config: delete the redundant full stamp in initialize_model_parallel (#39202)

This commit is contained in:
Cheng Wan
2026-09-12 17:27:21 -07:00
committed by GitHub
parent fa260f26da
commit fa663e7297
9 changed files with 283 additions and 73 deletions
@@ -171,7 +171,9 @@ def _sync_srt_tp_group() -> None:
published `srt` config cannot answer: `gpu_worker.py` publishes a dummy
carrying *this* package's `tp_size`, which a sequence-parallel launch sets
to 1 while the group lent here is as wide as the world. So the widths are
stamped alongside the group, as `srt.initialize_model_parallel` does.
permanently overridden alongside the group -- this runs with no `srt`
config published at all, which is exactly why it cannot go through
`RuntimeContext.override` (it requires one).
Only tensor parallelism folds this way, so every other dimension is one.
"""
@@ -183,7 +185,7 @@ def _sync_srt_tp_group() -> None:
if srt_parallel_state._ATTN_TP is None:
srt_parallel_state._ATTN_TP = _TP
if srt_parallel_state._ATTN_TP is _TP:
get_parallel().stamp_derived_widths(
get_parallel().override_permanently(
**derive_parallel_widths(
tp_size=_TP.world_size,
attn_cp_size=1,
@@ -192,7 +194,7 @@ def _sync_srt_tp_group() -> None:
moe_dp_size=1,
dcp_size=1,
dcp_enabled=False,
)
),
)
@@ -590,7 +590,10 @@ class MMEncoder:
distributed_init_method=dist_init_method,
local_rank=rank,
)
initialize_model_parallel(tensor_model_parallel_size=get_parallel().tp_size)
initialize_model_parallel(
tensor_model_parallel_size=get_parallel().tp_size,
attention_context_model_parallel_size=get_parallel().attn_cp_size,
)
initialize_dp_attention(server_args, self.model_config)
self.model = load_model(
@@ -2832,8 +2832,6 @@ def initialize_model_parallel(
group_name="self_pp",
)
get_parallel().stamp_derived_widths(**derived_widths)
def create_custom_parallel_group(
group_ranks: List[int], backend: str = "gloo"
+4 -3
View File
@@ -71,7 +71,7 @@ def update_dp_attention_post_scale(new_dp_size: int, new_dp_rank: int):
global _ATTN_DP_SIZE, _ATTN_DP_RANK
_ATTN_DP_SIZE = new_dp_size
_ATTN_DP_RANK = new_dp_rank
get_parallel().stamp_derived_widths(attn_dp_size=new_dp_size)
get_parallel().override_permanently(attn_dp_size=new_dp_size)
get_flags().dp.use_world_group_for_gather = True
logger.debug(
"[Elastic EP] dp_attention switched to WORLD: dp_size=%d dp_rank=%d",
@@ -350,7 +350,8 @@ def compute_dp_attention_world_info(
"""This rank's place in the attention topology, plus the widths it sits in.
The widths come from `derive_attention_widths`; what this adds is the two
ranks, which are per-process and so are not part of the stamped set.
ranks, which are per-process and so are not among the widths
`override_permanently` records.
"""
attn_dp_size, attn_tp_size = derive_attention_widths(
tp_size=tp_size,
@@ -391,7 +392,7 @@ def initialize_dp_attention(
_, _, _ATTN_DP_RANK, _ATTN_DP_SIZE = compute_dp_attention_world_info(
enable_dp_attention, tp_rank, tp_size, dp_size, attn_cp_size
)
get_parallel().stamp_derived_widths(attn_dp_size=_ATTN_DP_SIZE)
get_parallel().override_permanently(attn_dp_size=_ATTN_DP_SIZE)
if get_exec().moe.elastic_ep_backend is not None and get_parallel().max_ep_size:
_ATTN_DP_RANK = tp_rank + get_parallel().ep_join_rank_offset
+26 -22
View File
@@ -164,7 +164,7 @@ def derive_parallel_widths(
`world_size` is not among them: it is not a quotient, and `get_world_size()`
answers with the live WORLD group, which stays right through an elastic
scale-up that a stamp taken at group build would not survive.
scale-up that a value fixed at group build would not survive.
