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sglang/test/registered/unit/mem_cache/test_hisparse_allocator.py
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Python

import unittest
from concurrent.futures import ThreadPoolExecutor
from types import SimpleNamespace
from unittest.mock import MagicMock, patch
import numpy as np
import torch
from sglang.srt.managers.schedule_batch import ReqKvInfo
from sglang.srt.mem_cache.allocator.hisparse import (
DeepSeekV4HiSparseTokenToKVPoolAllocator,
)
from sglang.srt.runtime_context import get_context, publish, reset_context
from sglang.srt.server_args import ServerArgs
from sglang.test.ci.ci_register import register_cpu_ci
from sglang.test.test_utils import CustomTestCase
register_cpu_ci(est_time=10, suite="base-a-test-cpu")
class TestHiSparseDecodeRemap(CustomTestCase):
def test_page_size_one_reclaims_temporary_device_slot(self):
"""Decode remapping must reclaim its temporary slot without freeing the live slot."""
from sglang.srt.managers.hisparse_coordinator import HiSparseCoordinator
from sglang.srt.mem_cache.allocator.hisparse import (
HiSparseTokenToKVPoolAllocator,
)
from sglang.srt.mem_cache.memory_pool import MiniMaxSparseKVPool
pool = MiniMaxSparseKVPool(
size=8,
page_size=1,
dtype=torch.float32,
head_num=1,
head_dim=8,
idx_head_dim=16,
dense_layer_ids=[0],
sparse_layer_ids=[1],
disable_value_sparse_layer_ids=[1],
device="cpu",
start_layer=0,
end_layer=2,
enable_hisparse=True,
)
allocator = HiSparseTokenToKVPoolAllocator(
size=pool.size,
page_size=1,
dtype=pool.dtype,
device="cpu",
kvcache=pool,
need_sort=False,
)
coordinator = HiSparseCoordinator.__new__(HiSparseCoordinator)
coordinator.is_dsv4_hisparse = False
coordinator.mem_pool_device = pool.main_pool
coordinator.token_to_kv_pool_allocator = allocator
coordinator.device_buffer_size = 2
coordinator.req_to_device_buffer = allocator.hisparse_attn_allocator.alloc(
3
).reshape(1, 3)
coordinator.req_device_buffer_size = torch.tensor([3])
coordinator.req_device_buffer_token_locs = torch.zeros(
(1, 1, 3), dtype=torch.int32
)
coordinator._skip_first_backup = [True]
out_loc = allocator.alloc(1)
with patch("sglang.srt.managers.hisparse_coordinator._is_hip", False):
for _ in range(2):
coordinator._skip_first_backup[0] = True
coordinator.map_last_loc_to_buffer(
seq_lens=torch.tensor([3]),
out_cache_loc=out_loc,
req_pool_indices=torch.tensor([0]),
seq_lens_cpu=torch.tensor([3]),
req_pool_indices_cpu=torch.tensor([0]),
)
self.assertEqual(
allocator.hisparse_attn_allocator.available_size(), pool.size - 3
)
torch.testing.assert_close(
allocator.full_to_hisparse_device_index_mapping[out_loc],
coordinator.req_to_device_buffer[:, 2],
)
class TestDeepSeekV4HiSparseAllocator(CustomTestCase):
def setUp(self):
# The code under test reads its config from the bags.
reset_context()
self.addCleanup(reset_context)
publish(ServerArgs(model_path="dummy"), role="tokenizer")
def test_forwards_swa_tail_allocation_to_logical_allocator(self):
allocator = object.__new__(DeepSeekV4HiSparseTokenToKVPoolAllocator)
logical_allocator = MagicMock(spec=["alloc_extend_swa_tail"])
allocator.logical_attn_allocator = logical_allocator
expected = torch.tensor([8, 9, 10], dtype=torch.int64)
logical_allocator.alloc_extend_swa_tail.return_value = expected
prefix_lens = torch.tensor([0], dtype=torch.int64)
prefix_lens_cpu = torch.tensor([0], dtype=torch.int64)
seq_lens = torch.tensor([512], dtype=torch.int64)
seq_lens_cpu = torch.tensor([512], dtype=torch.int64)
last_loc = torch.tensor([-1], dtype=torch.int64)
result = allocator.alloc_extend_swa_tail(
prefix_lens=prefix_lens,
prefix_lens_cpu=prefix_lens_cpu,
seq_lens=seq_lens,
seq_lens_cpu=seq_lens_cpu,
last_loc=last_loc,
extend_num_tokens=512,
swa_tail_len=128,
)
self.assertIs(result, expected)
logical_allocator.alloc_extend_swa_tail.assert_called_once()
_, kwargs = logical_allocator.alloc_extend_swa_tail.call_args
self.assertIs(kwargs["prefix_lens"], prefix_lens)
self.assertIs(kwargs["prefix_lens_cpu"], prefix_lens_cpu)
self.assertIs(kwargs["seq_lens"], seq_lens)
self.assertIs(kwargs["seq_lens_cpu"], seq_lens_cpu)
self.assertIs(kwargs["last_loc"], last_loc)
self.assertEqual(kwargs["extend_num_tokens"], 512)
self.assertEqual(kwargs["swa_tail_len"], 128)
def test_forwards_prealloc_reclaim_to_logical_allocator(self):
"""PD decode preallocation must not crash on the HiSparse composite."""
