Empty _REQ_TYPES_WITH_OPAQUE_FIELDS on the msgpack IPC path (#29465 Task 4) (#30182)

This commit is contained in:
Jorge António
2026-07-15 14:55:06 -07:00
committed by GitHub
parent 67148447a6
commit 26cb0fcdda
12 changed files with 383 additions and 73 deletions
+3
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@@ -283,3 +283,6 @@ test/registered/xpu/test_nvidia_nemotron_3_nano.py
artifacts/
.claude/scheduled_tasks.lock
.humanize/
# Internal, non-published docs
internal-docs/
@@ -159,12 +159,10 @@ class ExpertBackupClient:
param = param.narrow(
0, param.shape[0] // 2, param.shape[0] // 2
)
server_ptr_list.append(weight_info["weight_ptr"])
server_ptr_list.append(weight_info.weight_ptr)
local_ptr_list.append(param.data_ptr())
assert (
param.numel() * param.element_size() == weight_info["byte_size"]
)
weight_size_list.append(weight_info["byte_size"])
assert param.numel() * param.element_size() == weight_info.byte_size
weight_size_list.append(weight_info.byte_size)
before_transfer = time.time()
ret = self.transfer_engine.engine.batch_transfer_sync_read(
self.session_id_list[i],
@@ -9,7 +9,12 @@ import zmq
from sglang.srt.configs.load_config import LoadConfig
from sglang.srt.configs.model_config import ModelConfig
from sglang.srt.environ import envs
from sglang.srt.managers.io_struct import BackupDramReq, sock_recv, sock_send
from sglang.srt.managers.io_struct import (
BackupDramReq,
ExpertWeightPointer,
sock_recv,
sock_send,
)
from sglang.srt.model_loader.loader import DefaultModelLoader, get_model_loader
from sglang.srt.model_loader.utils import set_default_torch_dtype
from sglang.srt.server_args import (
@@ -128,15 +133,10 @@ class ExpertBackupManager:
end_byte = current_byte_offset + byte_size
weight_ptr = buffer_base_ptr + current_byte_offset
self.continuous_buffer[start_byte:end_byte].copy_(weight_bytes)
self.weight_pointer_map[name] = {
"name": name,
"weight_ptr": weight_ptr,
"shape": weight_info["shape"],
"numel": weight_info["numel"],
"dtype": weight_info["dtype"],
"element_size": weight_info["element_size"],
"byte_size": byte_size,
}
self.weight_pointer_map[name] = ExpertWeightPointer(
weight_ptr=weight_ptr,
byte_size=byte_size,
)
current_byte_offset = end_byte
@@ -797,6 +797,11 @@ if os.environ.get("DUMPER_SERVER_PORT") == "reuse":
async def _dumper_control_handler(method: str, request: Request):
body_bytes = await request.body()
body = await request.json() if body_bytes else {}
if not isinstance(body, dict):
return ORJSONResponse(
status_code=400,
content={"error": "Request body must be a JSON object."},
)
obj = DumperControlReqInput(method=method, body=body)
results = await _global_state.tokenizer_manager.dumper_control(obj)
if any(not r.success for r in results):
+1
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@@ -235,6 +235,7 @@ class Envs:
# IPC
SGLANG_USE_PICKLE_IPC = EnvBool(True)
# Log top-level PickleWrapper frames unwrapped on msgpack IPC decode.
SGLANG_LOG_PICKLE_IPC_OBJECTS = EnvBool(False)
# SGLang CI
+52 -42
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@@ -1551,7 +1551,7 @@ class UpdateWeightFromDiskReqInput(BaseReq, kw_only=True):
token_step: int = 0
# Whether to flush the cache after updating weights
flush_cache: bool = True
# Tensor metadata
# Tensor metadata from the JSON request body, so it is already msgpack-native.
manifest: Optional[Dict[str, Any]] = None
@@ -1669,9 +1669,17 @@ class UpdateExpertBackupReq(BaseReq, kw_only=True):
pass
class ExpertWeightPointer(msgspec.Struct, kw_only=True, array_like=True):