"""
return {
"attn_dp_size": attn_dp_size,
@@ -268,7 +268,7 @@ class ParallelContext:
def __init__(self):
self._overrides = {}
self._config = None # parallel config bag, wired at publish
self._derived = {} # widths stamped when the groups are built
self._derived = {} # widths overridden permanently, as the groups are built
def __getattr__(self, name):
if name.startswith("_"):
@@ -291,14 +291,17 @@ class ParallelContext:
overrides = self._overrides
return overrides[name] if name in overrides else getter()
def stamp_derived_widths(self, **widths) -> None:
"""Record the widths derived from the leaves, as the groups are built.
def override_permanently(self, **widths) -> None:
"""Permanently correct a derived width the published bag can't answer
or no longer answers correctly -- not `RuntimeContext.override`,
because a derived width is not a resolved config leaf and this must
work with no config published at all (`multimodal_gen` lends a TP
group to `srt` layers with no `srt` config to publish against).
`initialize_model_parallel` computes the set through
`derive_parallel_widths` and hands it here; `initialize_dp_attention`
stamps `attn_dp_size` again once it knows the effective width, and
elastic EP restamps it where it already updates the live one. A stamped
width is what the readers answer with.
Lives beside, not inside, the `@contextmanager` `override` above -- a
name it cannot also have on this class -- because these are permanent
for the process, not scoped to a `with` block: none of the real
callers ever restore the value they set here.
"""
self._derived.update(widths)
@@ -306,13 +309,13 @@ class ParallelContext:
self._derived.clear()
def _derived_width(self, name):
"""A width the configuration implies: override, else stamp, else the
published leaf.
"""A width the configuration implies: scoped override, else permanent
override, else the published leaf.
The leaf is computed at publish by `parallel_widths_of`; the stamp sits
above it because an elastic scale-up restamps `attn_dp_size` after
publish, and a scope that swaps in another TP group states the quotients
through `override`.
The leaf is computed at publish by `parallel_widths_of`; the permanent
override sits above it because an elastic scale-up corrects
`attn_dp_size` after publish, and a scope that swaps in another TP
group states the quotients through the scoped `override` above that.
Nothing is recomputed on read, so overriding `tp_size` does not move
`attn_tp_size`: name the width, or publish a config.
@@ -328,10 +331,10 @@ class ParallelContext:
return getattr(config, name)
raise RuntimeError(
f"derived parallel width {name!r} is not available: it is computed "
"from the configured leaves at publish, and restamped when the "
"process groups are built. Nothing is published and nothing has "
"been stamped -- publish a parallel config, or state the width "
f"with get_parallel().override({name}=...)"
"from the configured leaves at publish, and permanently corrected "
"when the process groups are built. Nothing is published and "
"nothing has been set with override_permanently -- publish a "
f"parallel config, or state the width with get_parallel().override({name}=...)"
)
@contextmanager
@@ -1754,9 +1757,10 @@ def reset_context() -> None:
"""Clear the context-owned store (unit-test teardown): drop the published
``server_args`` and install fresh ``Flags`` and ``Resources``.
``parallel`` holds the stamped derived widths, which go with the lifecycle
that stamped them: `_derived_width` prefers the stamp over the leaves, so
leaving one behind lets the next test read the previous topology.
``parallel`` holds the permanently-overridden derived widths, which go
with the lifecycle that set them: `_derived_width` prefers them over the
published leaves, so leaving one behind lets the next test read the
previous topology.
"""
_CONTEXT._server_args = None
_CONTEXT._config_bags = None
+14 -8
View File
@@ -20,14 +20,9 @@ from sglang.test.test_utils import CustomTestCase
class TestFlashinferDispatcher(CustomTestCase):
@classmethod
def setUpClass(cls):
server_args = ServerArgs(model_path="dummy")
server_args.moe_runner_backend = "flashinfer_cutlass"
server_args.moe_a2a_backend = "flashinfer"
cls.server_args = server_args
set_global_server_args_for_scheduler(server_args)
publish(server_args, role="scheduler")
initialize_moe_config()
