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chore: import upstream snapshot with attribution
2026-07-13 12:38:16 +08:00

178 行
5.5 KiB
Python

import os
import shutil
import unittest
from types import SimpleNamespace
from sglang.srt.utils import kill_process_tree
from sglang.test.ci.ci_register import register_cuda_ci
from sglang.test.run_eval import run_eval
from sglang.test.server_fixtures.disaggregation_fixture import (
PDDisaggregationServerBase,
)
from sglang.test.test_utils import (
DEFAULT_MODEL_NAME_FOR_TEST,
DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
popen_launch_pd_server,
)
# Registering the test for CUDA CI with appropriate parameters
# Increasing estimated time since we run evaluation twice
register_cuda_ci(
est_time=600,
stage="base-b",
runner_config="2-gpu-large",
)
class TestDisaggregationDecodeOffload(PDDisaggregationServerBase):
"""
Test class for verifying KV cache offloading on the decode side in a
prefill-decode disaggregation setup.
"""
@classmethod
def setUpClass(cls):
# Set environment variable to make offloading more frequent for testing purposes
cls.old_stride = os.environ.get("SGLANG_HICACHE_DECODE_OFFLOAD_STRIDE")
cls.hicache_dir = "/tmp/hicache_test"
os.environ["SGLANG_HICACHE_FILE_BACKEND_STORAGE_DIR"] = cls.hicache_dir
os.environ["SGLANG_HICACHE_DECODE_OFFLOAD_STRIDE"] = "16"
# Ensure a clean cache directory
if os.path.exists(cls.hicache_dir):
shutil.rmtree(cls.hicache_dir)
os.makedirs(cls.hicache_dir, exist_ok=True)
super().setUpClass()
cls.model = DEFAULT_MODEL_NAME_FOR_TEST
# Non-blocking start of prefill and decode servers
cls.start_prefill()
cls.start_decode()
# Wait for both servers to be ready before proceeding
cls.wait_server_ready(cls.prefill_url + "/health")
cls.wait_server_ready(cls.decode_url + "/health")
cls.launch_lb()
@classmethod
def tearDownClass(cls):
# Restore the original environment variable state
super().tearDownClass()
if cls.old_stride is not None:
os.environ["SGLANG_HICACHE_DECODE_OFFLOAD_STRIDE"] = cls.old_stride
else:
os.environ.pop("SGLANG_HICACHE_DECODE_OFFLOAD_STRIDE", None)
os.environ.pop("SGLANG_HICACHE_FILE_BACKEND_STORAGE_DIR", None)
# Clean up the cache directory
if os.path.exists(cls.hicache_dir):
shutil.rmtree(cls.hicache_dir)
@classmethod
def start_prefill(cls):
prefill_args = [
"--trust-remote-code",
"--disaggregation-mode",
"prefill",
"--disaggregation-bootstrap-port",
cls.bootstrap_port,
"--tp",
"1",
"--page-size",
"16",
"--enable-hierarchical-cache",
"--hicache-storage-backend",
"file",
"--hicache-ratio",
"2",
]
prefill_args += cls.transfer_backend + cls.rdma_devices
cls.process_prefill = popen_launch_pd_server(
cls.model,
cls.prefill_url,
timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
other_args=prefill_args,
)
@classmethod
def start_decode(cls):
decode_args = [
"--trust-remote-code",
"--disaggregation-mode",
"decode",
"--disaggregation-bootstrap-port",
cls.bootstrap_port,
"--tp",
"1",
"--base-gpu-id",
"1",
"--disaggregation-decode-enable-offload-kvcache",
"--num-reserved-decode-tokens",
"128",
"--hicache-ratio",
"2",
"--page-size",
"16",
"--hicache-storage-backend",
"file",
]
decode_args += cls.transfer_backend + cls.rdma_devices
cls.process_decode = popen_launch_pd_server(
cls.model,
cls.decode_url,
timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
other_args=decode_args,
)
def test_mmlu_double_eval(self):
"""
Run two rounds of MMLU evaluation:
1. First round: Decode node offloads KV cache back to disk (HiCache).
2. Restart All Nodes to clear memory cache.
3. Second round: Prefill node loads KV cache from disk (HiCache).
Verify that both rounds produce consistent scores.
"""
args = SimpleNamespace(
base_url=f"http://{self.base_host}:{self.lb_port}",
model=self.model,
eval_name="mmlu",
num_examples=64,
num_threads=32,
)
metrics1 = run_eval(args)
# Ensure all offloads are committed to disk
import time
time.sleep(10)
kill_process_tree(self.process_prefill.pid)
kill_process_tree(self.process_decode.pid)
kill_process_tree(self.process_lb.pid)
self.process_prefill.wait()
self.process_decode.wait()
self.process_lb.wait()
self.start_prefill()
self.start_decode()
self.launch_lb()
self.wait_server_ready(self.prefill_url + "/health")
self.wait_server_ready(self.decode_url + "/health")
metrics2 = run_eval(args)
# Assert score is above a minimum threshold for both rounds
self.assertGreater(metrics1["score"], 0.65)
self.assertGreater(metrics2["score"], 0.65)
# Score should be consistent: round 2 should be >= round 1, or at least within a 0.05 margin if slightly lower
self.assertGreaterEqual(metrics2["score"], metrics1["score"] - 0.05)
if __name__ == "__main__":
unittest.main()