本文へ移動
cccskills
無料GitHub で公開

large-class-style

Code style for SGLang large classes `Scheduler`, `TokenizerManager`, and `ModelRunner`: frozen-code conventions and `__init__` orchestration style. Use when modifying any of these three classes or reviewing changes to them.

インストール方法を見る

含まれるファイル(1)

  • SKILL.md7.6 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Code Style for Scheduler / TokenizerManager / ModelRunner

Conventions for SGLang's three large classes:

  • Scheduler — python/sglang/srt/managers/scheduler.py
  • TokenizerManager — python/sglang/srt/managers/tokenizer_manager.py
  • ModelRunner — python/sglang/srt/model_executor/model_runner.py

1. Frozen Code

  • Some core files are frozen: orchestration-only — a thin composition root that constructs collaborators, wires them, delegates to them, and coordinates the calls. They must stay that way.
  • Domain logic does not belong in a frozen file; it lives in a collaborator class in its own module.

1.1 Why

  • The file is a thin orchestrator over collaborator classes; freezing keeps it that way and stops it growing back into a god class.
  • Keeping domain logic in collaborators (their own files) is what makes per-file code ownership, single responsibility, and unit testing possible.
  • The orchestrator is the composition root: it may know about every collaborator, because wiring and sequencing them is its job. Coordination stays here — domain logic does not.

1.2 Frozen files

  • python/sglang/srt/model_executor/model_runner.py

1.3 Allowed: orchestration

Every statement refers to a collaborator and is one of:

  1. Construct — a short init_<thing> helper whose body is essentially a single construction (follows §2); use maybe_init_<thing> with a one-line gate when conditional.
  2. Wire — a short call that runs the helper from the orchestrator (e.g. in __init__).
  3. Delegate — calls to a collaborator's methods at the necessary call sites (self.foo.run(...)).
  4. Coordinate — the minimal control flow that selects or orders the above: an if choosing whether / which collaborator to wire or call, the order of calls, threading one call's result into the next.
  • Heuristic: a statement is allowed only if it constructs, wires, delegates, or selects/orders those — never if it computes or transforms a value beyond passing arguments and results through.
# model_runner.py — orchestration only.
def init_foo(self):                        # construct
    self.foo = FooManager(server_args=self.server_args, device=self.device)

self.init_foo()                            # wire (in __init__)

if self.server_args.enable_bar:            # coordinate: select
    self.bar.prepare(forward_batch)        # delegate
out = self.foo.run(forward_batch)          # delegate
self.baz.consume(out)                      # coordinate: thread result into next delegate

1.4 Not allowed: domain logic

  • Config building, data transformation, algorithm bodies, math, post-processing — any branch or loop that computes rather than coordinates.
  • It belongs in the collaborator.
# NOT allowed in a frozen file: domain logic inlined.
self.foo = None
if self.server_args.enable_foo:
    config = build_foo_config(self.model_config, self.device)   # config logic in frozen file
    self.foo = FooManager(config)                               # inline construction, not via (maybe_)init_foo
    out = [step(x) for x in batch]                              # computation, not coordination
  • Fix: move that body into FooManager (its __init__ or a factory) plus a (maybe_)init_foo helper.

1.5 Where coordination logic goes

  1. Default: extract. Pull cohesive coordination into a low-coupling collaborator (an initializer, a forward pipeline) and delegate to it.
  2. Residue stays. Coordination that can't be cohesively extracted may remain — but only the minimal Coordinate form above, kept pseudocode-readable. This is the explicit exception, not a fallback; note why it stays.
  • When the residue outgrows pseudocode, that is the signal to extract a dedicated coordinator — not to keep inlining.

1.6 Pass what the collaborator needs, not the god object

  • When you extract domain logic into a collaborator (a factory, an initializer, a pipeline), give it the specific values it needs — model_config, device, the sizes — not the whole frozen object (ModelRunner, Scheduler).

  • Passing the god object back re-creates the coupling the split was meant to remove: the module still reads dozens of attributes off it, can't be unit-tested without building the whole class, and every field rename ripples back in.

  • Default to narrow, keyword args. Reference shape: layer_setup.resolve_layer_indices(*, model, model_config, is_draft_worker, spec_algorithm).

  • Return a small frozen struct and let the orchestrator assign it onto its own fields. The collaborator should not reach back in and mutate the god object.

  • If a leaf genuinely needs the live object — its constructor contract already takes the runner, or it reads state that mutates after init — confine that dependency to the smallest leaf and pass narrow args everywhere above it. Note why it can't be narrowed.

