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base_url=self.base_url,
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model=self.model,
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eval_name="gsm8k",
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api="completion",
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max_tokens=512,
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num_examples=200,
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num_threads=128,
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)
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metrics = run_eval(args)
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print(f"{metrics=}")
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self.assertGreaterEqual(metrics["score"], 0.65)
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# Wait a little bit so that the memory check happens.
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time.sleep(4)
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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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@unittest.skipIf(is_in_ci(), "To reduce the CI execution time.")
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def test_mmmu(self):
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args = SimpleNamespace(
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base_url=self.base_url,
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model=self.model,
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eval_name="mmmu",
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num_examples=None,
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num_threads=32,
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)
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metrics = run_eval(args)
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print(f"{metrics=}")
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self.assertGreater(metrics["score"], 0.26)
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class TestQwenPPAccuracy(unittest.TestCase):
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@classmethod
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def setUpClass(cls):
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cls.base_url = "http://127.0.0.1:23334" # different ports to avoid conflicts
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cls.model_name = "Qwen/Qwen3-8B" # replace with your Qwen Model if needed
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def run_gsm8k_test(self, pp_size):
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process = popen_launch_server(
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self.model_name,
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self.base_url,
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timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
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other_args=[
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"--pp-size",
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pp_size,
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"--chunked-prefill-size",
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256,
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],
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)
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try:
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args = SimpleNamespace(
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base_url=self.base_url,
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model=self.model_name,
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eval_name="gsm8k",
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api="completion",
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max_tokens=512,
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num_examples=512,
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num_threads=128,
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)
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metrics = run_eval(args)
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time.sleep(5)
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return metrics
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finally:
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kill_process_tree(process.pid)
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@unittest.skipIf(is_in_ci(), "To reduce the CI execution time.")
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def test_pp_consistency(self):
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baseline = self.run_gsm8k_test(pp_size=1)
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pp_metrics = self.run_gsm8k_test(pp_size=2)
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print(f"[Qwen PP Comparison] Baseline: {baseline} | PP: {pp_metrics}")
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self.assertGreaterEqual(baseline["score"], 0.74)
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self.assertGreaterEqual(
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pp_metrics["score"],
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baseline["score"] - 0.02,
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msg=(
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f"PP accuracy dropped more than 2% compared to baseline. "
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f"Baseline: {baseline['score']:.2%}, PP: {pp_metrics['score']:.2%}"
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),
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)
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@unittest.skipIf(is_in_amd_ci(), "PP consistency too flaky on AMD 4-GPU runners")
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class TestQwenPPTieWeightsAccuracy(unittest.TestCase):
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@classmethod
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def setUpClass(cls):
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cls.base_url = "http://127.0.0.1:23335" # different ports to avoid conflicts
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cls.model_name = (
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"Qwen/Qwen3-0.6B" # qwen3 < 8B all have tie_word_embeddings = True
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)
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def run_gsm8k_test(self, pp_size):
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process = popen_launch_server(
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self.model_name,
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self.base_url,
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timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
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other_args=[
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"--pp-size",
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pp_size,
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"--chunked-prefill-size",
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256,
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],
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)
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try:
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args = SimpleNamespace(
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base_url=self.base_url,
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model=self.model_name,
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eval_name="gsm8k",
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api="completion",
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max_tokens=512,
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num_examples=512,
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num_threads=128,
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)
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metrics = run_eval(args)
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time.sleep(5)
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return metrics
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finally:
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kill_process_tree(process.pid)
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def test_pp_consistency(self):
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baseline = self.run_gsm8k_test(pp_size=1)
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pp_metrics = self.run_gsm8k_test(pp_size=2)
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print(f"[Qwen PP Comparison] Baseline: {baseline} | PP: {pp_metrics}")
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self.assertGreaterEqual(baseline["score"], 0.38)
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self.assertGreaterEqual(
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pp_metrics["score"],
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baseline["score"] - 0.02,
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msg=(
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f"PP accuracy dropped more than 2% compared to baseline. "
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f"Baseline: {baseline['score']:.2%}, PP: {pp_metrics['score']:.2%}"
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),
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)
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class TestQwenMoePPAccuracy(unittest.TestCase):
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@classmethod
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def setUpClass(cls):
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cls.base_url = "http://127.0.0.1:23336" # different ports to avoid conflicts
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cls.model_name = "Qwen/Qwen3-30B-A3B" # replace with your Qwen Model if needed
