147 lines
5.5 KiB
Python
147 lines
5.5 KiB
Python
"""Nightly performance benchmark for DeepSeek-V3 model.
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This test benchmarks the DeepSeek-V3 model with basic and MTP configurations on 8 GPUs.
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The model path can be configured via DEEPSEEK_V3_MODEL_PATH environment variable.
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Example usage:
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DEEPSEEK_V3_MODEL_PATH=deepseek-ai/DeepSeek-V3-0324 python -m pytest test_deepseek_v3_perf.py -v
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"""
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import os
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import unittest
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from typing import List
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from sglang.test.ci.ci_register import register_amd_ci
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from sglang.test.nightly_bench_utils import BenchmarkResult
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from sglang.test.nightly_utils import NightlyBenchmarkRunner
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from sglang.test.test_utils import DEFAULT_URL_FOR_TEST, _parse_int_list_env
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# Register for AMD CI - DeepSeek-V3 benchmark (basic + MTP, ~300 min)
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register_amd_ci(est_time=18000, suite="nightly-perf-8-gpu-deepseek-v3", nightly=True)
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def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
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"""Generate a simplified markdown report without traces and cost columns."""
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model_header = results[0].model_path
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if results[0].run_name and results[0].run_name != "default":
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model_header += f" ({results[0].run_name})"
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gpu_config = os.getenv("GPU_CONFIG", "")
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if gpu_config:
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model_header += f" [{gpu_config}]"
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summary = f"### {model_header}\n"
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summary += "| batch size | input len | latency (s) | input throughput (tok/s) | output throughput (tok/s) | ITL (ms) |\n"
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summary += "| ---------- | --------- | ----------- | ------------------------ | ------------------------- | -------- |\n"
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for result in results:
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itl = 1 / (result.output_throughput / result.batch_size) * 1000
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summary += f"| {result.batch_size} | {result.input_len} | {result.latency:.2f} | {result.input_throughput:.2f} | {result.output_throughput:.2f} | {itl:.2f} |\n"
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return summary
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# Model path can be overridden via environment variable
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DEEPSEEK_V3_MODEL_PATH = os.environ.get(
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"DEEPSEEK_V3_MODEL_PATH", "deepseek-ai/DeepSeek-V3-0324"
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)
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PROFILE_DIR = "performance_profiles_deepseek_v3"
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class TestNightlyDeepseekV3Performance(unittest.TestCase):
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"""Nightly performance benchmark for DeepSeek-V3 model.
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Tests the DeepSeek-V3 model with both basic and MTP configurations on TP=8.
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"""
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@classmethod
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def setUpClass(cls):
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cls.model = DEEPSEEK_V3_MODEL_PATH
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cls.base_url = DEFAULT_URL_FOR_TEST
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cls.batch_sizes = [1, 1, 8, 16, 64]
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cls.input_lens = tuple(_parse_int_list_env("NIGHTLY_INPUT_LENS", "4096"))
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cls.output_lens = tuple(_parse_int_list_env("NIGHTLY_OUTPUT_LENS", "512"))
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# Define variant configurations for DeepSeek-V3
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cls.variants = [
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{
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"name": "basic",
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"other_args": [
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"--trust-remote-code",
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"--tp",
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"8",
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"--mem-fraction-static",
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"0.85",
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"--model-loader-extra-config",
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'{"enable_multithread_load": true}',
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],
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},
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{
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"name": "mtp",
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"other_args": [
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"--trust-remote-code",
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"--tp",
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"8",
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"--speculative-algorithm",
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"EAGLE",
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"--speculative-num-steps",
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"3",
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"--speculative-eagle-topk",
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"1",
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"--speculative-num-draft-tokens",
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"4",
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"--mem-fraction-static",
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"0.7",
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"--model-loader-extra-config",
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'{"enable_multithread_load": true}',
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],
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},
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]
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cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url)
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cls.runner.setup_profile_directory()
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# Override full_report to remove traces help text
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cls.runner.full_report = f"## {cls.__name__}\n"
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def test_bench_one_batch(self):
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"""Run benchmark across all configured variants."""
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failed_variants = []
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try:
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for variant_config in self.variants:
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with self.subTest(variant=variant_config["name"]):
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result_tuple = self.runner.run_benchmark_for_model(
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model_path=self.model,
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batch_sizes=self.batch_sizes,
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input_lens=self.input_lens,
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output_lens=self.output_lens,
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other_args=variant_config["other_args"],
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variant=variant_config["name"],
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extra_bench_args=["--trust-remote-code"],
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enable_profile=False, # Disable profiling for AMD tests
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)
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results = result_tuple[0]
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success = result_tuple[1]
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if not success:
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failed_variants.append(variant_config["name"])
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# Use simplified report format without traces
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if results:
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self.runner.full_report += (
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generate_simple_markdown_report(results) + "\n"
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)
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finally:
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self.runner.write_final_report()
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if failed_variants:
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raise AssertionError(
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f"Benchmark failed for {self.model} with the following variants: "
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f"{', '.join(failed_variants)}"
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)
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if __name__ == "__main__":
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unittest.main()
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