add dsv3 int8 test (#4705)
This commit is contained in:
@@ -41,6 +41,7 @@ suites = {
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TestFile("test_metrics.py", 32),
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TestFile("test_metrics.py", 32),
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TestFile("test_mla.py", 92),
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TestFile("test_mla.py", 92),
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TestFile("test_mla_deepseek_v3.py", 221),
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TestFile("test_mla_deepseek_v3.py", 221),
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TestFile("test_mla_int8_deepseek_v3.py", 421),
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TestFile("test_mla_flashinfer.py", 395),
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TestFile("test_mla_flashinfer.py", 395),
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TestFile("test_mla_fp8.py", 93),
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TestFile("test_mla_fp8.py", 93),
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TestFile("test_no_chunked_prefill.py", 126),
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TestFile("test_no_chunked_prefill.py", 126),
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209
test/srt/test_mla_int8_deepseek_v3.py
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209
test/srt/test_mla_int8_deepseek_v3.py
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@@ -0,0 +1,209 @@
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import unittest
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from types import SimpleNamespace
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import requests
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import torch
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from sglang.srt.utils import kill_process_tree
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from sglang.test.few_shot_gsm8k import run_eval as run_eval_few_shot_gsm8k
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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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popen_launch_server,
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)
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class TestMLADeepseekV3ChannelInt8(unittest.TestCase):
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@classmethod
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def setUpClass(cls):
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cls.model = "sgl-project/sglang-ci-dsv3-channel-int8-test"
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cls.base_url = DEFAULT_URL_FOR_TEST
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other_args = ["--trust-remote-code"]
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if torch.cuda.is_available() and torch.version.cuda:
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other_args.extend(["--enable-torch-compile", "--cuda-graph-max-bs", "2"])
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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=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_few_shot_gsm8k(args)
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print(metrics)
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self.assertGreater(metrics["accuracy"], 0.62)
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class TestDeepseekV3MTPChannelInt8(unittest.TestCase):
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@classmethod
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def setUpClass(cls):
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cls.model = "sgl-project/sglang-ci-dsv3-channel-int8-test"
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cls.base_url = DEFAULT_URL_FOR_TEST
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other_args = ["--trust-remote-code"]
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if torch.cuda.is_available() and torch.version.cuda:
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other_args.extend(
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[
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"--cuda-graph-max-bs",
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"2",
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"--disable-radix",
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"--enable-torch-compile",
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"--torch-compile-max-bs",
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"1",
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"--speculative-algorithm",
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"EAGLE",
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"--speculative-draft",
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"sgl-project/sglang-ci-dsv3-channel-int8-test-NextN",
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"--speculative-num-steps",
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"2",
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"--speculative-eagle-topk",
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"4",
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"--speculative-num-draft-tokens",
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"4",
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]
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)
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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=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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requests.get(self.base_url + "/flush_cache")
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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_few_shot_gsm8k(args)
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print(metrics)
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self.assertGreater(metrics["accuracy"], 0.60)
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server_info = requests.get(self.base_url + "/get_server_info")
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avg_spec_accept_length = server_info.json()["avg_spec_accept_length"]
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print(f"{avg_spec_accept_length=}")
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self.assertGreater(avg_spec_accept_length, 2.5)
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class TestMLADeepseekV3BlockInt8(unittest.TestCase):
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@classmethod
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def setUpClass(cls):
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cls.model = "sgl-project/sglang-ci-dsv3-block-int8-test"
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cls.base_url = DEFAULT_URL_FOR_TEST
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other_args = ["--trust-remote-code"]
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if torch.cuda.is_available() and torch.version.cuda:
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other_args.extend(["--enable-torch-compile", "--cuda-graph-max-bs", "2"])
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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=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_few_shot_gsm8k(args)
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print(metrics)
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self.assertGreater(metrics["accuracy"], 0.62)
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class TestDeepseekV3MTPBlockInt8(unittest.TestCase):
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@classmethod
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def setUpClass(cls):
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cls.model = "sgl-project/sglang-ci-dsv3-block-int8-test"
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cls.base_url = DEFAULT_URL_FOR_TEST
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other_args = ["--trust-remote-code"]
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if torch.cuda.is_available() and torch.version.cuda:
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other_args.extend(
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[
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"--cuda-graph-max-bs",
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"2",
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"--disable-radix",
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"--enable-torch-compile",
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"--torch-compile-max-bs",
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"1",
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"--speculative-algorithm",
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"EAGLE",
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"--speculative-draft",
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"sgl-project/sglang-ci-dsv3-block-int8-test-NextN",
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"--speculative-num-steps",
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"2",
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"--speculative-eagle-topk",
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"4",
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"--speculative-num-draft-tokens",
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"4",
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]
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)
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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=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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requests.get(self.base_url + "/flush_cache")
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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_few_shot_gsm8k(args)
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print(metrics)
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self.assertGreater(metrics["accuracy"], 0.60)
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server_info = requests.get(self.base_url + "/get_server_info")
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avg_spec_accept_length = server_info.json()["avg_spec_accept_length"]
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print(f"{avg_spec_accept_length=}")
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self.assertGreater(avg_spec_accept_length, 2.5)
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if __name__ == "__main__":
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unittest.main()
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