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def run_gsm8k_test(self, pp_size):
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process = popen_launch_server(
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self.model_name,
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self.base_url,
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timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
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other_args=[
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"--pp-size",
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pp_size,
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"--chunked-prefill-size",
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256,
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],
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)
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try:
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args = SimpleNamespace(
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base_url=self.base_url,
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model=self.model_name,
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eval_name="gsm8k",
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api="completion",
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max_tokens=512,
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num_examples=512,
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num_threads=128,
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)
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metrics = run_eval(args)
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time.sleep(5)
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return metrics
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finally:
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kill_process_tree(process.pid)
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def test_pp_consistency(self):
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baseline = self.run_gsm8k_test(pp_size=1)
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pp_metrics = self.run_gsm8k_test(pp_size=2)
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print(f"[Qwen PP Comparison] Baseline: {baseline} | PP: {pp_metrics}")
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self.assertGreaterEqual(baseline["score"], 0.74)
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self.assertGreaterEqual(
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pp_metrics["score"],
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baseline["score"] - 0.02,
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msg=(
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f"PP accuracy dropped more than 2% compared to baseline. "
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f"Baseline: {baseline['score']:.2%}, PP: {pp_metrics['score']:.2%}"
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),
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)
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@unittest.skipIf(
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is_in_ci(), "Qwen35 PP consistency too flaky on H100 and AMD 4-GPU runners"
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)
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class TestQwen35PPAccuracy(unittest.TestCase):
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@classmethod
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def setUpClass(cls):
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cls.base_url = "http://127.0.0.1:23337" # different ports to avoid conflicts
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cls.model_name = (
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"Qwen/Qwen3.5-35B-A3B" # replace with your Qwen Model if needed
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)
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def run_gsm8k_test(self, tp_size, pp_size):
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process = popen_launch_server(
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self.model_name,
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self.base_url,
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timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
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other_args=[
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"--tp-size",
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tp_size,
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"--pp-size",
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pp_size,
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"--chunked-prefill-size",
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256,
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],
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)
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try:
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args = SimpleNamespace(
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base_url=self.base_url,
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model=self.model_name,
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eval_name="gsm8k",
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api="completion",
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max_tokens=512,
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num_examples=512,
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num_threads=128,
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)
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metrics = run_eval(args)
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time.sleep(5)
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return metrics
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finally:
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kill_process_tree(process.pid)
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def test_pp_consistency(self):
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baseline = self.run_gsm8k_test(tp_size=2, pp_size=1)
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pp_metrics = self.run_gsm8k_test(tp_size=1, pp_size=2)
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print(f"[Qwen35 PP Comparison] Baseline: {baseline} | PP: {pp_metrics}")
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self.assertGreaterEqual(baseline["score"], 0.83)
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self.assertGreaterEqual(
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pp_metrics["score"],
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baseline["score"] - 0.05,
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msg=(
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f"PP accuracy dropped more than 5% compared to baseline. "
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f"Baseline: {baseline['score']:.2%}, PP: {pp_metrics['score']:.2%}"
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),
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)
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@unittest.skipIf(
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is_in_ci(), "Skipping GLM41V PP accuracy test before it gets more stable"
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)
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class TestGLM41VPPAccuracy(unittest.TestCase):
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@classmethod
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def setUpClass(cls):
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cls.model = DEFAULT_MODEL_NAME_FOR_TEST_GLM_41V_PP
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cls.base_url = DEFAULT_URL_FOR_TEST
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cls.process = popen_launch_server(
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DEFAULT_MODEL_NAME_FOR_TEST_GLM_41V_PP,
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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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"--tp-size",
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1,
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"--pp-size",
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2,
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"--chunked-prefill-size",
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8192,
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"--enable-multimodal",
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"--reasoning-parser",
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"glm45",
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],
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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_mmmu(self):
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args = SimpleNamespace(
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base_url=self.base_url,
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model=self.model,
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eval_name="mmmu",
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num_examples=None,
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num_threads=32,
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response_answer_regex=r"<\|begin_of_box\|>(.*)<\|end_of_box\|>",
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)
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metrics = run_eval(args)
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print(f"{metrics=}")
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self.assertGreater(metrics["score"], 0.45)
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if __name__ == "__main__":
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unittest.main()
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