allocator = object.__new__(DeepSeekV4HiSparseTokenToKVPoolAllocator)
logical_allocator = MagicMock(spec=["reclaim_for_prealloc"])
allocator.logical_attn_allocator = logical_allocator
logical_allocator.reclaim_for_prealloc.return_value = None
tree_cache = object()
self.assertIsNone(allocator.reclaim_for_prealloc(tree_cache, 512, 256))
logical_allocator.reclaim_for_prealloc.assert_called_once_with(
tree_cache, 512, 256
)
logical_allocator.reclaim_for_prealloc.return_value = "SWA eviction short"
self.assertEqual(
allocator.reclaim_for_prealloc(tree_cache, 512, 256),
"SWA eviction short",
)
def test_hisparse_budget_uses_full_logical_capacity_for_swa_tail(self):
from sglang.srt.disaggregation.decode import DecodePreallocQueue
queue = DecodePreallocQueue.__new__(DecodePreallocQueue)
logical_allocator = SimpleNamespace(
available_size=MagicMock(return_value=32),
full_available_size=MagicMock(return_value=512),
)
queue.token_to_kv_pool_allocator = SimpleNamespace(
logical_attn_allocator=logical_allocator
)
queue.scheduler = SimpleNamespace(enable_hisparse=True, last_batch=None)
queue.retracted_queue = []
queue.num_reserved_decode_tokens = 0
queue._uses_swa_tail_prealloc = MagicMock(return_value=True)
queue._need_space_for_single_req = MagicMock(return_value=0)
queue._active_reserved_tokens = MagicMock(return_value=0)
budget = queue._allocatable_token_budgets()
self.assertEqual(budget, 512)
logical_allocator.full_available_size.assert_called_once_with()
logical_allocator.available_size.assert_not_called()
def test_hisparse_prealloc_uses_swa_tail_for_direct_host_path(self):
from sglang.srt.disaggregation.decode import DecodePreallocQueue
fill_len = 512
sliding_window_size = 200
# _swa_tail_len floors the window start to a page boundary:
# floor_align(512 - 200, 256) = 256, so the tail is one whole page.
swa_tail_len = 256
kv_loc = torch.arange(512, 512 + fill_len, dtype=torch.int64)
host_indices = torch.arange(1000, 1128, dtype=torch.int64)
req = SimpleNamespace(
rid="req-0",
origin_input_ids=list(range(fill_len)),
output_ids=[],
kv=ReqKvInfo(),
)
def set_extend_range(start, end):
req.extend_range = SimpleNamespace(start=start, end=end, length=end - start)
req.set_extend_range = set_extend_range
class ReqToTokenPool:
def __init__(self):
self.writes = []
def alloc(self, reqs):
for item in reqs:
item.kv.req_pool_idx = 0
return torch.tensor([0], dtype=torch.int64)
def write(self, indices, values):
self.writes.append((indices, values))
req_to_token_pool = ReqToTokenPool()
allocator = SimpleNamespace(
device=torch.device("cpu"),
page_size=256,
available_size=MagicMock(return_value=fill_len),
swa_available_size=MagicMock(return_value=swa_tail_len),
alloc_extend_swa_tail=MagicMock(return_value=kv_loc),
alloc_logical_only=MagicMock(return_value=kv_loc),
)
regular_host_alloc = MagicMock(return_value=host_indices)
coordinator = SimpleNamespace(
mem_pool_host=SimpleNamespace(alloc_paged_token_slots=regular_host_alloc),
req_to_host_pool=object(),
req_to_host_pool_allocated_len=object(),
host_token_len=MagicMock(side_effect=lambda token_len: token_len // 4),
)
queue = DecodePreallocQueue.__new__(DecodePreallocQueue)
queue.req_to_token_pool = req_to_token_pool
queue.token_to_kv_pool_allocator = allocator
queue.tree_cache = SimpleNamespace(
evictable_size=MagicMock(return_value=0),
protected_size=MagicMock(return_value=0),
)
queue.scheduler = SimpleNamespace(
enable_hisparse=True,
hisparse_coordinator=coordinator,
server_args=SimpleNamespace(disaggregation_decode_enable_radix_cache=False),
sliding_window_size=sliding_window_size,
)
queue._uses_swa_tail_prealloc = MagicMock(return_value=True)
result = queue._pre_alloc(req)