# One expert weight's pointer + byte length in the DRAM backup buffer.
# array_like: the map has tens of thousands of entries, so positional
# encoding drops the repeated field names from the wire.
weight_ptr: int
byte_size: int
class BackupDramReq(BaseReq, kw_only=True):
rank: int
weight_pointer_map: Dict[str, Any]
weight_pointer_map: Dict[str, ExpertWeightPointer]
session_id: str
buffer_size: int
@@ -1718,7 +1726,9 @@ class GetWeightsByNameReqInput(BaseReq, kw_only=True):
class GetWeightsByNameReqOutput(BaseReq, kw_only=True):
parameter: Optional[List[Any]]
# A flat List[float] or a per-row List[List[float]]. The union is on the
# element: Union[List[float], List[List[float]]] is invalid msgspec.
parameter: Optional[List[Union[float, List[float]]]]
class ReleaseMemoryOccupationReqInput(BaseReq, kw_only=True):
@@ -1746,10 +1756,32 @@ class CheckWeightsReqInput(BaseReq, kw_only=True):
allow_quant_error: bool = False
# Wire versions of the pydantic ParallelismInfo/ChecksumInfo in
# sglang.srt.utils.weight_checker. Not array_like: the payload is read by field
# name and re-serialized to JSON, so it must stay a {field: value} map.
class ParallelismInfo(msgspec.Struct, kw_only=True):
tp_rank: int
tp_size: int
dp_rank: int
dp_size: int
pp_rank: int
pp_size: int
rank: int
size: int
class ChecksumInfo(msgspec.Struct, kw_only=True):
checksums: Dict[str, str]
per_gpu_checksum: str
parallelism_info: ParallelismInfo
class CheckWeightsReqOutput(BaseReq, kw_only=True):
success: bool
message: str
payload: Optional[Dict[str, Any]] = None
# One ChecksumInfo per TP rank. The producer wraps the tp==1 result in a
# one-element list so the shape is always a list.
payload: Optional[List[ChecksumInfo]] = None
class SlowDownReqInput(BaseReq, kw_only=True):
@@ -1782,16 +1814,19 @@ class GetInternalStateReq(BaseReq, kw_only=True):
class GetInternalStateReqOutput(BaseReq, kw_only=True):
# A vars() dump of ServerArgs, left untyped because a struct would drift. The
# producer sanitizes it with msgspec_to_builtins so every value is
# msgpack-native.
internal_state: Dict[str, Any]
class SetInternalStateReq(BaseReq, kw_only=True):
server_args: Dict[str, Any]
# Only numeric scheduler knobs are accepted (see Scheduler.set_internal_state).
server_args: Dict[str, Union[int, float]]
class SetInternalStateReqOutput(BaseReq, kw_only=True):
updated: bool
server_args: Dict[str, Any]
class ProfileReqType(Enum):
@@ -1922,13 +1957,16 @@ class SeparateReasoningReqInput(BaseReq, kw_only=True):
class VertexGenerateReqInput(BaseReq, kw_only=True):
# Both fields come from the JSON request body, so they are already
# msgpack-native.
instances: List[Dict[str, Any]]
parameters: Optional[Dict[str, Any]] = None
class RpcReqInput(BaseReq, kw_only=True):
method: str
parameters: Optional[Dict[str, Any]] = None
# collective_rpc kwargs are flat scalars across all in-tree callers.
parameters: Optional[Dict[str, Union[bool, int, float, str, None]]] = None
class RpcReqOutput(BaseReq, kw_only=True):
@@ -1970,10 +2008,12 @@ class UnloadLoRAAdapterReqInput(BaseReq, kw_only=True):
class LoadLoRAAdapterFromTensorsReqInput(BaseReq, kw_only=True):
