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sglang/test/registered/unit/mem_cache/test_mem_pool_host.py
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"""Unit tests for host-pool allocation and free-list bookkeeping."""
import threading
import unittest
import unittest.mock
import torch
from sglang.srt.mem_cache.hicache_storage import PoolName, PoolTransfer
from sglang.srt.mem_cache.memory_pool import MHATokenToKVPool
from sglang.srt.mem_cache.memory_pool_host import (
DeepSeekV4PagedHostPool,
LogicalHostPool,
)
from sglang.srt.mem_cache.pool_host import HostPoolGroup, PoolEntry, base
from sglang.srt.mem_cache.pool_host.mamba import MambaPoolHost
from sglang.srt.mem_cache.pool_host.mha import MHATokenToKVPoolHost
from sglang.srt.runtime_context import get_context
from sglang.test.ci.ci_register import register_cpu_ci
from sglang.test.test_utils import CustomTestCase
register_cpu_ci(est_time=11, suite="base-a-test-cpu")
class TestHostKVCache(CustomTestCase):
def setUp(self):
self.page_size = 2
# Small device pool is enough to construct the host pool.
self.device_pool = MHATokenToKVPool(
size=self.page_size * 2,
page_size=self.page_size,
dtype=torch.float16,
head_num=2,
head_dim=4,
layer_num=2,
device="cpu",
enable_memory_saver=False,
)
self.host_pool = MHATokenToKVPoolHost(
device_pool=self.device_pool,
host_to_device_ratio=2.0,
host_size=0,
page_size=self.page_size,
layout="layer_first",
pin_memory=False,
device="cpu",
allocator_type="default",
)
def test_multiple_attention_rows_per_token(self):
for rows_per_token in (1, 3):
device_pool = MHATokenToKVPool(
size=4,
page_size=self.page_size,
dtype=torch.float16,
head_num=2 * rows_per_token,
head_dim=4,
layer_num=2,
device="cpu",
enable_memory_saver=False,
)
# Report logical heads while retaining the wider physical rows.
device_pool.head_num = 2
for layout in (
"layer_first",
"page_first",
"page_first_direct",
"page_head",
):
with self.subTest(rows_per_token=rows_per_token, layout=layout):
host_pool = MHATokenToKVPoolHost(
device_pool=device_pool,
host_to_device_ratio=2.0,
host_size=0,
page_size=self.page_size,
layout=layout,
pin_memory=False,
)
device_row = device_pool.k_buffer[0][0]
row_bytes = device_row.numel() * device_row.element_size()
self.assertEqual(host_pool.element_dim, device_row.numel())
self.assertEqual(host_pool.token_stride_size, row_bytes)
self.assertEqual(
host_pool.size_per_token, 2 * device_pool.layer_num * row_bytes
)
self.assertEqual(
host_pool.kv_buffer.nbytes,
host_pool.size * host_pool.size_per_token,
)
def test_double_alloc(self):
indices = self.host_pool.alloc(4)
self.assertEqual(len(indices), 4)
# Mimic bookkeeping corruption: push an already-used slot back to the
# head of free_slots so the next alloc would hand out an in-use slot.
leak = torch.tensor([int(indices[0])])
self.host_pool.free_slots = torch.cat([leak, self.host_pool.free_slots])
with self.assertRaises(AssertionError) as ctx:
self.host_pool.alloc(4)
msg = str(ctx.exception)
self.assertIn("Double-alloc", msg)
self.assertIn(f"[{int(leak[0])}]", msg)
def test_double_free(self):
indices = self.host_pool.alloc(4)
self.assertEqual(len(indices), 4)
self.host_pool.free(indices[:2])
