"""Archived test classes split out of test/registered/mla/test_flashmla.py. Originally registered with `register_cuda_ci(...)`. Moved here as part of the per-commit pruning effort to keep the code reachable manually. Run with `python3 test/manual/mla/test_flashmla_archived.py`. """ """ Usage: python3 test/registered/mla/test_flashmla.py """ import unittest from types import SimpleNamespace import torch from sglang.srt.utils import kill_process_tree from sglang.test.run_eval import run_eval from sglang.test.test_utils import ( DEFAULT_MODEL_NAME_FOR_TEST_MLA, DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH, DEFAULT_URL_FOR_TEST, popen_launch_server, ) # FlashMLA attention backend tests with MTP speculative decoding class TestFlashMLAAttnBackend(unittest.TestCase): @classmethod def setUpClass(cls): cls.model = DEFAULT_MODEL_NAME_FOR_TEST_MLA 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-decode", "2", "--attention-backend", "flashmla", ] ) # Use longer timeout for DeepGEMM JIT compilation which can take 10-20 minutes cls.process = popen_launch_server( cls.model, cls.base_url, timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH * 2, other_args=other_args, ) @classmethod def tearDownClass(cls): kill_process_tree(cls.process.pid) def test_gsm8k(self): args = SimpleNamespace( base_url=self.base_url, model=self.model, eval_name="gsm8k", api="completion", max_tokens=512, num_examples=200, num_threads=128, ) metrics = run_eval(args) print(metrics) self.assertGreater(metrics["score"], 0.60) if __name__ == "__main__": unittest.main()