Files
sglang/test/registered/unit/mem_cache/test_cp_hicache_metadata.py
T

266 lines
9.6 KiB
Python

import sys
import unittest
from unittest.mock import MagicMock
import torch
# Stub out sgl_kernel before any sglang import so this CPU unit test does not
# require CUDA extension libraries to be installed.
for _mod in ("sgl_kernel", "sgl_kernel.kvcacheio"):
if _mod not in sys.modules:
sys.modules[_mod] = MagicMock()
from sglang.srt.mem_cache.hiradix_cache import CpHiCacheNodeMetadata, HiRadixCache
from sglang.srt.mem_cache.radix_cache import RadixKey, TreeNode
from sglang.test.ci.ci_register import register_cpu_ci
from sglang.test.test_utils import CustomTestCase
register_cpu_ci(est_time=2, suite="stage-a-test-cpu")
class TestCpHiCacheNodeMetadata(CustomTestCase):
def test_split_zero_len_moves_all_positions_to_child(self):
metadata = CpHiCacheNodeMetadata(
logical_len=8,
owned_positions=torch.tensor([1, 3, 7], dtype=torch.int64),
host_indices=torch.tensor([10, 11, 12], dtype=torch.int64),
)
parent, child = metadata.split(0)
self.assertEqual(parent.logical_len, 0)
self.assertEqual(parent.owned_positions.tolist(), [])
self.assertEqual(parent.host_indices.tolist(), [])
self.assertEqual(child.logical_len, 8)
self.assertEqual(child.owned_positions.tolist(), [1, 3, 7])
self.assertEqual(child.host_indices.tolist(), [10, 11, 12])
def test_split_rebases_child_positions(self):
metadata = CpHiCacheNodeMetadata(
logical_len=10,
owned_positions=torch.tensor([0, 2, 5, 9], dtype=torch.int64),
host_indices=torch.tensor([20, 21, 22, 23], dtype=torch.int64),
)
parent, child = metadata.split(5)
self.assertEqual(parent.logical_len, 5)
self.assertEqual(parent.owned_positions.tolist(), [0, 2])
self.assertEqual(parent.host_indices.tolist(), [20, 21])
self.assertEqual(child.logical_len, 5)
self.assertEqual(child.owned_positions.tolist(), [0, 4])
self.assertEqual(child.host_indices.tolist(), [22, 23])
def test_zero_owned_metadata_is_valid(self):
metadata = CpHiCacheNodeMetadata(
logical_len=64,
owned_positions=torch.empty((0,), dtype=torch.int32),
host_indices=torch.empty((0,), dtype=torch.int32),
)
self.assertEqual(metadata.logical_len, 64)
self.assertEqual(metadata.owned_positions.device.type, "cpu")
self.assertEqual(metadata.host_indices.device.type, "cpu")
self.assertEqual(metadata.owned_positions.dtype, torch.int64)
self.assertEqual(metadata.host_indices.dtype, torch.int64)
def test_non_int64_inputs_are_converted(self):
metadata = CpHiCacheNodeMetadata(
logical_len=4,
owned_positions=torch.tensor([1, 3], dtype=torch.int32),
host_indices=torch.tensor([10, 11], dtype=torch.int32),
)
self.assertEqual(metadata.owned_positions.dtype, torch.int64)
self.assertEqual(metadata.host_indices.dtype, torch.int64)
def test_negative_logical_len_raises(self):
with self.assertRaisesRegex(ValueError, "logical_len"):
CpHiCacheNodeMetadata(
logical_len=-1,
owned_positions=torch.empty((0,), dtype=torch.int64),
host_indices=torch.empty((0,), dtype=torch.int64),
)
def test_metadata_does_not_alias_input_tensors(self):
owned_positions = torch.tensor([1, 3], dtype=torch.int64)
host_indices = torch.tensor([10, 11], dtype=torch.int64)
metadata = CpHiCacheNodeMetadata(
logical_len=4,
owned_positions=owned_positions,
host_indices=host_indices,
)
owned_positions[0] = 2
host_indices[0] = 12
self.assertEqual(metadata.owned_positions.tolist(), [1, 3])
self.assertEqual(metadata.host_indices.tolist(), [10, 11])
def test_invalid_split_raises(self):
metadata = CpHiCacheNodeMetadata(
logical_len=4,
owned_positions=torch.tensor([1], dtype=torch.int64),
host_indices=torch.tensor([9], dtype=torch.int64),
)
with self.assertRaisesRegex(ValueError, "split_len"):
metadata.split(5)
def test_unsorted_positions_raise(self):
with self.assertRaisesRegex(ValueError, "sorted"):
CpHiCacheNodeMetadata(
logical_len=4,
owned_positions=torch.tensor([2, 1], dtype=torch.int64),
host_indices=torch.tensor([9, 10], dtype=torch.int64),
)
def test_duplicate_positions_raise(self):
with self.assertRaisesRegex(ValueError, "strictly increasing"):