# Dist-init first: world_size (and so the tp/ep width ServerArgs must
# carry) is only known after it, and init_distributed_environment
# itself reads no published config.
init_distributed_environment(
world_size=-1, # Auto-detect from environment
rank=-1, # Auto-detect from environment
@@ -38,6 +33,17 @@ class TestFlashinferDispatcher(CustomTestCase):
rank = torch.distributed.get_rank()
device = torch.device(f"cuda:{rank % torch.cuda.device_count()}")
torch.cuda.set_device(device)
server_args = ServerArgs(
model_path="dummy", tp_size=world_size, ep_size=world_size
)
server_args.moe_runner_backend = "flashinfer_cutlass"
server_args.moe_a2a_backend = "flashinfer"
cls.server_args = server_args
set_global_server_args_for_scheduler(server_args)
publish(server_args, role="scheduler")
initialize_moe_config()
initialize_model_parallel(
tensor_model_parallel_size=world_size, expert_model_parallel_size=world_size
)
@@ -212,6 +212,13 @@ def _worker_main(local_rank: int, world_size: int):
set_global_server_args_for_scheduler(
ServerArgs(
model_path="dummy",
# Match the tp/ep width initialize_model_parallel is about to
# build below -- get_parallel()'s derived widths (attn_tp_size,
# moe_ep_size, ...) are projected from this at publish time, and
# nothing here should leave that projection reflecting a width
# this process never actually runs at.
tp_size=world_size,
ep_size=world_size,
)
)
@@ -0,0 +1,67 @@
"""MMEncoder must forward attn_cp_size to initialize_model_parallel, not just
tp_size.
Real 2-GPU hardware confirmed a live mismatch this test guards against
statically: with `tp_size=2, attn_cp_size=2` published, calling
`initialize_model_parallel(tensor_model_parallel_size=2)` alone builds the
live attention-TP group at width 2, while `get_parallel().attn_tp_size`
(derived from the published config) answers 1 -- `VisionAttention`
(`layers/attention/vision.py`) reads that derived value as its own
weight-sharding width, so the mismatch is a real, silent wrong-sharding bug,
not just a reporting discrepancy. Forwarding
`attention_context_model_parallel_size=get_parallel().attn_cp_size` too
makes the two agree (confirmed on the same hardware).
A full `MMEncoder` instantiation needs real weights and a live process
group, so this checks the one line that matters statically: the call passes
`attention_context_model_parallel_size` as well as
`tensor_model_parallel_size`. Not a substitute for testing `MMEncoder`
end-to-end under `--attn-cp-size > 1` on real hardware, but cheap enough to
run everywhere and catches the specific regression class (a future edit
that reverts to the tp-only call).
"""
import ast
import os
import sglang.srt.disaggregation.encoder.server as encoder_server_module
from sglang.test.ci.ci_register import register_cpu_ci
from sglang.test.test_utils import CustomTestCase
register_cpu_ci(est_time=5, suite="base-a-test-cpu")
class TestMMEncoderForwardsAttnCpSize(CustomTestCase):
def test_initialize_model_parallel_call_forwards_attn_cp_size(self):
path = encoder_server_module.__file__
tree = ast.parse(open(path).read())
calls = [
node
for node in ast.walk(tree)
if isinstance(node, ast.Call)
and isinstance(node.func, ast.Name)
and node.func.id == "initialize_model_parallel"
]
self.assertEqual(
len(calls),
1,
f"expected exactly one initialize_model_parallel(...) call in "
f"{os.path.basename(path)}, found {len(calls)} -- update this "
"test if that's now intentional",
)
kwarg_names = {kw.arg for kw in calls[0].keywords}
self.assertIn(
"attention_context_model_parallel_size",
kwarg_names,
"MMEncoder's initialize_model_parallel(...) call must forward "
"attention_context_model_parallel_size (not just "
"tensor_model_parallel_size), or get_parallel().attn_tp_size "
"silently disagrees with the group actually built whenever "
"--attn-cp-size > 1 -- confirmed on real 2-GPU hardware",
)
if __name__ == "__main__":
import unittest
unittest.main()
+156 -34
View File
@@ -1375,7 +1375,8 @@ class TestParallelLeafReads(_IsolatedServerArgs):
class TestDerivedWidths(_IsolatedOverrides):
"""The widths no flag sets are computed from the leaves and stamped.
"""The widths no flag sets are computed from the leaves and permanently
overridable.