lora_name: str
# The PEFT adapter_config.json, already JSON — a tighter type would only add
# decode strictness with no benefit.
config_dict: Dict[str, Any]
serialized_tensors: str
pinned: bool = False
added_tokens_config: Optional[Dict[str, Any]] = None
added_tokens_config: Optional[Dict[str, int]] = None
lora_id: Optional[str] = None
load_format: Optional[str] = None
@@ -2006,10 +2046,6 @@ class BlockReqInput(BaseReq, kw_only=True):
req_type: BlockReqType
class SetInjectDumpMetadataReqInput(BaseReq, kw_only=True):
dump_metadata: Dict[str, Any]
class SetInjectDumpMetadataReqOutput(BaseReq, kw_only=True):
success: bool
@@ -2024,11 +2060,13 @@ class LazyDumpTensorsReqOutput(BaseReq, kw_only=True):
class DumperControlReqInput(BaseReq, kw_only=True):
method: str
# JSON request body (guarded to be a dict at the /dumper endpoint).
body: Dict[str, Any]
class DumperControlReqOutput(BaseReq, kw_only=True):
success: bool
# JSON-native per-worker response dicts.
response: List[Dict[str, Any]]
error: str = ""
@@ -2068,28 +2106,6 @@ def _check_all_req_types():
_check_all_req_types()
# IPC struct types whose fields still use opaque annotations (Any, Dict[str, Any],
# List[Any], etc.) instead of precise types. Keep these on explicit pickle
# transport until their field schemas are tightened, and keep the registry
# explicit so opaque usage can be audited and gradually narrowed.
# NOTE: GenerateReqInput and EmbeddingReqInput are standalone (not BaseReq/
# BaseBatchReq subclasses) and are tracked separately.
_REQ_TYPES_WITH_OPAQUE_FIELDS: tuple[Type[msgspec.Struct], ...] = (
UpdateWeightFromDiskReqInput, # manifest: Optional[Dict[str, Any]]
BackupDramReq, # weight_pointer_map: Dict[str, Any]
GetWeightsByNameReqOutput, # parameter: Optional[List[Any]]
CheckWeightsReqOutput, # payload: Optional[Dict[str, Any]]
GetInternalStateReqOutput, # internal_state: Dict[str, Any]
SetInternalStateReq, # server_args: Dict[str, Any]
SetInternalStateReqOutput, # server_args: Dict[str, Any]
VertexGenerateReqInput, # instances, parameters: Dict[str, Any]
RpcReqInput, # parameters: Optional[Dict[str, Any]]
LoadLoRAAdapterFromTensorsReqInput, # config_dict, added_tokens_config: Dict[str, Any]
SetInjectDumpMetadataReqInput, # dump_metadata: Dict[str, Any]
DumperControlReqInput, # body: Dict[str, Any]
DumperControlReqOutput, # response: List[Dict[str, Any]]
)
def wrap_as_pickle(obj: object) -> object:
if obj is None:
@@ -2180,19 +2196,13 @@ def hook_custom_types(*new_types: Type):
def _maybe_wrap_pickle(obj: Any) -> Any:
if isinstance(obj, _REQ_TYPES_WITH_OPAQUE_FIELDS):
if envs.SGLANG_LOG_PICKLE_IPC_OBJECTS.get():
logger.info(f"Object of type {type(obj)} is wrapped via PickleWrapper.")
return PickleWrapper(pickle.dumps(obj))
if isinstance(obj, (msgspec.Struct, *_primitive_types)):
return obj
raise TypeError(
f"Cannot serialize object of type {type(obj)} over msgpack IPC. "
"Add a precise msgspec-compatible type, use an explicit PickleWrapper "
"field for the opaque payload, or add the struct to "
"_REQ_TYPES_WITH_OPAQUE_FIELDS with an audit comment."
"Add a precise msgspec-compatible type, or use an explicit PickleWrapper "
"field via wrap_as_pickle(...) for the opaque payload."
)
+4 -8
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@@ -3823,8 +3823,10 @@ class Scheduler(
if info_record is not None:
