147 lines
5.1 KiB
Python
147 lines
5.1 KiB
Python
"""Nightly performance benchmark for Grok-2.
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This test benchmarks Grok-2 with FP8 quantization on 8 GPUs.
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Model paths can be configured via environment variables:
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- GROK2_MODEL_PATH: Path to Grok-2 model (default: xai-org/grok-2)
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- GROK2_TOKENIZER_PATH: Path to Grok-2 tokenizer (default: alvarobartt/grok-2-tokenizer)
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Example usage:
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python -m pytest test_grok2_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 - Grok-2 benchmark (~25 min)
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register_amd_ci(est_time=1500, suite="nightly-perf-8-gpu-grok2", 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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Skips the first result if it's a warmup run (duplicate batch_size).
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"""
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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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# Skip first result if it's a warmup (same batch_size as second result)
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report_results = (
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results[1:]
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if len(results) > 1 and results[0].batch_size == results[1].batch_size
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else results
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)
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for result in report_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 and tokenizer paths can be overridden via environment variables
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GROK2_MODEL_PATH = os.environ.get("GROK2_MODEL_PATH", "xai-org/grok-2")
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GROK2_TOKENIZER_PATH = os.environ.get(
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"GROK2_TOKENIZER_PATH", "alvarobartt/grok-2-tokenizer"
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)
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PROFILE_DIR = "performance_profiles_grok2"
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class TestNightlyGrok2Performance(unittest.TestCase):
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"""Nightly performance benchmark for Grok-2.
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Tests Grok-2 with FP8 quantization on TP=8.
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Runtime: ~25 minutes
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"""
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@classmethod
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def setUpClass(cls):
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cls.base_url = DEFAULT_URL_FOR_TEST
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cls.batch_sizes = [1, 8, 16, 64]
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cls.input_lens = tuple(_parse_int_list_env("NIGHTLY_INPUT_LENS", "1024"))
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cls.output_lens = tuple(_parse_int_list_env("NIGHTLY_OUTPUT_LENS", "512"))
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cls.model_config = {
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"name": "grok2",
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"model_path": GROK2_MODEL_PATH,
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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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"--quantization",
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"fp8",
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"--mem-fraction-static",
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"0.85",
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"--tokenizer-path",
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GROK2_TOKENIZER_PATH,
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"--attention-backend",
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"aiter",
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],
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"env_vars": {
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"RCCL_MSCCL_ENABLE": "0",
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"SGLANG_USE_AITER": "1",
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"SGLANG_INT4_WEIGHT": "0",
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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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cls.runner.full_report = f"## {cls.__name__}\n"
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def test_bench_grok2(self):
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"""Run benchmark for Grok-2."""
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# Set environment variables
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old_env = {}
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for key, value in self.model_config.get("env_vars", {}).items():
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old_env[key] = os.environ.get(key)
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os.environ[key] = value
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print(f"Setting env: {key}={value}")
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try:
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result_tuple = self.runner.run_benchmark_for_model(
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model_path=self.model_config["model_path"],
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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=self.model_config["other_args"],
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variant=self.model_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 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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self.assertTrue(success, "Benchmark failed for Grok-2")
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finally:
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# Restore original environment
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for key, value in old_env.items():
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if value is None:
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os.environ.pop(key, None)
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else:
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os.environ[key] = value
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self.runner.write_final_report()
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if __name__ == "__main__":
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unittest.main()
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