`attn_tp_size` and its siblings used to be read back off the group
coordinator that was built from them, which made the answer depend on
@@ -1390,7 +1391,7 @@ class TestDerivedWidths(_IsolatedOverrides):
self.addCleanup(
lambda: (
parallel.clear_derived_widths(),
parallel.stamp_derived_widths(**self._saved_derived),
parallel.override_permanently(**self._saved_derived),
)
)
@@ -1439,13 +1440,14 @@ class TestDerivedWidths(_IsolatedOverrides):
get_parallel().attn_tp_size
self.assertIn("not available", str(caught.exception))
def test_a_stamp_and_a_live_group_both_win_over_the_leaves(self):
"""Order is stamp, then live group, then the leaves. Where a group
exists it is the truth -- elastic scale-up moves the group without
restamping -- so the leaf derivation only answers where there is none.
def test_a_permanent_override_and_a_live_group_both_win_over_the_leaves(self):
"""Order is permanent override, then live group, then the leaves.
Where a group exists it is the truth -- elastic scale-up moves the
group without a fresh override -- so the leaf derivation only
answers where there is none.
"""
parallel = get_parallel()
parallel.stamp_derived_widths(attn_tp_size=7)
parallel.override_permanently(attn_tp_size=7)
self.addCleanup(parallel.clear_derived_widths)
with parallel.override(tp_size=8, attn_dp_size=2):
self.assertEqual(parallel.attn_tp_size, 7)
@@ -1464,9 +1466,9 @@ class TestDerivedWidths(_IsolatedOverrides):
self.assertEqual(widths["moe_tp_size"], 8 // 4 // 2)
self.assertEqual(widths["attn_dcp_size"], 1)
def test_the_world_size_is_not_stamped(self):
def test_the_world_size_is_not_permanently_overridden(self):
"""It is not a quotient, and the live getter is right at every moment.
A stamp taken when the groups are built would answer with the launch
A value fixed when the groups are built would answer with the launch
count after `try_admit_scale_ranks` expands WORLD, and with the joining
cohort's own width on a scale-joiner, which lays its groups out at
`tp * pp` while WORLD spans `ep_join_rank_offset + tp * pp`."""
@@ -1481,31 +1483,30 @@ class TestDerivedWidths(_IsolatedOverrides):
)
self.assertNotIn("world_size", widths)
parallel = get_parallel()
parallel.stamp_derived_widths(attn_tp_size=4)
parallel.override_permanently(attn_tp_size=4)
with patch(f"{_PS}.get_world_size", return_value=9):
self.assertEqual(parallel.world_size, 9)
def test_a_stamped_width_is_what_the_reader_answers_with(self):
def test_a_permanently_overridden_width_is_what_the_reader_answers_with(self):
parallel = get_parallel()
parallel.stamp_derived_widths(attn_tp_size=4, moe_tp_size=1)
parallel.override_permanently(attn_tp_size=4, moe_tp_size=1)
with patch(
f"{_PS}.get_attn_tensor_model_parallel_world_size",
side_effect=AssertionError("the group must not be asked"),
):
self.assertEqual(parallel.attn_tp_size, 4)
def test_an_override_still_wins_over_the_stamp(self):
def test_a_scoped_override_still_wins_over_the_permanent_one(self):
parallel = get_parallel()
parallel.stamp_derived_widths(attn_tp_size=4)
parallel.override_permanently(attn_tp_size=4)
with parallel.override(attn_tp_size=1):
self.assertEqual(parallel.attn_tp_size, 1)
self.assertEqual(parallel.attn_tp_size, 4)
def test_the_group_is_never_consulted(self):
"""There is no third source. A quotient comes from an override, a stamp
or the published leaf -- never from a group coordinator, which could
only ever agree, since `initialize_model_parallel` stamps as its last
statement."""