ret["dspark_info_record"] = info_record
# This field is not serializable.
# These fields are not msgpack-serializable (a config object and a bound
# signal handler); no reader consumes them.
ret.pop("model_config", None)
ret.pop("custom_sigquit_handler", None)
return GetInternalStateReqOutput(internal_state=msgspec_to_builtins(ret))
@@ -3906,13 +3908,7 @@ class Scheduler(
get_server_args().override(source="update_server_args", **remaining)
logger.info(f"Global server args updated! {get_server_args()=}")
server_args = dict(vars(get_server_args()))
# This field is not serializable.
server_args.pop("model_config", None)
return SetInternalStateReqOutput(
updated=if_success,
server_args=msgspec_to_builtins(server_args),
)
return SetInternalStateReqOutput(updated=if_success)
def save_remote_model(self, **kwargs):
self.weight_updater.save_remote_model(kwargs)
@@ -8,6 +8,7 @@ from contextlib import contextmanager
from dataclasses import dataclass, field
from typing import Any, Callable, Dict, Iterator, Optional, Tuple
import msgspec
import torch
from sglang.srt.constants import (
@@ -18,6 +19,7 @@ from sglang.srt.constants import (
)
from sglang.srt.disaggregation.utils import DisaggregationMode
from sglang.srt.managers.io_struct import (
ChecksumInfo,
CheckWeightsReqInput,
CheckWeightsReqOutput,
DestroyWeightsUpdateGroupReqInput,
@@ -289,6 +291,11 @@ class SchedulerWeightUpdaterManager:
all_payloads, payload, group=self.tp_cpu_group
)
payload = all_payloads
if payload is not None:
# Normalize to one ChecksumInfo per rank so the wire shape is a
# uniform List[ChecksumInfo] (tp==1 becomes a single-element list).
per_rank = payload if isinstance(payload, list) else [payload]
payload = [msgspec.convert(p, ChecksumInfo) for p in per_rank]
return CheckWeightsReqOutput(
success=True, message="Success.", payload=payload
)
@@ -15,6 +15,7 @@ from sglang.srt.managers.io_struct import (
AddExternalCorpusReqOutput,
AttachHiCacheStorageReqInput,
AttachHiCacheStorageReqOutput,
ChecksumInfo,
CheckWeightsReqInput,
CheckWeightsReqOutput,
ClearHiCacheReqInput,
@@ -77,6 +78,7 @@ from sglang.srt.utils import (
get_bool_env_var,
normalize_serialized_named_tensor_payloads,
)
from sglang.srt.utils.msgspec_utils import msgspec_to_builtins
from sglang.utils import TypeBasedDispatcher
if TYPE_CHECKING:
@@ -760,16 +762,15 @@ class TokenizerControlMixin:
ranks: Optional[List[Dict]] = None
per_engine_checksum: Optional[str] = None
if any(r.payload is not None for r in results):
ranks = []
rank_infos: List[ChecksumInfo] = []
for r in results:
if isinstance(r.payload, list):
ranks.extend(r.payload)
else:
ranks.append(r.payload)
if r.payload is not None:
rank_infos.extend(r.payload)
h = hashlib.sha256()
for rank in ranks:
h.update(rank["per_gpu_checksum"].encode())
for info in rank_infos:
h.update(info.per_gpu_checksum.encode())
per_engine_checksum = h.hexdigest()
ranks = [msgspec_to_builtins(info) for info in rank_infos]
return success, message, ranks, per_engine_checksum
async def slow_down(
+8 -1
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@@ -2,6 +2,7 @@ from __future__ import annotations
import base64
import binascii
import dataclasses
from typing import Any
import msgspec
@@ -35,13 +36,19 @@ class Base64Bytes:
def msgspec_to_builtins(obj: Any) -> Any:
"""Recursively convert msgspec structs to dict/list Python builtins."""
"""Recursively convert msgspec structs and dataclasses to builtins."""
if isinstance(obj, msgspec.Struct):
return {
field.name: msgspec_to_builtins(getattr(obj, field.name))
for field in msgspec.structs.fields(type(obj))
}
if dataclasses.is_dataclass(obj) and not isinstance(obj, type):
return {
f.name: msgspec_to_builtins(getattr(obj, f.name))
for f in dataclasses.fields(obj)
}
if isinstance(obj, dict):
return {key: msgspec_to_builtins(value) for key, value in obj.items()}
@@ -3,6 +3,12 @@ import unittest
import torch
from sglang.srt.environ import envs
from sglang.srt.managers.io_struct import (
GetInternalStateReqOutput,
PickleWrapper,
msgpack_decode,
msgpack_encode,
)
from sglang.srt.speculative.dspark_components.dspark_observability import (
DecodeStepObservation,
DsparkInfoDumper,
@@ -12,6 +18,7 @@ from sglang.srt.speculative.dspark_components.dspark_observability import (
resolve_components,
resolve_enabled_components,
)
from sglang.srt.utils.msgspec_utils import msgspec_to_builtins
from sglang.test.ci.ci_register import register_cpu_ci
from sglang.test.test_utils import CustomTestCase
@@ -394,5 +401,39 @@ class TestReqsAndGpuTiming(CustomTestCase):
self.assertGreater(record["target_verify_gpu_ms"], 0.0)
class TestDumpCrossesMsgpackIpc(CustomTestCase):
"""Guard the DSpark -> GetInternalStateReqOutput serialization contract.
