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Author SHA1 Message Date
iomgaa 4fb7a61f8b fix(question_gen): resolve pipeline integration issues from final review 
1. Apply postprocess shuffle result (pp.options, pp.answer) to final
   GeneratedQuestion output instead of using original candidate values.

2. Record dedup rejection in store via new mark_item_rejected() method,
   preventing items from staying as 'accepted' after dedup rejects them.

3. Add .flatten() to embed_fn outputs in _is_duplicate and embed_pool
   append to handle 2D (1,D) arrays from embedding implementations.

4. Validate exactly 4 options in _validate_parsed_fields (was >= 2),
   matching the A-D answer constraint.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-07-12 00:14:12 -04:00
iomgaa eecb86e27a feat(question_gen): add generate-v2 CLI subcommand and experiment script 
- Add generate-v2 subparser with --config, --store-dir, --db-path,
  --seed, and --dry-run arguments to tools/generate_questions.py
- Implement _run_generate_v2 async handler: config loading, video
  discovery, DI client construction, TreeIndex loading, pipeline
  invocation, and result persistence
- Add scripts/generate_questions_v2.sh following build_trees.sh
  conventions (source .env, conda run python path, MODE=mock support)
- Update app/question_gen/__init__.py to export full v2 public API:
  run_pipeline_v2, PipelineConfig, PipelineResult, QuestionFamilySpec,
  ALL_FAMILIES, CandidateQuestion, generate_one_v2, GateReport, run_gates
- Add QuestionGenStore.load_progress() for pipeline resumption
- Add integration tests for CLI help and dry-run behavior
- Update test_question_gen_api to match expanded __all__

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-07-12 00:04:42 -04:00
iomgaa f46e87258c refactor(question_gen): extract helpers to reduce pipeline_v2 CC below grade C 
Extract _get_git_sha, _filter_pending_slots, and _run_heavy_sampling
from run_pipeline_v2. Reduces cyclomatic complexity from C(15) to B(6).

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-07-11 23:57:35 -04:00
iomgaa 206c553143 feat(question_gen): add v2 pipeline with retry loop and heavy check 
- PipelineConfig: YAML-driven configuration with family_ratios, retry,
  concurrency, dedup threshold, and heavy sampling rate
- _assign_slots: deterministic round-robin slot assignment across videos
  with per-family weighted random selection
- _process_one_slot: full retry loop (generate → postprocess → gates →
  dedup) with reject-reason feedback to VLM on retry
- _heavy_check_one: blind LLM agent trial-answer for difficulty_steps
- run_pipeline_v2: orchestration with semaphore-bounded concurrency,
  progress/resume support, and store integration
- is_duplicate: cosine similarity dedup against embedding pool

Tests: 11 integration tests covering slot assignment, retry behavior,
max-retries exhaustion, full pipeline flow, progress resume, heavy
sampling, and store record completeness.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-07-11 23:55:15 -04:00
iomgaa 6d6eb8e3a3 refactor(question_gen): extract _validate_parsed_fields to reduce CC 
Split field validation logic out of _parse_v2_response into a dedicated
_validate_parsed_fields helper. This brings _parse_v2_response from CC=11
(grade C) down to CC=3 (grade A). The extracted validator is CC=9 (grade B).
No grade-C functions remain.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-07-11 23:43:35 -04:00
iomgaa cf51d2de9d feat(question_gen): add v2 generator with per-family prompt templates 
Implement generator_v2.py with:
- CandidateQuestion dataclass (canonical location)
- _load_prompt_template: loads per-family .md from store/prompts/
- _build_v2_prompt: constructs system+user messages with material context
- _parse_v2_response: JSON extraction, json_repair, field validation
- generate_one_v2: async VLM call orchestration with reject_reason support

Add 5 family-specific prompt templates:
- retrieval.md: factual recall from visible content
- reasoning.md: multi-hop inference across segments
- enumeration.md: counting/listing entities and actions
- visual.md: visual details requiring frame observation
- spatial.md: spatial relationships between objects/people

Tests: 11 unit tests covering prompt build, parse, and e2e generation.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-07-11 23:41:36 -04:00
iomgaa 9053233f99 fix(question_gen): gates reject_reason returns raw reason; short-circuit skips LLM 
- GateReport.reject_reason now returns gate.reason directly (no [name] prefix)
- verbatim short-circuit sets other 3 gates to SKIP without calling LLM
- test_high_verbatim_shortcircuits asserts zero LLM calls and SKIP verdicts

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-07-11 23:33:57 -04:00
iomgaa 9f739e831d refactor(question_gen): reduce cyclomatic complexity in sampler_v2 
Extract shared _resolve_subtree helper to eliminate repeated tri-level
node resolution. Break _validate_sampling_constraints into focused
single-purpose helpers:
- _count_l3_descendants
- _has_frames
- _count_subtitles
- _resolve_subtree / _find_l3_parent

Extract _subtitles_from_l2_list and _frames_from_l2_list to simplify
collection functions.