CpHiCacheNodeMetadata(
logical_len=4,
owned_positions=torch.tensor([1, 1], dtype=torch.int64),
host_indices=torch.tensor([9, 10], dtype=torch.int64),
)
def test_length_mismatch_raises(self):
with self.assertRaisesRegex(ValueError, "same length"):
CpHiCacheNodeMetadata(
logical_len=4,
owned_positions=torch.tensor([1, 2], dtype=torch.int64),
host_indices=torch.tensor([9], dtype=torch.int64),
)
def test_out_of_range_positions_raise(self):
with self.assertRaisesRegex(ValueError, r"\[0, logical_len\)"):
CpHiCacheNodeMetadata(
logical_len=4,
owned_positions=torch.tensor([4], dtype=torch.int64),
host_indices=torch.tensor([9], dtype=torch.int64),
)
class FakeWriteFailure:
metadata = None
def __init__(self, required_host_slots):
self.required_host_slots = required_host_slots
class FakeWriteSuccess:
required_host_slots = 0
def __init__(self, metadata):
self.metadata = metadata
class FakeWriteController:
def __init__(self, required_host_slots):
self.required_host_slots = required_host_slots
self.calls = 0
self.write_policy = "write_through"
self.evicted_host_indices = []
def write(self, device_indices, node_id=-1, priority=None):
self.calls += 1
if self.calls == 1:
return FakeWriteFailure(self.required_host_slots)
return FakeWriteSuccess(
CpHiCacheNodeMetadata(
logical_len=len(device_indices),
owned_positions=torch.tensor([0], dtype=torch.int64),
host_indices=torch.tensor([99], dtype=torch.int64),
)
)
def evict_host(self, host_indices):
self.evicted_host_indices.append(host_indices.clone())
return len(host_indices)
class FakeEvictionStrategy:
def get_priority(self, node):
return 0
class TestHiRadixCacheCPBackup(CustomTestCase):
def test_node_backuped_uses_cp_metadata(self):
cache = HiRadixCache.__new__(HiRadixCache)
cache._uses_cp_hicache = True
node = TreeNode()
node.host_len = 8
node.cp_hicache = CpHiCacheNodeMetadata(
logical_len=8,
owned_positions=torch.tensor([1, 2], dtype=torch.int64),
host_indices=torch.tensor([10, 11], dtype=torch.int64),
)
self.assertTrue(cache._node_backuped(node))
def test_inc_hit_count_does_not_rewrite_cp_backed_node(self):
cache = HiRadixCache.__new__(HiRadixCache)
cache._uses_cp_hicache = True
cache.write_through_threshold = 1
cache.cache_controller = type(
"Controller", (), {"write_policy": "write_through"}
)()
cache.write_backup = lambda node: (_ for _ in ()).throw(
AssertionError("must not rewrite")
)
node = TreeNode()
node.host_len = 4
node.cp_hicache = CpHiCacheNodeMetadata(
logical_len=4,
owned_positions=torch.tensor([], dtype=torch.int64),
host_indices=torch.tensor([], dtype=torch.int64),
)
cache._inc_hit_count(node)
self.assertEqual(node.hit_count, 1)
def test_write_backup_retries_by_required_physical_slots(self):
cache = HiRadixCache.__new__(HiRadixCache)
cache._uses_cp_hicache = True
cache.cache_controller = FakeWriteController(required_host_slots=1)
cache.evictable_host_leaves = set()
cache.eviction_strategy = FakeEvictionStrategy()
cache.get_child_key_fn = lambda key: key.token_ids[0]
cache._record_remove_event = lambda node: None
cache.ongoing_write_through = {}
cache.inc_node_lock_ref = lambda node: None
root = TreeNode()
root.key = RadixKey(token_ids=[], extra_key=None)
root.value = []
cache.root_node = root
evictable_node = TreeNode()
evictable_node.parent = root
evictable_node.key = RadixKey(token_ids=[1], extra_key=None)
evictable_node.value = None
evictable_node.host_len = 4
evictable_node.cp_hicache = CpHiCacheNodeMetadata(
logical_len=4,
owned_positions=torch.tensor([0], dtype=torch.int64),
host_indices=torch.tensor([55], dtype=torch.int64),
)
root.children[1] = evictable_node
cache.evictable_host_leaves.add(evictable_node)
node = TreeNode()
node.value = torch.arange(16, dtype=torch.int64)
cache.write_backup(node)
self.assertEqual(
cache.cache_controller.evicted_host_indices[0].tolist(), [55]
)
self.assertEqual(evictable_node.host_len, 0)
self.assertIsNone(evictable_node.cp_hicache)
self.assertNotIn(1, root.children)
self.assertEqual(node.host_len, 16)
if __name__ == "__main__":
unittest.main()