`Scheduler.get_internal_state` stores `draft_worker.dump_info_records()` under
`internal_state["dspark_info_record"]`, then ships the struct over the strict
msgpack IPC path (issue #29465). That path has no PickleWrapper fallback: any
value that is not msgpack-native (a numpy scalar, a torch tensor, an
un-converted `msgspec.Struct`) raises at encode time. The dumper's own tests
assert record *values* -- and `assertEqual(np.int64(3), 3)` passes -- so a
scalar that silently became numpy would escape them but fail this round-trip.
"""
def _real_dump(self):
dumper, clock = make_dumper({"core"})
dumper.observe_decode_step(make_obs(forward_ct=1))
clock.advance(0.01)
dumper.observe_decode_step(make_obs(forward_ct=2))
dumped = dumper.dump()
# DsparkObservability.dump_info_records appends this float onto the raw
# dumper output before the scheduler reads it; mirror the full payload.
dumped["simulate_acc_len"] = 4.0
return dumped
def test_real_dump_output_round_trips_natively(self):
internal_state = msgspec_to_builtins(
{"dspark_info_record": self._real_dump(), "max_running_requests": 256}
)
output = GetInternalStateReqOutput(internal_state=internal_state)
decoded = msgpack_decode(msgpack_encode(output))
self.assertNotIsInstance(decoded, PickleWrapper)
self.assertEqual(decoded, output)
if __name__ == "__main__":
unittest.main()
@@ -0,0 +1,241 @@
"""Round-trip coverage for the IPC structs that used to be pickle-wrapped.
Issue #29465 Task 4 tightened the 13 types in `_REQ_TYPES_WITH_OPAQUE_FIELDS` to
precise msgspec-native annotations and deleted the registry. This test proves
each type now encodes natively over the msgpack IPC path (no `PickleWrapper`
frame) by asserting `msgpack_decode(msgpack_encode(x)) == x`, and guards the
type-specific decisions (the `ExpertWeightPointer` narrowing, the
`CheckWeightsReqOutput` struct mirrors, and the internal-state sanitization).
"""
import dataclasses
import unittest
import msgspec
from sglang.srt.managers import io_struct
from sglang.srt.managers.io_struct import (
BackupDramReq,
ChecksumInfo,
CheckWeightsReqOutput,
DumperControlReqInput,
DumperControlReqOutput,
ExpertWeightPointer,
GetInternalStateReqOutput,
GetWeightsByNameReqOutput,
LoadLoRAAdapterFromTensorsReqInput,
ParallelismInfo,
RpcReqInput,
SetInternalStateReq,
SetInternalStateReqOutput,
UpdateWeightFromDiskReqInput,
VertexGenerateReqInput,
msgpack_decode,
msgpack_encode,
)
from sglang.srt.model_executor.cuda_graph_config import CudaGraphConfig
from sglang.srt.utils.msgspec_utils import msgspec_to_builtins
from sglang.srt.utils.weight_checker import ChecksumInfo as PydanticChecksumInfo
from sglang.srt.utils.weight_checker import ParallelismInfo as PydanticParallelismInfo
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-c-test-cpu")
def _round_trip(obj):
return msgpack_decode(msgpack_encode(obj))
def _double_hop(obj):