Complexity improvements:
- _validate_sampling_constraints: D(23) -> B(8)
- _collect_subtitle_sentences: C(16) -> A(3)
- _collect_frame_paths: C(13) -> A(2)

All functions now grade B or better per radon cc.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-07-11 23:33:48 -04:00
iomgaa f74711cd11 feat(question_gen): add v2 material sampler with family constraints 
Implement sample_material_v2 module that samples tree nodes with
QuestionFamilySpec-aware constraint validation, providing richer
MaterialContext output (subtitles, cross-L2 context, frame paths).

Key components:
- AnchorContext/MaterialContext frozen dataclasses
- _validate_sampling_constraints: multi-level constraint checking
- _collect_subtitle_sentences: subtree subtitle extraction
- _collect_cross_l2_context: peer L2 event descriptions
- sample_material_v2: main entry with retry-on-constraint-violation

Tests: 11 unit tests covering normal sampling, used-node exclusion,
constraint violation retries, cross-L2 population, and subtitle
collection.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-07-11 23:30:56 -04:00
iomgaa 271d1682c9 feat(question_gen): add lightweight 4-gate quality check 
Implement 4 concurrent LLM-based quality gates for generated questions:
- key_verify: validates answer evidence in source material
- blind_answer: rejects questions answerable without video context
- multi_true: detects ambiguous multi-correct options
- leak_test: per-family shortcut detection (5 probe templates)

Includes run_gates orchestrator with verbatim_ratio short-circuit,
JSON response parsing with fallback, and 9 unit tests (all passing).

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-07-11 23:30:13 -04:00
iomgaa 9627ac9cf9 fix(question_gen): raise ValueError on UPDATE of missing rows 
record_run_end, update_gates, and update_difficulty now check
cursor.rowcount after UPDATE+commit and raise ValueError if 0 rows
were affected. Prevents silent telemetry loss.

Adds three negative-path tests:
- test_record_run_end_missing_run_raises
- test_update_gates_missing_item_raises
- test_update_difficulty_missing_item_raises

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-07-11 23:23:48 -04:00
iomgaa 7abe92eb1c fix(question_gen): check_verbatim covers question_text + add missing blacklist patterns 
- check_verbatim now computes n-gram overlap for BOTH question_text and
  correct_option vs source texts, returning max(question_ratio, option_ratio).
  Extracted _ngram_overlap_ratio helper for reuse.

- Added 4 missing blacklist patterns: 'this segment', 'this frame',
  'the current frame', 'frame summary'.

- Added 5 new test cases covering the above changes.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-07-11 23:23:37 -04:00
iomgaa 9525726133 fix(question_gen): rename finished_at to ended_at per schema spec 
Aligns DDL column name with research-wiki/schemas/question-gen-runs.md
which specifies 'ended_at' (not 'finished_at').

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-07-11 23:18:52 -04:00
iomgaa 74686dde68 refactor(question_gen): reduce check_forbidden_material complexity to A(3) 
Extract _match_any helper and declarative _FORBIDDEN_MATERIAL_RULES table
to replace repetitive per-category for-loops. Reduces cyclomatic complexity
from C(11) to A(3).

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-07-11 23:16:34 -04:00
iomgaa 6a5424a618 feat(question_gen): add SQLite run store for generation telemetry 
Implements QuestionGenStore with:
- Idempotent schema initialization (question_gen_runs + question_gen_items)
- Run lifecycle: record_run_start / record_run_end / get_run_stats
- Per-item recording: record_item / update_gates / update_difficulty
- GateReportLike Protocol for duck-type gate report compatibility
- WAL mode + foreign keys + check_same_thread=False

DDL aligns with research-wiki/schemas/question-gen-{runs,items}.md.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-07-11 23:15:53 -04:00
iomgaa c83d771923 feat(question_gen): add deterministic postprocess layer 
Add app/question_gen/postprocess.py with zero-LLM deterministic
post-processing for generated questions:

- shuffle_options: deterministic option permutation with answer remapping
- check_referent_blacklist: detect self-referential language (this clip, etc.)
- check_verbatim: word-level n-gram overlap ratio measurement
- has_time_anchor: timestamp and temporal phrase detection
- check_forbidden_material: T1/T7 source material validation
- run_postprocess: orchestration returning PostprocessResult

Tests: 31 unit tests covering all functions.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-07-11 23:14:43 -04:00
iomgaa 75e6d8c550 feat(question_gen): add 5 question family specs with sampling constraints 
Define QuestionFamilySpec, LeakTestProfile, SamplingConstraint dataclasses
and instantiate 5 families (RETRIEVAL/REASONING/ENUMERATION/VISUAL/SPATIAL)
targeting failure mechanisms M1-M5. Implement get_family_for_slot with
legal-type filtering + weighted random selection.