self.assertTrue(torch.equal(result, host_indices))
allocator.alloc_extend_swa_tail.assert_called_once()
allocator.alloc_logical_only.assert_not_called()
_, kwargs = allocator.alloc_extend_swa_tail.call_args
self.assertEqual(kwargs["extend_num_tokens"], fill_len)
self.assertEqual(kwargs["swa_tail_len"], swa_tail_len)
self.assertEqual(req.kv.swa_evicted_seqlen, fill_len - swa_tail_len)
self.assertEqual(req.kv.kv_allocated_len, fill_len)
self.assertEqual(req.kv.kv_committed_len, fill_len)
self.assertEqual(req.extend_range.length, fill_len)
self.assertEqual(len(req_to_token_pool.writes), 1)
coordinator.host_token_len.assert_called_once_with(fill_len)
regular_host_alloc.assert_called_once_with(
coordinator.req_to_host_pool,
coordinator.req_to_host_pool_allocated_len,
req.kv.req_pool_idx,
0,
len(host_indices),
)
self.assertTrue(torch.equal(req_to_token_pool.writes[0][1], kv_loc))
# C4 indexer/C128 use the logical allocator's full-page IDs. They do not
# use either the independently allocated host pages or C4 sparse slots.
np.testing.assert_array_equal(
np.unique(kv_loc.numpy() // allocator.page_size),
np.array([2, 3]),
)
def test_mooncake_uses_separate_host_and_device_page_indices(self):
from sglang.srt.disaggregation.mooncake.conn import MooncakeKVManager
manager = object.__new__(MooncakeKVManager)
manager.is_mla_backend = True
manager.is_hybrid_mla_backend = False
manager.enable_custom_mem_pool = False
manager.max_transfer_batch_indices = 0
manager._transfer_data = MagicMock(return_value=0)
with ThreadPoolExecutor(max_workers=1) as executor:
ret = manager._send_kvcache_generic(
mooncake_session_id="session",
src_data_ptrs=[1000, 2000, 3000],
dst_data_ptrs=[10000, 20000, 30000],
item_lens=[100, 100, 100],
prefill_data_indices=np.array([1, 2], dtype=np.int32),
dst_data_indices=np.array([7, 8], dtype=np.int32),
executor=executor,
dst_device_data_indices=np.array([21, 22], dtype=np.int32),
dst_device_data_ptrs={20000, 30000},
)
self.assertEqual(ret, 0)
manager._transfer_data.assert_called_once_with(
"session",
[
(1100, 10700, 200),
(2100, 22100, 200),
(3100, 32100, 200),
],
)
def test_mooncake_derives_device_buffers_from_local_pp_layout(self):
from sglang.srt.disaggregation.mooncake.conn import MooncakeKVManager
manager = object.__new__(MooncakeKVManager)
manager.kv_args = SimpleNamespace(
kv_data_ptrs=[1000, 2000, 3000],
kv_item_lens=[100, 100, 100],
kv_layer_ids=[],
mla_compression_ratios=[4, 128, 4, 128],
prefill_start_layer=0,
prefill_end_layer=2,
)
manager._send_kvcache_generic = MagicMock(return_value=0)
executor = MagicMock()
# send_kvcache reads the memory bag (the unified-memory envelope-layout
# check), so the context has to be published. This is the non-unified
# path -- pin that explicitly rather than leaning on the default.
with get_context().override_server_args(enable_unified_memory=False):
manager.send_kvcache(
"session",
np.array([1], dtype=np.int32),
[10000, 20000, 30000],
np.array([7], dtype=np.int32),
executor,
dst_device_kv_indices=np.array([21], dtype=np.int32),
)
kwargs = manager._send_kvcache_generic.call_args.kwargs
self.assertEqual(kwargs["dst_device_data_ptrs"], {20000, 30000})
def test_mooncake_transfer_metadata_carries_device_page_indices(self):
from sglang.srt.disaggregation.mooncake.conn import TransferInfo
host_pages = np.array([7, 8], dtype=np.int32)
device_pages = np.array([21, 22], dtype=np.int32)
info = TransferInfo.from_zmq(
[
b"9",
b"127.0.0.1",
b"12345",
b"session",
host_pages.tobytes(),
b"0",
b"",
b"1",
b"0",
device_pages.tobytes(),
]
)
np.testing.assert_array_equal(info.dst_kv_indices, host_pages)
np.testing.assert_array_equal(info.dst_device_kv_indices, device_pages)
if __name__ == "__main__":
unittest.main()