# MultiTokenizerRouter and the DP controller re-encode already-decoded
# structs, so a single hop cannot catch re-encode bugs.
return msgpack_decode(msgpack_encode(msgpack_decode(msgpack_encode(obj))))
def _contains_dataclass(obj) -> bool:
if dataclasses.is_dataclass(obj) and not isinstance(obj, type):
return True
if isinstance(obj, dict):
return any(_contains_dataclass(v) for v in obj.values())
if isinstance(obj, (list, tuple, set)):
return any(_contains_dataclass(v) for v in obj)
return False
def _parallelism_info() -> ParallelismInfo:
return ParallelismInfo(
tp_rank=0, tp_size=2, dp_rank=0, dp_size=1, pp_rank=0, pp_size=1, rank=0, size=2
)
def _checksum_info(tag: str) -> ChecksumInfo:
return ChecksumInfo(
checksums={f"model.layers.{tag}": "deadbeef"},
per_gpu_checksum="cafef00d",
parallelism_info=_parallelism_info(),
)
# One representative instance per (now-tightened) ex-registry type. The 13th
# entry, SetInjectDumpMetadataReqInput, was deleted as dead code, leaving 12.
REGISTRY_TYPE_INSTANCES = {
"UpdateWeightFromDiskReqInput": UpdateWeightFromDiskReqInput(
model_path="dummy", manifest={"w": [1, 2], "meta": {"k": "v"}}
),
"BackupDramReq": BackupDramReq(
rank=0,
weight_pointer_map={
"experts.0.gate_proj": ExpertWeightPointer(weight_ptr=8, byte_size=4),
"experts.1.up_proj": ExpertWeightPointer(weight_ptr=16, byte_size=8),
},
session_id="session",
buffer_size=1024,
),
"GetWeightsByNameReqOutput/flat": GetWeightsByNameReqOutput(
parameter=[1.0, 2.5, 3.0]
),
"GetWeightsByNameReqOutput/nested": GetWeightsByNameReqOutput(
parameter=[[1.0, 2.0], [3.0]]
),
"GetWeightsByNameReqOutput/none": GetWeightsByNameReqOutput(parameter=None),
"CheckWeightsReqOutput": CheckWeightsReqOutput(
success=True,
message="Success.",
payload=[_checksum_info("0"), _checksum_info("1")],
),
"GetInternalStateReqOutput": GetInternalStateReqOutput(
internal_state={"a": 1, "b": [1, 2], "c": {"d": "e"}, "f": None}
),
"SetInternalStateReq": SetInternalStateReq(
server_args={
"pp_max_micro_batch_size": 4,
"speculative_accept_threshold_acc": 0.5,
}
),
"SetInternalStateReqOutput": SetInternalStateReqOutput(updated=True),
"VertexGenerateReqInput": VertexGenerateReqInput(
instances=[{"prompt": "hi"}], parameters={"max_tokens": 8}
),
"RpcReqInput/empty": RpcReqInput(method="collective_rpc", parameters={}),
"RpcReqInput/scalars": RpcReqInput(
method="collective_rpc",
parameters={"flag": True, "n": 1, "ratio": 2.0, "name": "x", "opt": None},
),
"RpcReqInput/none": RpcReqInput(method="collective_rpc", parameters=None),
"LoadLoRAAdapterFromTensorsReqInput": LoadLoRAAdapterFromTensorsReqInput(
lora_name="adapter",
config_dict={"r": 8, "lora_alpha": 16, "target_modules": ["q_proj", "v_proj"]},
serialized_tensors="",
added_tokens_config={"<extra>": 32000},
),
"DumperControlReqInput": DumperControlReqInput(method="start", body={"k": "v"}),
"DumperControlReqOutput": DumperControlReqOutput(
success=True, response=[{"worker": 0, "ok": True}]
),
}
NARROWED_BACKUP_KEYS = ("name", "shape", "numel", "dtype", "element_size")
class TestMsgpackIpcRoundtrip(CustomTestCase):
def test_registry_is_empty(self):