13 unit tests cover: full task-type coverage, skill_target uniqueness,
deterministic seeding, invalid input errors, and chi-square distribution.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-07-11 23:14:22 -04:00
iomgaa 811ffa648b feat(types): extend GeneratedQuestion with skill_target & difficulty_steps 
- Add skill_target (str | None) and difficulty_steps (int | None) fields
  to GeneratedQuestion dataclass with field(default=None)
- Update loader.py to pass new fields from JSON (backward-compatible)
- Update pools.py _q_to_dict/_dict_to_q for serialization compat
- Add question_gen_v2 config section to default.yaml
- Add comprehensive test coverage (7 tests)

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-07-11 23:05:38 -04:00
iomgaa e9073bfdc2 feat(tree): expose build_async and accept injected API semaphore 
Core algorithms #1/#2/#3 unchanged: only entry wrapping and semaphore
source switch (injected vs self-built); build logic untouched.
- rename _build_async to public build_async (body unchanged)
- __init__ accepts keyword-only api_semaphore for cross-video sharing
- default path (no injection) is verbatim-equivalent to previous code
 2026-07-11 11:14:45 -04:00
iomgaa ebbd112d50 fix(tree): move Iterable import into type-checking block 2026-07-11 09:05:04 -04:00
iomgaa f0284199b8 refactor(tree): narrow _clean_join parameter type to Iterable 2026-07-11 09:04:25 -04:00
iomgaa a2c6a97621 refactor(tree): extract _clean_join to keep entity-fields complexity at B 
质量门要求新增代码复杂度不超过 B 级：将 node_entity_fields 中重复的
"清洗-去重-拼接"逻辑抽为模块级纯函数 _clean_join，主体收敛为两次
调用。radon：node_entity_fields C(13) → B(6)，_clean_join A(5)。

算法 #11（树环境语义搜索）数据访问层，行为不变（既有 4 测试未改全绿）。
 2026-07-11 08:56:17 -04:00
iomgaa 4e0e05210d feat(search): append raw entity fields after view_node summary 
view_node 按题两轮摘要（summarize_node）会吞掉 entities/visible_text
字段信号，Agent 站在证据节点上仍漏读实体（benchmark 错题 M1，案例
786-2、872-3、750-1）。dispatcher 侧在摘要后确定性追加 [实体]/[画面
文字] 原文区块，LLM 无法吞掉。

- TreeEnvironment.node_entity_fields：按层级取 card 实体字段原文，
  去空白、去重、分号拼接；空字段省键；未知节点抛 KeyError
- _handle_view_node Phase 2.5：摘要后、子节点概览前追加实体区块
- 附带 ruff format 修正 test_tree_environment.py 两处既有格式

算法 #11（树环境语义搜索）数据访问层扩展，不改搜索算法本身。
 2026-07-11 08:53:56 -04:00
iomgaa 307c64c388 fix(harness): infer mode honors CLI --questions over manifest 2026-07-11 07:45:33 -04:00
iomgaa 5b51f4bd0c fix(synthesizer): generate_one 捕获所有异常避免 VLM 超时穿透崩溃 
except (ValueError, KeyError) → except Exception，
覆盖 StreamLivenessTimeout 等网络/超时异常。

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-07-10 01:08:03 -04:00
iomgaa a7ca6d15ed feat(harness): InferenceDepsRouter per-video 路由器 
按 video_id 懒加载 InferenceDeps 并缓存，路由 dispatch/prompt_builder:
- create_dispatch: 按 session_id 路由到对应视频的工具调度
- create_prompt_builder: 自动注册 qid→vid 映射并路由 prompt 构建
- 三元组 (video_id, skills_dir, prompts_dir) 缓存键