# indices[1] is double freed.
with self.assertRaises(AssertionError) as ctx:
self.host_pool.free(indices[1:])
msg = str(ctx.exception)
self.assertIn("Double-free", msg)
self.assertIn(f"[{int(indices[1])}]", msg)
def test_free_unallocated(self):
indices = torch.tensor([1])
with self.assertRaises(AssertionError) as ctx:
self.host_pool.free(indices)
msg = str(ctx.exception)
self.assertIn("Double-free", msg)
self.assertIn(f"[{int(indices[0])}]", msg)
def test_free_after_clear(self):
indices = self.host_pool.alloc(4)
self.host_pool.clear()
with self.assertRaises(AssertionError) as ctx:
self.host_pool.free(indices)
msg = str(ctx.exception)
self.assertIn("Double-free", msg)
self.assertIn(str(indices.tolist()), msg)
def test_shm_allocator(self):
shm_host_pool = MHATokenToKVPoolHost(
device_pool=self.device_pool,
host_to_device_ratio=2.0,
host_size=0,
page_size=self.page_size,
layout="layer_first",
pin_memory=False,
device="cpu",
allocator_type="shm",
)
self.assertIsNotNone(shm_host_pool.fd)
self.assertGreaterEqual(shm_host_pool.fd, 0)
indices = shm_host_pool.alloc(4)
self.assertEqual(len(indices), 4)
shm_host_pool.free(indices)
def test_empty_free_keeps_release_list_empty(self):
self.assertEqual(self.host_pool.free(torch.empty(0, dtype=torch.int64)), 0)
self.assertEqual(self.host_pool.num_release_slots, 0)
self.assertEqual(self.host_pool.release_slots, [])
class TestLazyHostPoolRelease(CustomTestCase):
@staticmethod
def _make_mamba_pool():
pool = MambaPoolHost.__new__(MambaPoolHost)
pool.size = 8
pool.page_size = 1
pool.device = "cpu"
pool.lock = threading.RLock()
pool.clear()
return pool
@staticmethod
def _make_deepseek_v4_pool():
pool = DeepSeekV4PagedHostPool.__new__(DeepSeekV4PagedHostPool)
pool.size = 8
pool.slot_page_size = 2
pool.lock = threading.RLock()
pool.clear()
return pool
@staticmethod
def _make_logical_pool():
return LogicalHostPool(size=8, page_size=2)
@staticmethod
def _make_transfer_pool(*, page_aligned_only):
pool = DeepSeekV4PagedHostPool.__new__(DeepSeekV4PagedHostPool)
pool.pool_name = str(PoolName.DEEPSEEK_V4_C4_INDEXER)
pool.slot_page_size = 4
pool.layer_num = 1
pool.page_aligned_only = page_aligned_only
pool.device_ptrs = [0]
pool.data_ptrs = [0]
return pool
def _assert_lazy_release(self, pool):
self.assertEqual(pool.free(torch.empty(0, dtype=torch.int64)), 0)
self.assertEqual(pool.num_release_slots, 0)
self.assertEqual(pool.release_slots, [])
allocated = pool.alloc(6)
free_slots_before = pool.free_slots
pool.free(allocated[:2])
# free() should keep the primary free-list untouched and only record
# the released chunk for a later merge.
self.assertIs(pool.free_slots, free_slots_before)
self.assertEqual(pool.num_release_slots, 2)
self.assertEqual(len(pool.release_slots), 1)
self.assertEqual(pool.available_size(), 4)
# Consume the primary free-list first without merging pending slots.
self.assertTrue(torch.equal(pool.alloc(2), torch.tensor([6, 7])))
self.assertEqual(pool.num_release_slots, 2)
# Once the primary free-list is exhausted, alloc() merges and reuses
# the pending slots.
self.assertTrue(torch.equal(pool.alloc(2), torch.tensor([0, 1])))
self.assertEqual(pool.num_release_slots, 0)
self.assertEqual(pool.release_slots, [])
self.assertEqual(pool.available_size(), 0)
pool.free(torch.tensor([0, 1]))
pool.clear()
self.assertEqual(pool.num_release_slots, 0)
self.assertEqual(pool.release_slots, [])
self.assertEqual(pool.available_size(), 8)
# Exercise the general merge path with multiple released chunks.
allocated = pool.alloc(8)
pool.free(allocated[:2])
pool.free(allocated[2:4])
self.assertEqual(len(pool.release_slots), 2)
self.assertTrue(torch.equal(pool.alloc(4), torch.tensor([0, 1, 2, 3])))
self.assertEqual(pool.num_release_slots, 0)
self.assertEqual(pool.release_slots, [])
def test_mamba_pool_lazy_release(self):
self._assert_lazy_release(self._make_mamba_pool())
def test_deepseek_v4_pool_lazy_release(self):
pool = self._make_deepseek_v4_pool()
self._assert_lazy_release(pool)
# Preserve the pool's page-aligned allocation behavior.
pool.clear()
self.assertEqual(len(pool.alloc(1)), 2)
def test_grouped_page_rows_reject_unaligned_transfers(self):
