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ViperEkura c50adbaac0 feat : replace AdamW with MuonMix (Muon + AdamW) optimizer 
- Muon for 2D matrix params, AdamW for 1D (norm/bias/embed)
- MuonMix wrapper handles combined step/zero_grad/state_dict
- New CLI args: weight_decay, muon_momentum, muon_nesterov, muon_ns_steps, muon_adjust_lr
- Removed adamw_beta1/adamw_beta2/adamw_weight_decay
- Moved optimizer/strategy params from signature to **kwargs
 2026-07-07 14:10:36 +08:00
ViperEkura 536dbc0c9a fix: set tqdm postfix before update so first step shows metrics 2026-07-07 00:14:13 +08:00
ViperEkura 4af7acd449 fix: support single .h5 file loading in load_h5 2026-07-07 00:11:16 +08:00
ViperEkura 53ed52b4b8 refactor: extension dispatch layer with CUDA/torch fallback 
- Add gqa_decode_attn/gqa_prefill_attn dispatch functions
- Internal _available/__modules with underscore prefix
- CUDA kernel path with F.scaled_dot_product_attention fallback
- GQA head expansion in fallback path
 2026-07-06 21:07:16 +08:00
ViperEkura f1cc7cedce feat: ldmatrix + smem padding for mma prefill kernel 
- replace scalar fragment loads with ldmatrix.sync.x4/x2
- add smem row-stride padding (LD = HEAD_DIM + 8) to eliminate 8-way bank conflicts from HEAD_DIM being a 32-bank multiple
- switch build flag from positive to negative: -DASTRAI_NO_MMA for pre-sm_80 only; mma is the default path
- vectorize scalar path smem loads with float4 ld8
- fix pure-C test configs for ld8 alignment
 2026-07-06 20:55:22 +08:00
ViperEkura ddc4bd1cf6 feat: tensor-core mma prefill with build-time dispatch 
- add register-resident flash-attention kernel using mma.sync.m16n8k16
- dispatch mma vs scalar at build time: pre-sm_80 defines
  -DASTRAI_NO_MMA, else defaults to mma
- scalar path vectorized with float4 smem loads (ld8)
 2026-07-06 20:33:24 +08:00
ViperEkura cc36530c73 perf: group-split register-blocking gqa_prefill kernel 
- one query row per group of G=8 lanes, each owning HEAD_DIM/G dims of qreg[]/acc[] in registers
- removes full 32-lane warp_reduce_sum; S dot reduces over only G lanes
- templated on <HEAD_DIM,G,ROWS,P_BC>, block=(G,ROWS)=(8,32)
- per-group shuffle mask so causal loop-bound divergence doesn't deadlock the shuffle
- update pure-C test to the templated launch
 2026-07-06 18:33:08 +08:00
ViperEkura 11fa807cfc fix: correct prefill mask index, unify GQA kernel interface 
- Fix mask indexing: batch*q_len*kv_len -> batch*kv_len
- Add csrc/kernels/gqa_common.cuh with shared GQAParams struct
- Unify decode/prefill Python API: both accept (q,k,v,mask=None,...)
- Decode now supports optional mask, is_causal, causal_offset, scale
- Rename struct fields: B->batch, Hq->q_head, Hk->kv_head, D->head_dim
- Use py::arg() for correct None/defaults handling in pybind11
- Update pure C tests and build instructions (-arch=sm_89)
 2026-07-06 17:21:23 +08:00
ViperEkura bcdd93e0eb feat: split kernel defs from bindings, add prefill tiled kernel and pure C tests 
- Split .cuh/.cu for gqa_decode_attn and gqa_prefill_attn
- gqa_prefill_attn: tiled shared-memory K/V, fused load, compute-opt, mask support
- Add pure C tests under csrc/tests/ for fast nvcc-only iteration
- Update .gitignore for build artifacts
 2026-07-06 16:14:55 +08:00
ViperEkura 579b8c3129 fix: correct gqa_decode_attn reduction + add gqa_prefill_attn 
- gqa_decode_attn: rewrite to per-KV-head, K in smem
- gqa_prefill_attn: new kernel for Q_len > 1 with GQA
 2026-07-06 13:45:18 +08:00
ViperEkura d7da51569f docs: update install instructions in EN/CN README 2026-07-06 12:25:36 +08:00
ViperEkura e8e228d035 feat: add optional CUDA kernel system (csrc/) + fused GQA decode attention 
Structure:
  csrc/               -- .cu sources + build.py registry
  astrai/extension/   -- compiled .so + __init__.py (import dispatcher)
  setup.py            -- CUDAExtension from csrc/build.py REGISTRY

Control: CSRC_KERNELS=true|false env var at install time.
