test_mla_int8_deepseek_v3.py 6.91 KB
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import unittest
from types import SimpleNamespace

import requests
import torch

from sglang.srt.utils import kill_process_tree
from sglang.test.few_shot_gsm8k import run_eval as run_eval_few_shot_gsm8k
from sglang.test.test_utils import (
    DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
    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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class TestMLADeepseekV3ChannelInt8(CustomTestCase):
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    @classmethod
    def setUpClass(cls):
        cls.model = "sgl-project/sglang-ci-dsv3-channel-int8-test"
        cls.base_url = DEFAULT_URL_FOR_TEST
        other_args = ["--trust-remote-code"]
        if torch.cuda.is_available() and torch.version.cuda:
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            other_args.extend(
                [
                    "--cuda-graph-max-bs",
                    "16",
                    "--enable-torch-compile",
                    "--torch-compile-max-bs",
                    "2",
                ]
            )
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        cls.process = popen_launch_server(
            cls.model,
            cls.base_url,
            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
            other_args=other_args,
        )

    @classmethod
    def tearDownClass(cls):
        kill_process_tree(cls.process.pid)

    def test_gsm8k(self):
        args = SimpleNamespace(
            num_shots=5,
            data_path=None,
            num_questions=200,
            max_new_tokens=512,
            parallel=128,
            host="http://127.0.0.1",
            port=int(self.base_url.split(":")[-1]),
        )
        metrics = run_eval_few_shot_gsm8k(args)
        print(metrics)

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        self.assertGreaterEqual(metrics["accuracy"], 0.61)
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@unittest.skipIf(is_in_ci(), "To reduce the CI execution time.")
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class TestDeepseekV3MTPChannelInt8(CustomTestCase):
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    @classmethod
    def setUpClass(cls):
        cls.model = "sgl-project/sglang-ci-dsv3-channel-int8-test"
        cls.base_url = DEFAULT_URL_FOR_TEST
        other_args = ["--trust-remote-code"]
        if torch.cuda.is_available() and torch.version.cuda:
            other_args.extend(
                [
                    "--cuda-graph-max-bs",
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                    "16",
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                    "--enable-torch-compile",
                    "--torch-compile-max-bs",
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                    "2" "--speculative-algorithm",
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                    "EAGLE",
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                    "--speculative-draft-model-path",
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                    "sgl-project/sglang-ci-dsv3-channel-int8-test-NextN",
                    "--speculative-num-steps",
                    "2",
                    "--speculative-eagle-topk",
                    "4",
                    "--speculative-num-draft-tokens",
                    "4",
                ]
            )
        cls.process = popen_launch_server(
            cls.model,
            cls.base_url,
            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
            other_args=other_args,
        )

    @classmethod
    def tearDownClass(cls):
        kill_process_tree(cls.process.pid)

    def test_gsm8k(self):
        requests.get(self.base_url + "/flush_cache")

        args = SimpleNamespace(
            num_shots=5,
            data_path=None,
            num_questions=200,
            max_new_tokens=512,
            parallel=128,
            host="http://127.0.0.1",
            port=int(self.base_url.split(":")[-1]),
        )
        metrics = run_eval_few_shot_gsm8k(args)
        print(metrics)

        self.assertGreater(metrics["accuracy"], 0.60)

        server_info = requests.get(self.base_url + "/get_server_info")
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        avg_spec_accept_length = server_info.json()["internal_states"][0][
            "avg_spec_accept_length"
        ]
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        print(f"{avg_spec_accept_length=}")
        self.assertGreater(avg_spec_accept_length, 2.5)


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@unittest.skipIf(is_in_ci(), "To reduce the CI execution time.")
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class TestMLADeepseekV3BlockInt8(CustomTestCase):
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    @classmethod
    def setUpClass(cls):
        cls.model = "sgl-project/sglang-ci-dsv3-block-int8-test"
        cls.base_url = DEFAULT_URL_FOR_TEST
        other_args = ["--trust-remote-code"]
        if torch.cuda.is_available() and torch.version.cuda:
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            other_args.extend(
                [
                    "--cuda-graph-max-bs",
                    "16",
                    "--enable-torch-compile",
                    "--torch-compile-max-bs",
                    "2",
                ]
            )
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        cls.process = popen_launch_server(
            cls.model,
            cls.base_url,
            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
            other_args=other_args,
        )

    @classmethod
    def tearDownClass(cls):
        kill_process_tree(cls.process.pid)

    def test_gsm8k(self):
        args = SimpleNamespace(
            num_shots=5,
            data_path=None,
            num_questions=200,
            max_new_tokens=512,
            parallel=128,
            host="http://127.0.0.1",
            port=int(self.base_url.split(":")[-1]),
        )
        metrics = run_eval_few_shot_gsm8k(args)
        print(metrics)

        self.assertGreater(metrics["accuracy"], 0.62)


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class TestDeepseekV3MTPBlockInt8(CustomTestCase):
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    @classmethod
    def setUpClass(cls):
        cls.model = "sgl-project/sglang-ci-dsv3-block-int8-test"
        cls.base_url = DEFAULT_URL_FOR_TEST
        other_args = ["--trust-remote-code"]
        if torch.cuda.is_available() and torch.version.cuda:
            other_args.extend(
                [
                    "--cuda-graph-max-bs",
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                    "16",
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                    "--enable-torch-compile",
                    "--torch-compile-max-bs",
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                    "2" "--speculative-algorithm",
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                    "EAGLE",
                    "--speculative-num-steps",
                    "2",
                    "--speculative-eagle-topk",
                    "4",
                    "--speculative-num-draft-tokens",
                    "4",
                ]
            )
        cls.process = popen_launch_server(
            cls.model,
            cls.base_url,
            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
            other_args=other_args,
        )

    @classmethod
    def tearDownClass(cls):
        kill_process_tree(cls.process.pid)

    def test_gsm8k(self):
        requests.get(self.base_url + "/flush_cache")

        args = SimpleNamespace(
            num_shots=5,
            data_path=None,
            num_questions=200,
            max_new_tokens=512,
            parallel=128,
            host="http://127.0.0.1",
            port=int(self.base_url.split(":")[-1]),
        )
        metrics = run_eval_few_shot_gsm8k(args)
        print(metrics)

        self.assertGreater(metrics["accuracy"], 0.60)

        server_info = requests.get(self.base_url + "/get_server_info")
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        avg_spec_accept_length = server_info.json()["internal_states"][0][
            "avg_spec_accept_length"
        ]
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        print(f"{avg_spec_accept_length=}")
        self.assertGreater(avg_spec_accept_length, 2.5)


if __name__ == "__main__":
    unittest.main()