# FP4 indexer rows group their slots, so a partial page has no
# well-defined token-granular copy and must not silently fall back.
pool = self._make_transfer_pool(page_aligned_only=True)
unaligned = torch.arange(3, dtype=torch.int64)
with self.assertRaisesRegex(ValueError, "page-aligned"):
pool.backup_from_device_all_layer(None, unaligned, unaligned, "direct")
with self.assertRaisesRegex(ValueError, "page-aligned"):
pool.load_to_device_per_layer(None, unaligned, unaligned, 0, "direct")
def test_fused_page_rows_keep_token_granular_transfers(self):
pool = self._make_transfer_pool(page_aligned_only=False)
unaligned = torch.arange(3, dtype=torch.int64)
with unittest.mock.patch(
"sglang.srt.mem_cache.memory_pool_host.transfer_cache_dsv4_mla"
) as transfer:
pool.backup_from_device_all_layer(None, unaligned, unaligned, "direct")
pool.load_to_device_per_layer(None, unaligned, unaligned, 0, "direct")
self.assertEqual(transfer.call_count, 2)
def test_logical_pool_lazy_release(self):
pool = self._make_logical_pool()
self._assert_lazy_release(pool)
# Preserve the logical pool's strict page-alignment checks.
pool.clear()
with self.assertRaises(ValueError):
pool.alloc(1)
with self.assertRaises(ValueError):
pool.free(torch.tensor([0]))
class TestHostMemoryBudget(CustomTestCase):
# Pinned so the two budget reads below see identical free memory; the real
# psutil value drifts between calls and would flake the equality checks.
_AVAILABLE = base.HICACHE_HOST_MEMORY_RESERVE_BYTES + 64 * (1024**3)
def _budget_with_ranks(self, ranks):
# Deliberate single-accessor stub: isolates the budget math from the
# topology derivation, which the ranks_per_host case below covers.
with (
unittest.mock.patch.object(base, "ranks_per_host", return_value=ranks),
unittest.mock.patch.object(
base, "available_host_memory_bytes", return_value=self._AVAILABLE
),
):
return base.host_memory_budget_bytes()
def test_budget_is_split_across_co_located_ranks(self):
solo = self._budget_with_ranks(1)
self.assertEqual(self._budget_with_ranks(4), solo // 4)
def test_reserve_is_taken_before_the_split(self):
# Each rank must not get its own copy of the reserve.
budget = self._budget_with_ranks(8)
self.assertLessEqual(
budget * 8, self._AVAILABLE - base.HICACHE_HOST_MEMORY_RESERVE_BYTES
)
def test_ranks_per_host_divides_world_size_by_nodes(self):
with (
get_context().override_server_args(nnodes=2, tp_size=16),
unittest.mock.patch.object(
torch.distributed, "is_initialized", return_value=True
),
):
self.assertEqual(base.ranks_per_host(), 8)
class TestHostPoolGroup(CustomTestCase):
@staticmethod
def _group(**sizes):
return HostPoolGroup(
[
PoolEntry(
name=PoolName(name),
host_pool=LogicalHostPool(size=size, page_size=1),
device_pool=None,
layer_mapper=lambda layer_id: layer_id,
is_primary_index_anchor=name == PoolName.KV.value,
)
for name, size in sizes.items()
]
)
def test_resolve_and_release_multi_pool_allocation(self):
group = self._group(kv=4, swa=2)
primary = group.alloc(2)
transfers = [
PoolTransfer(name=PoolName.SWA, device_indices=torch.arange(2)),
PoolTransfer(name=PoolName.INDEXER, indices_from_pool=PoolName.SWA),
]
self.assertIsNotNone(
group.resolve_host_transfers(
transfers,
primary_device_indices=torch.arange(2),
primary_host_indices=primary,
)
)
self.assertIs(transfers[1].host_indices, transfers[0].host_indices)
group.free(primary)
group.release_transfers(transfers)
self.assertEqual(group.available_size(), 4)
self.assertEqual(group.available_size(PoolName.SWA), 2)
def test_resolve_rolls_back_partial_allocation(self):
group = self._group(kv=4, swa=2, mamba=1)
transfers = [
PoolTransfer(name=PoolName.SWA, device_indices=torch.arange(2)),
PoolTransfer(name=PoolName.MAMBA, device_indices=torch.arange(2)),
]
self.assertIsNone(group.resolve_host_transfers(transfers))
self.assertIsNone(transfers[0].host_indices)
self.assertEqual(group.available_size(PoolName.SWA), 2)
if __name__ == "__main__":
unittest.main()