Fallback: astrai.extension.available dict for runtime detection.
 2026-07-06 12:09:58 +08:00
ViperEkura 2579658e15 chore : shields release badge from /release to /tag 2026-07-05 20:34:40 +08:00
ViperEkura f0cd0134c6 fix : update benchmark for v1.3.8 cache API, add argparse and cache type switch 
- Replaced old KVCage API with PageCache/ContiguousCache
- Added --cache contiguous|paged switch for decoding comparison
- Added argparse for all params (batch/prompt/gen/device/dtype)
- Fixed PageCache decode crash by extending pages for full sequence
 2026-07-05 20:30:26 +08:00
ViperEkura abb96996f8 docs : sync 6 doc files to actual code 
- architecture.md: removed TrainConfig.log_interval, split KVCache into
  PageCache/ContiguousCache with CacheView/PageCacheView/ContiguousCacheView,
  added JsonlStore, fixed GradientCheckpointingCallback type,
  CheckpointCallback typo, ProgressBarCallback hooks
- training.md: added position_ids to SFT keys, fixed callback hook table,
  removed merged ValidationCallback
- inference.md: documented ContiguousCache default vs PageCache paged
- dataflow.md: added JsonlStore to storage backends and format detection
- params.md: removed nonexistent --log_interval
- preprocessing.md: updated timestamp
 2026-07-05 19:35:18 +08:00
ViperEkura bbe6ff2d8f release : v1.3.8 
- refactor: 重写 IFD 评估为三层架构，引入 BFD 装箱与自定义 attention mask 批处理打分
- refactor: 重写 HumanEval 评估为函数式流水线，修复测试超时与动态 pass@k
- perf: 替换 paged KV cache 为 ContiguousCache，解码所有 group
- feat: 新增 ROUGE 评估脚本、JSONL 数据集 store、stream_chat 参数
- fix: 修复 IFD token-set 不对称、SFT position_ids 默认值、文档边界保留
 2026-07-05 19:12:33 +08:00
ViperEkura db9b39b084 fix: resolve IFD token-set asymmetry and support single-token answers 
- Sentinel-anchored unconditional pass: both branches now predict the same N response tokens
- Single-token responses (rl=1) fully supported
- ctx_len tracked per sample; skip_reason replaces silent None
- --per_token flag for per-token IFD breakdown
 2026-07-05 17:48:26 +08:00
ViperEkura 849e1e00a3 refactor: clean up inference design patterns 
1. KVCache base: add default task_cached/task_record_hashes, remove getattr from scheduler
2. Remove page_size param from scheduler constructor (ContiguousCache-only)
3. InferenceEngine expose cache param for KVCache injection
4. Rename page_cache -> kv_cache in Executor
5. Move stream_callback from Task to TaskManager._callbacks dict
6. TaskManager.clear_queues clears callbacks
 2026-07-05 11:41:54 +08:00
ViperEkura 5416c2e8fb perf: replace paged KV cache with contiguous ContiguousCache, decode all groups 
- Add KVCache/CacheView abstract base classes in cache.py
- Add ContiguousCache (contiguous per-slot buffer, default) alongside PageCache (paged, renamed from old KVCache)
- Merge make_table_tensor + bind into bind_tasks on KVCache interface
- Remove task_cached/task_record_hashes from base class (PageCache-only)
- Scheduler: decode all position groups instead of just the largest (eliminates 63% group skip rate)
- Scheduler: accept optional cache param for swapping implementations
- Model layer type hints use CacheView base class
- Batch 1-32: 1-7% speedup from eliminating Storage.gather overhead
- All 183 inference tests pass
 2026-07-05 11:34:36 +08:00