"""There is no third source. A quotient comes from a scoped override, a
permanent override, or the published leaf -- never from a group
coordinator."""
reset_context()
self.addCleanup(reset_context)
with patch(
@@ -1528,50 +1529,51 @@ class TestDerivedWidths(_IsolatedOverrides):
with self.assertRaisesRegex(RuntimeError, r"derived parallel width"):
get_parallel().attn_tp_size
def test_a_temporary_disable_beats_the_stamp(self):
def test_a_temporary_disable_beats_the_permanent_override(self):
"""`disable_dp_size()` runs a draft scope without DP attention. It moves
the module global the legacy getter reads, so it has to move the derived
width too -- the stamp wins over the live group, and a scope that left
it alone would answer with the target model's width for its duration."""
width too -- the scoped override wins over the permanent one, and a
scope that left it alone would answer with the target model's width
for its duration."""
from sglang.srt.layers import dp_attention
parallel = get_parallel()
parallel.stamp_derived_widths(attn_dp_size=4)
parallel.override_permanently(attn_dp_size=4)
with patch.object(dp_attention, "_ATTN_DP_SIZE", 4):
with dp_attention.disable_dp_size():
self.assertEqual(dp_attention.get_attention_dp_size(), 1)
self.assertEqual(parallel.attn_dp_size, 1)
self.assertEqual(parallel.attn_dp_size, 4)
def test_the_stamp_is_cleared_and_restamped(self):
def test_the_permanent_override_is_cleared_and_reset(self):
parallel = get_parallel()
parallel.stamp_derived_widths(attn_dp_size=2)
parallel.override_permanently(attn_dp_size=2)
self.assertEqual(parallel.attn_dp_size, 2)
# Elastic scaling restamps where it updates the live width.
parallel.stamp_derived_widths(attn_dp_size=4)
# Elastic scaling overrides again where it updates the live width.
parallel.override_permanently(attn_dp_size=4)
self.assertEqual(parallel.attn_dp_size, 4)
parallel.clear_derived_widths()
with parallel.override(tp_size=8, attn_dp_size=1):
self.assertEqual(parallel.attn_dp_size, 1)
def test_reset_context_drops_the_stamp(self):
"""The stamp belongs to the lifecycle that made it.
def test_reset_context_drops_the_permanent_override(self):
"""The permanent override belongs to the lifecycle that made it.
`_derived_width` prefers the stamp over the published leaf, so a stamp
that outlived `reset_context()` would let the next test read the
previous topology.
`_derived_width` prefers it over the published leaf, so one that
outlived `reset_context()` would let the next test read the previous
topology.
"""
parallel = get_parallel()
parallel.stamp_derived_widths(attn_tp_size=4)
parallel.override_permanently(attn_tp_size=4)
self.assertEqual(parallel.attn_tp_size, 4)
reset_context()
self.addCleanup(reset_context)
publish(ServerArgs(model_path="dummy", tp_size=1), role="test")
self.assertEqual(get_parallel().attn_tp_size, 1)
def test_the_rank_helper_agrees_with_the_stamp(self):
def test_the_rank_helper_agrees_with_the_override(self):
"""`compute_dp_attention_world_info` keeps the ranks and takes the
widths from the same derivation the stamp uses."""
widths from the same derivation `override_permanently`'s callers use."""
from sglang.srt.layers.dp_attention import compute_dp_attention_world_info
for tp_size, dp_size, attn_cp_size in ((8, 2, 1), (8, 2, 2), (16, 4, 2)):
@@ -1590,6 +1592,126 @@ class TestDerivedWidths(_IsolatedOverrides):
self.assertEqual(attn_tp_size, widths["attn_tp_size"])
self.assertEqual(attn_dp_size, widths["attn_dp_size"])
def test_recomputing_from_published_leaves_matches_the_publish_bag(self):
"""`initialize_model_parallel` no longer overrides anything -- see
`test_initialize_model_parallel_no_longer_touches_the_bag` below --
which makes this the load-bearing half of 16-field-registry-design.md
§6e: every real caller must forward leaves that already match its own
published config, because nothing corrects a mismatch anymore.
`scheduler.py`'s `ps.attn_dp_size`/`ps.moe_ep_size`/etc, and the
weight-cache daemon's own already-published config, both do -- this
pins that the formula they'd recompute from those leaves
(`derive_attention_widths`, `derive_parallel_widths`, the same ones
`publish` itself used) agrees with what's already in the bag, across
the widths `test_the_rank_helper_agrees_with_the_override` does not
vary -- moe_ep_size, moe_dp_size, and dcp_size -- using real
`publish()`.