# `getattr(..., ())` is deliberate: the acceptance criterion for Task 4 is
# that the symbol is *deleted*, so this asserts its absence rather than
# defensively reading a field. It must survive the symbol removal.
self.assertEqual(
getattr(io_struct, "_REQ_TYPES_WITH_OPAQUE_FIELDS", ()),
(),
)
def test_each_type_round_trips_natively(self):
for name, instance in REGISTRY_TYPE_INSTANCES.items():
with self.subTest(type=name):
encoded = msgpack_encode(instance)
# Natively encoded structs are never wrapped: a PickleWrapper
# frame would decode back to a PickleWrapper, not the type.
self.assertNotIsInstance(
msgpack_decode(encoded), io_struct.PickleWrapper
)
self.assertEqual(_round_trip(instance), instance)
self.assertEqual(_double_hop(instance), instance)
def test_backup_dram_req_is_narrowed(self):
# ExpertWeightPointer carries only the two fields the consumer reads; the
# five torch-metadata keys the producer used to send are gone.
field_names = {f.name for f in msgspec.structs.fields(ExpertWeightPointer)}
self.assertEqual(field_names, {"weight_ptr", "byte_size"})
for dropped in NARROWED_BACKUP_KEYS:
self.assertNotIn(dropped, field_names)
decoded = _round_trip(REGISTRY_TYPE_INSTANCES["BackupDramReq"])
pointer = decoded.weight_pointer_map["experts.0.gate_proj"]
self.assertEqual((pointer.weight_ptr, pointer.byte_size), (8, 4))
def test_check_weights_mirrors_match_pydantic_models(self):
# Field-parity guard: the msgspec wire structs must not drift from the
# pydantic source of truth in weight_checker.
self.assertEqual(
{f.name for f in msgspec.structs.fields(ParallelismInfo)},
set(PydanticParallelismInfo.model_fields),
)
self.assertEqual(
{f.name for f in msgspec.structs.fields(ChecksumInfo)},
set(PydanticChecksumInfo.model_fields),
)
def test_check_weights_multi_rank_payload(self):
# tp>1 sends one ChecksumInfo per rank; the list round-trips and stays a
# {field: value} dict once converted back to builtins for the HTTP body.
instance = REGISTRY_TYPE_INSTANCES["CheckWeightsReqOutput"]
decoded = _round_trip(instance)
self.assertEqual(len(decoded.payload), 2)
as_dict = msgspec_to_builtins(decoded.payload[0])
self.assertEqual(as_dict["per_gpu_checksum"], "cafef00d")
self.assertIn("tp_rank", as_dict["parallelism_info"])
def test_check_weights_producer_conversion(self):
# Mirrors weight_updater.check_weights: WeightChecker returns
# ChecksumInfo.model_dump() (a dict), converted to the msgspec struct via
# msgspec.convert, and the result round-trips as the payload.
pydantic_checksum = PydanticChecksumInfo(
checksums={"model.layers.0": "deadbeef"},
per_gpu_checksum="cafef00d",
parallelism_info=PydanticParallelismInfo(
tp_rank=0,
tp_size=2,
dp_rank=0,
dp_size=1,
pp_rank=0,
pp_size=1,
rank=0,
size=2,
),
)
converted = msgspec.convert(pydantic_checksum.model_dump(), ChecksumInfo)
self.assertEqual(converted.per_gpu_checksum, "cafef00d")
self.assertEqual(converted.parallelism_info.tp_rank, 0)
output = CheckWeightsReqOutput(success=True, message="ok", payload=[converted])
self.assertEqual(_round_trip(output), output)
def test_get_internal_state_sanitizes_dataclass(self):
# A live vars(ServerArgs) dump holds a dataclass: cuda_graph_config is an
# Optional[CudaGraphConfig]. The producer sanitizes via msgspec_to_builtins
# so it does not survive onto the wire; materialize CudaGraphConfig
# explicitly.
raw = {
"cuda_graph_config": CudaGraphConfig(),
"max_running_requests": 256,
}
self.assertTrue(_contains_dataclass(raw))
sanitized = msgspec_to_builtins(raw)
self.assertFalse(_contains_dataclass(sanitized))
self.assertIsInstance(sanitized["cuda_graph_config"], dict)
output = GetInternalStateReqOutput(internal_state=sanitized)
self.assertEqual(_round_trip(output), output)
if __name__ == "__main__":
unittest.main()