ViperEkura 599a51f4f7 fix: reliable test timeout, separate generate/test phases, dynamic pass@k 
- Replace SIGALRM+exec() with subprocess.run(timeout=) for test execution
- Add --test_only flag to skip generation and test existing completions
- Add --generate_only flag for generation-only runs
- Derive pass@k values from num_samples (filter k > n)
- Support loading completions from array JSON (not just JSONL)
 2026-07-05 08:47:30 +08:00
ViperEkura 17d6eaa2f2 refactor: rewrite humaneval evaluation with functional pipeline design 
- fix KeyError race condition in inference cache touch()
- EvalConfig dataclass for centralized configuration
- load->generate->extract->test->score->report pipeline
- two-phase generation+testing for max GPU utilization
- signal-based SIGALRM timeout protection for code exec
- suppress subprocess stdout/stderr pollution
 2026-07-05 07:58:28 +08:00
ViperEkura 2d908639e9 feat : add ROUGE evaluation script (manual impl, no deps) 
- ROUGE-1/2 via n-gram overlap (Counter)
- ROUGE-L via LCS (DP)
- CLI: python scripts/eval/evaluate_rouge.py --data_path ... --output ...
- Library: compute_rouge(ref, cand) -> dict of precision/recall/f1
 2026-07-05 01:15:01 +08:00
ViperEkura c7158418dd perf: add BFD bin-packing and custom attention mask to IFD batch scoring 2026-07-04 18:58:13 +08:00
ViperEkura 4d3c9341c1 refactor: rewrite IFD evaluation with clean three-layer architecture 2026-07-04 18:33:51 +08:00
ViperEkura 4e508afa2d fix : SFT pipeline position_ids default & doc boundary preservation 
- change position_ids_mode default from "none" to "doc_reset" so SFT preprocessing always generates position_ids (was causing dataset load KeyError)
- generate per-doc position_ids before packing (doc_reset mode), preserving document boundaries for BFD packing (cross-doc attention leak fix)
- change _align_bucket padding from [1] to [0] to avoid accidentally training on loss_mask padding
 2026-07-04 15:59:11 +08:00
ViperEkura 8999ca89b8 feat: add JSONL dataset store with on-the-fly tokenization 
- Add JsonlStore registered under "jsonl" in astrai/dataset/storage.py
- Reuse PipelineConfig schema for JSONL dataset configuration
- Update detect_format to recognize JSONL directories and files
- Move save_h5/load_h5/save_bin/load_bin to astrai/serialization
- Split astrai/serialization.py into checkpoint/dataset submodules
- Add tests for JSONL detection, seq/SFT stores, and config roundtrip
 2026-07-04 15:42:33 +08:00
ViperEkura 1adca39cd8 fix: handle long sequences and optimize IFD computation 2026-07-04 08:35:45 +08:00
ViperEkura 204873fa2f fix: handle long sequences and optimize IFD computation 2026-07-04 08:23:32 +08:00
ViperEkura a5c1de6b1b feat: add model_path temperature top_p top_k max_tokens system_prompt args to stream_chat 2026-07-04 07:33:32 +08:00
ViperEkura 27524ad085 fix: reset sampler iter at epoch end so progress bar shows total after first epoch 2026-07-04 06:35:55 +08:00
ViperEkura 27d1921d9c fix: scheduler division-by-zero, loss_mask bool 
- schedule.py: guard warmup_steps/lr_decay_steps against zero
- strategy.py: use ~loss_mask instead of loss_mask==0 on bool tensor
 2026-07-03 22:04:55 +08:00
ViperEkura 70c0e5de90 refactor: merge validation into MetricCallback, simplify progress bar to optimizer steps 