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-07-09 12:20:32 -04:00
iomgaa f21bf345a6 feat(runner): 注入 tool_dispatch_factory/prompt_builder_factory + fail-fast 
Runner.__init__ 新增 2 个可选参数:
- tool_dispatch_factory: 工具调度工厂
- prompt_builder_factory: prompt 构建工厂

infer/eval/train 模式缺少工厂时 fail-fast 抛 ValueError。
_make_tool_dispatch_fn/_make_prompt_builder 优先使用注入工厂。

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-07-09 12:20:25 -04:00
iomgaa 924160c779 feat(ports): 新增 ToolDispatchFactory/PromptBuilderFactory Protocol 
4 个新 Protocol 类型:
- ToolDispatchFn: 工具调度函数签名
- ToolDispatchFactory: per-version 工具调度工厂
- PromptBuilderFn: Prompt 构建函数签名
- PromptBuilderFactory: per-version prompt 构建工厂

含 runtime_checkable isinstance 测试。

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-07-09 12:20:16 -04:00
iomgaa 16140cafcc fix(tree): from_dict L2 subtitle 旧格式兼容 fallback 
旧格式 tree.json 无 card-level L2 subtitle 时，从已构造的 L3
children 聚合 subtitle，避免运行时加载静默丢失 L2 字幕。

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-07-09 12:04:36 -04:00
iomgaa d3be9b1322 refactor(tree): subtitle 迁入 L3Card/L2Card + 建树管线修正 
- L3Card/L2Card 新增 subtitle: str 字段（L1Card 不加）
- L3Node 移除 subtitle 字段（数据迁入 Card）
- assign_subtitles_voronoi 改写 Card.subtitle + L2 聚合
- _collect_card_strings 增加 skip_fields 排除 subtitle
- _node_full_text/_node_anchored_text 保持 字幕:/[sN] 语义
- get_subtitle 读 Card.subtitle（L2/L3）
- verify.py/synthesizer.py: l3.subtitle → l3.card.subtitle
- 迁移脚本 tools/migrate_subtitle_to_card.py（幂等，300 棵树已迁移）
- 9→6 个测试文件适配（3 个无需改动）

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-07-09 11:57:41 -04:00
iomgaa 45403b23b4 feat(repair): regenerator + supplement 防御修复 + 迁移脚本 
- 新增 app/tree/repair/regenerator.py（VLM 重生成 + 级联修复）
- supplement.py: deduplicate_field str() 防御 + inject_value strip
- patch.py: ruff format 格式化
- repair_trees.sh: conda source 激活修复
- 新增 migrate_from_trm4.sh 迁移工具
- enhance/__init__.py → repair/__init__.py 重命名

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-07-09 07:53:59 -04:00
iomgaa f57ee45dc0 fix: Codex 全量审查修正 
Critical:
- C1: assemble_mode 'plain' → 'ids'（合法枚举值）
- C2: question_id 加入 task_type slug 避免跨题型冲突

Important/Minor:
- generate_one 移除未用的 embed_fn/similarity_threshold 参数
- config.py 注释 11→12 同步
- 测试 question_id 断言更新

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-07-09 07:40:27 -04:00
iomgaa fad8147d71 refactor(question_gen): __init__.py 追加 synthesizer re-export 
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-07-09 05:49:05 -04:00
iomgaa 6e46d184b8 feat(harness): add factory.py — InferenceDeps dataclass + build_inference_deps 
组装一次推理所需的全套依赖的工厂函数：
- TreeIndex 加载（FileNotFoundError if missing）
- TreeEnvironment 构建
- SkillRegistry 按需发现
- SearchToolDispatcher 装配
- PromptManager + prompt_builder 闭包

测试覆盖：正常路径、缺失树文件、skills 注入、frozen 不可变性。

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-07-09 05:36:07 -04:00
iomgaa 5aa7cc48c5 feat(question_gen): is_duplicate + generate_one — 去重判定与单题生成编排 
- is_duplicate: 余弦相似度去重，空池短路
- generate_one: 异步重试循环，不含去重（由调用方汇总点原子执行）

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-07-09 05:32:39 -04:00
iomgaa 90f17e330e feat(question_gen): build_generation_prompt + parse_vlm_response 
- prompt 组装：system(角色+题型+约束+few-shot) + user(card+字幕+干扰项)
- VLM 响应解析：JSON 直接 + markdown code block 回退，四选一 schema 校验

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-07-09 05:28:25 -04:00
iomgaa 40b04f886e fix(question_gen): sample_anchor Codex 审查修正 
- C1/C2: Temporal Reasoning ≥3 L2 + Object Reasoning ≥2 L2 下限检查
- I1: L2 题型子帧不足时 ValueError
- I2: L3 过滤无 frame_path 的节点
- I3/I4: distractor_texts 扩展到整棵树范围
- I5-I7: 测试补强 Information Synopsis/Temporal Reasoning/Object Reasoning
- M1: Spatial Reasoning 测试断言 spatial_layout