1.7 If you do pass the god object, keep it read-only

  • A callee that genuinely takes the live object should read fields off it and return results; it writes fields back only when there is genuinely no other way.
  • The orchestrator owns the assignment onto its own fields.
  • Why: a callee that mutates the god object scatters its writes across other modules — you can no longer see what ModelRunner owns by reading model_runner.py, the hidden writes race with the orchestrator's own ordering, and the callee silently depends on being invoked at exactly the right moment.
# Good — callee reads the runner and returns a small frozen struct; the orchestrator
# owns the writes.
# model_runner.py
class ModelRunner:
    def bar(self):
        self.foo_result = foo(self)

# another_file.py
def foo(model_runner) -> FooResult:
    return FooResult(a=xx, b=yy, c=zz)

# Avoid — callee reaches back in and writes the runner's fields.
# model_runner.py
class ModelRunner:
    def bar(self):
        foo(self)

# another_file.py
def foo(model_runner):
    model_runner.a = xx
    model_runner.b = yy
    model_runner.c = zz

2. __init__ style

Apply when modifying the __init__ of the three classes above.

2.1 Why

  • Downstream forks override one piece (tokenizer, KV cache, IPC, …).
  • Inline logic forces them to copy the whole __init__, which rots against upstream.
  • Splitting into init_* helpers lets them override exactly what they need.
  • Reference shape: TokenizerManager.__init__ in python/sglang/srt/managers/tokenizer_manager.py.

2.2 Rules

  • __init__ is an orchestrator. Sequence of self.init_*(...) calls + minimal glue. No non-trivial construction inlined.
  • One helper per overridable unit. Each init_* = one concern a subclass might swap. Don't lump.
  • Naming: init_<thing> (snake_case, names the component). Conditional construction → maybe_init_<thing>, gate inside the helper.
  • No silent state coupling. A helper only reads self.* set by earlier helpers. Ordering lives in __init__. Shared intermediates → pass as args, not via self.*.
  • New logic = new helper. Default to adding init_<thing>, not another inline block. One-line self.foo = server_args.foo is fine; structured logic is not.
  • Preserve override points. Prefer additive changes to existing init_* signatures. Breaking changes → call out in PR.

2.3 Scope

  • Only the three classes listed above.
  • Not other manager-style classes, not small dataclass/utility constructors.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

Step-by-step tutorial for adding a new lightweight JIT CUDA kernel to sglang.kernels JIT infrastructure and public operator groups

日本語の概要は準備中です。原文の説明を表示しています。

sgl-project/sglang3.7万2026年10月12日 更新

Step-by-step tutorial for adding a heavyweight AOT CUDA/C++ kernel to sgl-kernel (including tests & benchmarks)

日本語の概要は準備中です。原文の説明を表示しています。

sgl-project/sglang3.7万2026年10月12日 更新

Start and persistently pursue a goal to babysit an SGLang pull request until selected GitHub Actions workflows pass on the latest PR head. Use when asked to monitor, babysit, retry, or fix PR CI for lint.yml, pr-test.yml, pr-test-extra.yml, AMD, or other named workflows; classify failures as PR-related versus flaky or infrastructural, auto-fix and push only small clean fixes, rerun failed jobs only up to 10 times, and ignore unselected workflows.

日本語の概要は準備中です。原文の説明を表示しています。

sgl-project/sglang3.7万2026年10月12日 更新

Audit the existing test tree and CI configuration for improvements, using a catalog of patterns previously applied in this repo. Use when asked to audit tests or CI, shrink CI time or cost, find redundant or misplaced tests, clean up a test group, or review whether a CI change follows established practice.

日本語の概要は準備中です。原文の説明を表示しています。

sgl-project/sglang3.7万2026年10月12日 更新

Guide to SGLang CI workflow orchestration — stage ordering, fail-fast, gating, partitioning, execution modes, and debugging CI failures. Use when modifying CI workflows, adding stages, debugging CI pipeline issues, or understanding how tests are dispatched and gated across stages.

日本語の概要は準備中です。原文の説明を表示しています。

sgl-project/sglang3.7万2026年10月12日 更新

Audit SGLang startup logs, save evidence, and propose cleanup for user review. With no arguments, run Qwen3-8B at TP1 and TP2 plus gpt-oss-20b at TP1.

日本語の概要は準備中です。原文の説明を表示しています。

sgl-project/sglang3.7万2026年10月12日 更新

sgl-project のスキルをすべて見る

このスキルの問題を報告する