A caller that does NOT keep the two in sync is a bug in that caller,
not something this framework silently corrects: two real ones existed
(`test/registered/eplb/test_lplb_distributed.py` and
`test/manual/ep/test_flashinfer_dispatcher.py`, both publishing a
placeholder config and then building real groups at a width it never
reflected) and were fixed by publishing the actual width instead of
relying on a correction to paper over the mismatch.
"""
shapes = (
dict(tp_size=8),
dict(tp_size=8, dp_size=2, enable_dp_attention=True),
dict(tp_size=8, ep_size=4, moe_dp_size=2),
dict(tp_size=8, dcp_size=8),
)
for shape in shapes:
with self.subTest(shape=shape):
reset_context()
self.addCleanup(reset_context)
publish(ServerArgs(model_path="dummy", **shape), role="test")
parallel = get_parallel()
published = {
"attn_tp_size": parallel.attn_tp_size,
"attn_dp_size": parallel.attn_dp_size,
"moe_ep_size": parallel.moe_ep_size,
"moe_tp_size": parallel.moe_tp_size,
"dcp_enabled": parallel.dcp_enabled,
"attn_dcp_size": parallel.attn_dcp_size,
}
# What every real `initialize_model_parallel` caller forwards:
# its own already-published leaves, through the same two
# functions the bag was projected with.
recomputed = derive_parallel_widths(
tp_size=parallel.tp_size,
attn_cp_size=parallel.attn_cp_size,
attn_dp_size=(
parallel.dp_size if parallel.enable_dp_attention else 1
),
moe_ep_size=parallel.ep_size,
moe_dp_size=parallel.moe_dp_size,
dcp_size=parallel.dcp_size,
dcp_enabled=parallel.dcp_size > 1,
)
self.assertEqual(published, recomputed)
def test_initialize_model_parallel_no_longer_touches_the_bag(self):
"""§6e, landed: `initialize_model_parallel` used to recompute and
permanently override the six derived widths on `get_parallel()`
after building its groups; that call is gone. Publish a placeholder
config (tp_size defaults to 1), then build real groups at a
different width -- the published leaf must now stay exactly what it
was, because nothing corrects it. This is the behavior a caller
relies on being told about, loudly, the first time it publishes and
builds inconsistently -- see
`test_recomputing_from_published_leaves_matches_the_publish_bag`
for why every real caller must not do that.
"""
from unittest.mock import Mock
from sglang.srt.distributed import parallel_state
reset_context()
self.addCleanup(reset_context)
publish(ServerArgs(model_path="dummy"), role="test")
self.assertEqual(get_parallel().attn_tp_size, 1)
self.assertEqual(get_parallel().moe_ep_size, 1)
world_size = 8
with (
patch.object(parallel_state, "_WORLD", None),
patch.object(parallel_state, "_TP", None),
patch.object(parallel_state, "_DCP", None),
patch.object(parallel_state, "_ATTN_CP", None),
patch.object(parallel_state, "_ATTN_TP", None),
patch.object(parallel_state, "_MOE_DP", None),
patch.object(parallel_state, "_MOE_EP", None),
patch.object(parallel_state, "_MOE_TP", None),
patch.object(parallel_state, "_PP", None),
patch.object(parallel_state, "_SELF_PP", None),
patch("torch.distributed.is_initialized", return_value=True),
patch("torch.distributed.get_world_size", return_value=world_size),
patch("torch.distributed.get_rank", return_value=0),
patch("torch.distributed.get_backend", return_value="nccl"),
patch.object(
parallel_state,
"init_model_parallel_group",
return_value=Mock(device_group=Mock()),
),
patch.object(parallel_state, "get_world_group") as mock_world_group,
):
mock_world_group.return_value = Mock(device_group=Mock(), local_rank=0)
parallel_state.initialize_model_parallel(
tensor_model_parallel_size=world_size,
expert_model_parallel_size=world_size,
)
self.addCleanup(parallel_state.destroy_model_parallel)
self.assertEqual(
get_parallel().attn_tp_size,
1,
"initialize_model_parallel must not touch the published leaf -- "
"a caller that needs it corrected must publish a config that "
"already matches the width it is about to build",
)
self.assertEqual(get_parallel().moe_ep_size, 1)
class TestTheDerivedHalfIsDeclared(CustomTestCase):
"""The quotients are declared beside the leaves, in the same class.