[Fix][DCP] Localize widened KV ids in MLA retraction CPU backup/restore (#39487)
Co-authored-by: Claude Fable 5.1 <noreply@anthropic.com>
This commit is contained in:
co-authored by
Claude Fable 5.1
parent
ddd4600197
commit
2c37b90ad6
@@ -9,9 +9,14 @@ from sglang.srt.mem_cache.cache_init_params import CacheInitParams
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from sglang.srt.mem_cache.common import retraction_backup
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from sglang.srt.mem_cache.hicache_storage import PoolName
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from sglang.srt.mem_cache.kv_cache_builder import maybe_register_hicache_draft
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from sglang.srt.mem_cache.memory_pool import MHATokenToKVPool, ReqToTokenPool
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from sglang.srt.mem_cache.memory_pool import (
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MHATokenToKVPool,
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MLATokenToKVPool,
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ReqToTokenPool,
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)
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from sglang.srt.mem_cache.unified_cache.components import ComponentType
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from sglang.srt.mem_cache.unified_radix_cache import UnifiedRadixCache
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from sglang.srt.runtime_context import get_parallel
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from sglang.srt.server_args import ServerArgs, set_global_server_args_for_scheduler
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from sglang.srt.speculative.base_spec_worker import (
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HiCacheDraftMode,
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@@ -215,5 +220,67 @@ class TestDecodeRetractionBackup(unittest.TestCase):
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req_to_token_pool.free(req)
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DCP_SIZE = 4
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DCP_RANK = 1
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DCP_ROWS = 8
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def _bare_mla_pool() -> MLATokenToKVPool:
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pool = object.__new__(MLATokenToKVPool)
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pool.layer_num = 2
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pool.cpu_offloading_chunk_size = 3
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pool.kv_buffer = [
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(torch.arange(DCP_ROWS, dtype=torch.float32) + 100 * layer).view(DCP_ROWS, 1, 1)
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for layer in range(pool.layer_num)
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]
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return pool
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def _dcp():
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return get_parallel().override(
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dcp_enabled=True, attn_dcp_size=DCP_SIZE, attn_dcp_rank=DCP_RANK
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)
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class TestDcpRetractionBackup(unittest.TestCase):
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"""`req_to_token` names KV slots in the widened DCP id space while
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`kv_buffer` holds only this rank's rows; a widened id used as a row index
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reads past the buffer or copies another token's row."""
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def test_restore_lands_on_new_owned_rows(self):
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pool = _bare_mla_pool()
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before = [buf.clone() for buf in pool.kv_buffer]
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old_widened = torch.arange(0, 12, dtype=torch.int64)
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new_widened = torch.arange(12, 24, dtype=torch.int64)
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with _dcp():
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pool.load_cpu_copy(pool.get_cpu_copy(old_widened), new_widened)
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old_rows = old_widened[DCP_RANK::DCP_SIZE] // DCP_SIZE
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new_rows = new_widened[DCP_RANK::DCP_SIZE] // DCP_SIZE
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self.assertEqual(new_rows.tolist(), [3, 4, 5])
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untouched = torch.tensor(
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[r for r in range(DCP_ROWS) if r not in new_rows.tolist()]
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)
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for layer in range(pool.layer_num):
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torch.testing.assert_close(
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pool.kv_buffer[layer][new_rows], before[layer][old_rows]
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)
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torch.testing.assert_close(
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pool.kv_buffer[layer][untouched], before[layer][untouched]
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)
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def test_resolved_pool_takes_ids_as_rows(self):
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pool = _bare_mla_pool()
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pool.write_loc_is_dcp_resolved = True
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rows = torch.arange(DCP_ROWS, dtype=torch.int64)
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with _dcp():
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kv_cpu = pool.get_cpu_copy(rows)
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for layer in range(pool.layer_num):
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torch.testing.assert_close(torch.cat(kv_cpu[layer]), pool.kv_buffer[layer])
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if __name__ == "__main__":
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unittest.main()
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@@ -16,6 +16,7 @@ from unittest import mock
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import torch
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from sglang.srt.layers.dcp.layout import maybe_dcp_kernel_indices
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from sglang.srt.mem_cache.pool_host.mla import MLATokenToKVPoolHost
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from sglang.test.ci.ci_register import register_cpu_ci
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from sglang.test.test_utils import CustomTestCase
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@@ -57,24 +58,16 @@ def _make_host_pool(dcp_rank: int, device_size: int = 1024) -> MLATokenToKVPoolH
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class TestDcpKernelIndices(CustomTestCase):
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def _bare_pool(self, dcp_size: int, dcp_rank: int) -> MLATokenToKVPoolHost:
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pool = MLATokenToKVPoolHost.__new__(MLATokenToKVPoolHost)
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pool.dcp_size = dcp_size
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pool.dcp_rank = dcp_rank
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return pool
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def test_identity_without_dcp(self):
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pool = self._bare_pool(1, 0)
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indices = torch.arange(37)
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self.assertIs(pool.maybe_dcp_kernel_indices(indices), indices)
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self.assertIs(maybe_dcp_kernel_indices(indices, 1, 0), indices)
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def test_aligned_page_translates_to_full_physical_page(self):
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# One widened page starting at logical 512 covers physical rows
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# 64..127 on every rank.
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indices = torch.arange(WIDENED_PAGE, 2 * WIDENED_PAGE)
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for rank in range(DCP_SIZE):
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pool = self._bare_pool(DCP_SIZE, rank)
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out = pool.maybe_dcp_kernel_indices(indices)
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out = maybe_dcp_kernel_indices(indices, DCP_SIZE, rank)
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torch.testing.assert_close(
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out, torch.arange(PHYSICAL_PAGE, 2 * PHYSICAL_PAGE)
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)
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@@ -87,19 +80,13 @@ class TestDcpKernelIndices(CustomTestCase):
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[torch.arange(p * WIDENED_PAGE, (p + 1) * WIDENED_PAGE) for p in pages]
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)
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for rank in range(DCP_SIZE):
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pool = self._bare_pool(DCP_SIZE, rank)
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out = pool.maybe_dcp_kernel_indices(indices)
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out = maybe_dcp_kernel_indices(indices, DCP_SIZE, rank)
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expected = (
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indices[indices % DCP_SIZE == rank] // DCP_SIZE
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) # owner rule, same as filter_dcp_local_kv_indices
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torch.testing.assert_close(out, expected)
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self.assertEqual(out.numel() * DCP_SIZE, indices.numel())
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def test_ragged_run_is_rejected(self):
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pool = self._bare_pool(DCP_SIZE, 0)
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with self.assertRaises(AssertionError):
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pool.maybe_dcp_kernel_indices(torch.arange(WIDENED_PAGE + 1))
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def test_positional_residue_pairing_survives_host_sort(self):
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# move_indices (direct/layer_first) sorts host indices and permutes
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# device indices to match. Independent residue filtering of both
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@@ -122,13 +109,12 @@ class TestDcpKernelIndices(CustomTestCase):
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host_sorted, order = host[perm].sort()
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device_matched = device[perm][order]
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for rank in range(DCP_SIZE):
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pool = self._bare_pool(DCP_SIZE, rank)
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host_mask = host_sorted % DCP_SIZE == rank
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device_mask = device_matched % DCP_SIZE == rank
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# same positions selected on both sides -> pairing preserved
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torch.testing.assert_close(host_mask, device_mask)
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self.assertEqual(
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pool.maybe_dcp_kernel_indices(host_sorted).numel(),
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maybe_dcp_kernel_indices(host_sorted, DCP_SIZE, rank).numel(),
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host.numel() // DCP_SIZE,
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)
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