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-07-09 05:24:30 -04:00
iomgaa a597a9f901 feat(question_gen): sample_anchor — 按题型层级采样锚节点 
含 6 种层级分支：L3 单帧、L2 多帧、Temporal Perception 特例、
L1 全量/采样 L2、L1-L2 混合。时间排序 + used_node_ids 排除。

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-07-09 05:18:25 -04:00
iomgaa 9eb9b86954 feat(question_gen): AnchorContext + 12 题型-层级映射常量 
- AnchorContext frozen dataclass: 锚节点生成上下文（node_id, card_text, frame_paths, subtitle, distractor_texts）
- TaskTypeSpec frozen dataclass: 题型生成规格（level, needs_frames, frame_count, context_fields）
- TASK_TYPE_LEVEL_MAP: 12 种 Video-MME 题型 → 树层级 + 生成规格映射
- 11 项单元测试覆盖：映射完整性、值类型、层级合法性、frozen 不变性

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-07-09 05:10:58 -04:00
iomgaa eb15ab315e fix(config): _VIDEO_MME_TASK_TYPE_COUNT 11→12，Video-MME 实际有 12 种题型 
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-07-09 05:08:05 -04:00
iomgaa 8c383354c5 fix(detector): 移除 ongoing_actions/visible_entities 空字段检测 + 新增 repair sh 
抽检确认这两个字段为空是合法内容状态（静物/黑帧/模糊帧），
VLM 重修也修不好，保留会导致断点续跑死循环。
L3 空字段检测缩减为 frame_summary + spatial_layout。
 2026-07-09 00:54:27 -04:00
iomgaa 8182cb86b1 feat(detector): 扩展空字段检测到 L2 event_description / L1 scene_summary 
断点续跑判据需要 L2/L1 层的 empty_field 检测。零 LLM 成本。
 2026-07-09 00:12:55 -04:00
iomgaa 53286ac3ab refactor: remove deprecated retriever module 
RecursiveRetriever was a failed approach, not carried into TRM5.
- delete app/retriever/ (empty placeholder)
- drop retriever + train blocks from config/default.yaml
- renumber fidelity checklist 13->12 items (drop #4, shift up)
- sync core-goal text, dir tree, module-interaction diagrams
  across CLAUDE.md, ARCHITECTURE.md, overview.md, README.md
- reference/ kept intact as historical code
 2026-07-08 23:09:30 -04:00
iomgaa 9a42bbcf85 style(harness): ruff format batching.py + log.py 2026-07-07 20:34:48 -04:00
iomgaa a668fc173c feat(harness): __init__.py public API + lint fixes 2026-07-07 13:45:48 -04:00
iomgaa d6e74f2734 feat(harness): runner.py — train loop orchestrator (#13 algorithm fidelity) 
Three-level nesting (epoch -> step -> per-skill), slow update 10-step
sequence, checkpoint/resume, early stop, probation accept/reject/rollback.

Key TRM4->TRM5 changes:
- sync -> async (all inference/diagnosis/evolve/validate awaited)
- LLMClient.from_env -> injected LLMProvider (DI via constructor)
- Direct DB/file access -> module functions (workspace/store/log)
- _TrainState as train() local, explicit param passing to helpers

Module-level pure functions extracted for testability:
resume_plan, _guard_infra_failures, _apply_batch_correctness,
_compute_total_steps, _should_early_stop, _format_applied_edits,
_fallback_summary, _write_skip_report, _outcome_to_quadrant_pairs,
_build_comparison_pairs, _batch_from_ids, _snapshot_current_skills.

Tests: 34 unit tests covering 13a-13e sub-tasks.
Radon: all functions Grade B or better.
 2026-07-07 13:43:20 -04:00
iomgaa 6baddcc17d feat(harness): validate.py — async 块序贯验证编排 + Probation 统一定义 2026-07-07 13:20:43 -04:00
iomgaa 8c9f7d2d37 feat(harness): checkpoint.py — TrainState 序列化 + 原子写 + 指纹校验 2026-07-07 13:13:37 -04:00
iomgaa 6b56fc8f98 feat(harness): inference.py — async run_inference + DI 2026-07-07 13:04:26 -04:00
iomgaa 49e272719e feat(harness): momentum.py — async 慢更新动量生成 2026-07-07 13:01:04 -04:00