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chore: import upstream snapshot with attribution
2026-07-13 12:38:16 +08:00

246 lines
9.1 KiB
Python

# Copyright 2023-2026 SGLang Team
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Phase / backend identifiers, the canonical default for
cuda_graph_config, and the --cuda-graph-config JSON CLI parser.
Module-level imports are pure stdlib — no torch / sglang.srt deps — so
ServerArgs can import everything here without pulling in backend
classes. check_cuda_graph_backend lazy-imports get_server_args
inside the function body to preserve that invariant.
"""
import argparse
import dataclasses
import json
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional
class Phase:
"""The two phases of model forward."""
DECODE = "decode"
PREFILL = "prefill"
ALL = (DECODE, PREFILL)
class Backend:
"""CUDA graph capture backends a phase can use."""
FULL = "full"
BREAKABLE = "breakable"
TC_PIECEWISE = "tc_piecewise"
DISABLED = "disabled"
ALL = (FULL, BREAKABLE, TC_PIECEWISE, DISABLED)
ALLOWED_BACKENDS_PER_PHASE = {
Phase.DECODE: (
Backend.FULL,
Backend.BREAKABLE,
Backend.TC_PIECEWISE,
Backend.DISABLED,
),
# full for prefill captures one whole-forward graph per num_tokens
# bucket (bs=1 only); replay pads num_tokens up to the nearest
# captured bucket. Opt-in: the padding waste is the operator's call.
Phase.PREFILL: (
Backend.FULL,
Backend.BREAKABLE,
Backend.TC_PIECEWISE,
Backend.DISABLED,
),
}
# Per-phase settings schema. Keys other than backend are runner-level
# (read by any backend in that phase); tc_compiler is the lone
# backend-specific knob (only meaningful when backend == tc_piecewise).
# For prefill, bs carries the captured shape size (token count for
# tc_piecewise, request count for breakable) — one shape knob per phase.
# full_prefill_max_req is prefill-only and only meaningful when backend == full.
ALLOWED_KEYS_PER_PHASE = {
Phase.DECODE: ("backend", "max_bs", "bs", "tc_compiler"),
Phase.PREFILL: ("backend", "max_bs", "bs", "tc_compiler", "full_prefill_max_req"),
}
@dataclass
class PhaseConfig:
"""Per-phase CUDA graph settings."""
backend: str = Backend.DISABLED
max_bs: Optional[int] = None
bs: Optional[List[int]] = None
# Only meaningful when backend == tc_piecewise; ignored otherwise.
tc_compiler: str = "eager"
# Only meaningful for the prefill phase with backend == full: max number of
# request slots baked into each captured graph. Real bs <= full_prefill_max_req
# reuses the graph (unused slots become zero-length sentinels); larger
# batches fall back to eager. Ignored by BCG (bs=1 only) and TC_PIECEWISE
# (bs-invariant via torch.compile). None auto-derives chunked_prefill_size // 512.
full_prefill_max_req: Optional[int] = None
def default_prefill_backend() -> str:
"""BCG (breakable) is the prefill default on CUDA only; other platforms
(HIP/NPU/...) keep tc_piecewise until BCG is validated there. Lazy import
keeps this module's stdlib-only import invariant (see module docstring)."""
from sglang.srt.utils import is_cuda
return Backend.BREAKABLE if is_cuda() else Backend.TC_PIECEWISE
@dataclass
class CudaGraphConfig:
"""Top-level CUDA graph config: one PhaseConfig per phase."""
decode: PhaseConfig = field(
default_factory=lambda: PhaseConfig(backend=Backend.FULL)
)
prefill: PhaseConfig = field(
default_factory=lambda: PhaseConfig(backend=default_prefill_backend())
)
def __getitem__(self, phase: str) -> PhaseConfig:
"""Phase-string lookup; kept for migration ergonomics."""
if phase not in Phase.ALL:
raise KeyError(phase)
return getattr(self, phase)
def to_dict(self) -> Dict[str, Dict[str, Any]]:
# Diff-only, not asdict: the parser locks every (phase, key) it sees,
# so emitting defaults would lock fields the caller never set.
baseline = default_cuda_graph_config()
return {
Phase.DECODE: _diff_phase(self.decode, baseline.decode),
Phase.PREFILL: _diff_phase(self.prefill, baseline.prefill),
}
@classmethod
def from_dict(cls, raw: Optional[Dict[str, Dict[str, Any]]]) -> "CudaGraphConfig":
"""Build from a (partial) dict of overrides, defaults fill the rest.
Unknown phases / keys are silently dropped — the JSON-input
validator (parse_cuda_graph_config_arg) rejects them upstream."""
cfg = cls()
if not raw:
return cfg
for phase, phase_settings in raw.items():
if phase not in Phase.ALL or not isinstance(phase_settings, dict):
continue
phase_cfg = getattr(cfg, phase)
allowed = ALLOWED_KEYS_PER_PHASE[phase]
for key, value in phase_settings.items():
if key in allowed:
setattr(phase_cfg, key, value)
return cfg
def default_cuda_graph_config() -> CudaGraphConfig:
"""Fresh CudaGraphConfig populated with canonical defaults."""
return CudaGraphConfig()
def _diff_phase(actual: PhaseConfig, baseline: PhaseConfig) -> Dict[str, Any]:
"""Return only fields whose value differs from the per-phase default."""
return {
f.name: getattr(actual, f.name)
for f in dataclasses.fields(actual)
if getattr(actual, f.name) != getattr(baseline, f.name)
}
def check_cuda_graph_backend(phase: str, backend: str) -> bool:
"""True if cuda_graph_config[phase].backend == backend on the
global server args. Returns False if the global server args have not
been initialized yet (e.g. unit tests, early startup)."""
from sglang.srt.runtime_context import get_server_args
try:
server_args = get_server_args()
except ValueError:
return False
cfg = server_args.cuda_graph_config
if cfg is None or phase not in Phase.ALL:
return False
return getattr(cfg, phase).backend == backend
def cuda_graph_fully_disabled() -> bool:
"""True iff cuda_graph_config has Backend.DISABLED on every phase.
Use at sites that ask the legacy server_args.disable_cuda_graph
question ("no CG anywhere globally") — e.g., preallocating buffers
that any captured graph would otherwise reuse, or one-shot init
that's a no-op when CG is completely off.
"""
return check_cuda_graph_backend(
Phase.DECODE, Backend.DISABLED
) and check_cuda_graph_backend(Phase.PREFILL, Backend.DISABLED)
def parse_cuda_graph_config_arg(raw: str) -> Dict[str, Dict[str, Any]]:
"""argparse type for --cuda-graph-config: parse JSON dict of
phase → settings dict. Each phase's settings dict is itself validated
against ALLOWED_KEYS_PER_PHASE. Returns a plain dict — the
precedence pipeline in ServerArgs converts to CudaGraphConfig
after merging."""
try:
parsed = json.loads(raw)
except json.JSONDecodeError as e:
raise argparse.ArgumentTypeError(f"--cuda-graph-config must be JSON: {e}")
if not isinstance(parsed, dict):
raise argparse.ArgumentTypeError(
f"--cuda-graph-config must be a JSON object, got {type(parsed).__name__}"
)
result: Dict[str, Dict[str, Any]] = {}
for phase, phase_settings in parsed.items():
phase = str(phase)
if phase not in Phase.ALL:
raise argparse.ArgumentTypeError(
f"--cuda-graph-config: unknown phase '{phase}', expected one of {Phase.ALL}"
)
if not isinstance(phase_settings, dict):
raise argparse.ArgumentTypeError(
f"--cuda-graph-config['{phase}'] must be a JSON object, got "
f"{type(phase_settings).__name__}"
)
allowed = ALLOWED_KEYS_PER_PHASE[phase]
result[phase] = {}
for key, value in phase_settings.items():
if key not in allowed:
raise argparse.ArgumentTypeError(
f"--cuda-graph-config['{phase}']: unknown key '{key}', expected one of {allowed}"
)
result[phase][key] = value
return result
def explicit_keys_in(
settings: Optional[Dict[str, Dict[str, Any]]],
) -> set:
"""Return the set of (phase, key) tuples present in settings
(the raw dict form, as it arrives from CLI/SDK). Used by ServerArgs
to track keys the user explicitly set so the auto-disable cascade can
skip them."""
out: set = set()
if not settings:
return out
for phase, phase_settings in settings.items():
if not isinstance(phase_settings, dict):
continue
for key in phase_settings.keys():
out.add((phase, key))
return out