- Remove separate ValidationCallback, merge into MetricCallback
- Progress bar now tracks optimizer steps instead of micro-steps
- Remove unused log_interval config field and CLI flag
- Fix validation all_reduce: use SUM(loss, count) instead of AVG
- Simplify metric logging: always log every optimizer step
- Add grad_norm display to progress bar
 2026-07-03 21:43:08 +08:00
ViperEkura dfb151537b fix: ForwardRef._evaluate Python 3.12 compatibility 2026-07-03 18:41:19 +08:00
ViperEkura 500c605fad fix: unify scheduler min_rate default to 0.01, clamp WSD warmup 2026-07-03 17:52:23 +08:00
ViperEkura dc9faca3b1 fix: align docs with actual code (40+ inconsistencies) 
- Remove nonexistent Muon class from architecture diagram
- Fix Checkpoint/TrainConfig/TrainContext field names (iteration -> consumed_samples, start_batch -> start_samples)
- Add missing fields: neftune_alpha, val_split, grad_norm, optimizer_step, tool_calls/tools
- Fix CLI param defaults: --log_interval 1, --metrics [loss,lr,grad_norm], --start_samples
- Add missing scheduler CLI params; remove nonexistent --num_workers from preprocess docs
- Fix inference SSE format, stats response keys, error codes to match actual server output
- Fix preprocessing docs: BOS once, shard_0000 layout, from_json->from_file, GRPO prompts_mask
- Fix dataflow detect_format/_normalize descriptions; correct callback order in training.md
 2026-06-30 20:47:23 +08:00
ViperEkura aabb0d83e9 refactor : replace iteration with consumed_samples 
- Replace context.iteration with consumed_samples (global sample count)
- Add optimizer_step property derived from consumed_samples
- Checkpoint meta.json stores consumed_samples, drops iteration
- CLI --start_batch renamed to --start_samples (per-rank samples)
- Checkpoint dir naming: epoch_X_step_Y instead of epoch_X_iter_Y
- Metric log entries use step and consumed_samples fields
- Backward compat removed (old iteration checkpoints unsupported)
 2026-06-30 18:42:42 +08:00
ViperEkura 44579ea6dc refactor : metric 日志改为以 optimizer step 为单位，默认每步记录 
- log_interval 默认 100 -> 1，语义从 batch iteration 改为 optimizer step
- step 指标从 on_batch_end 移到 on_optimizer_step，不受梯度累积影响
- JSONL 条目新增 step 字段，保留 iter
- flush 落盘仍在 on_batch_end
 2026-06-30 15:12:31 +08:00
ViperEkura 0f1fcb079f refactor : grad_norm 指标简化，clip_grad_norm 移至 executor 
- metrics 默认加入 grad_norm，移除 grad_std/max/min/mean/nan_num
- grad_norm 默认返回总 L2 范数，per_param=True 返回各参数范数
- clip_grad_norm 从 callback 移至 BaseExecutor/FSDPExecutor
- FSDPExecutor 覆盖为 model.clip_grad_norm_() 保证分布式正确
- ctx_get_grad_norm 改为读取 context.grad_norm
 2026-06-30 14:59:43 +08:00
ViperEkura 84d4769163 feat: SVD 有效秩/权重统计分析脚本 2026-06-29 21:39:22 +08:00
ViperEkura bf09a35c95 feat: optimizer 参数分组，bias/norm 不做 weight decay 2026-06-27 16:30:34 +08:00
ViperEkura 6715461a36 chore : 升级 torch 2.11.0+cu128，移除自定义 Muon，修复 gloo device_id 
- torch 2.7.1-cu126 升级至 2.11.0-cu128，numpy 2.3.2 升级至 2.4.4
- 移除 astrai/trainer/optim.py，改用 torch.optim.Muon
- parallel setup: gloo 后端不再传递 device_id，单卡多进程不再报错
 2026-06-27 16:10:37 +08:00
ViperEkura b4587c5d08 refactor : metric_logger 改用事件类型 (type=step/validation/epoch) 
- 每种事件独立 schema，不再混入 null 字段
- 回调顺序 validation 移到 metric_logger 之前，确保 on_optimizer_step 先跑
- 用内部 _last_val_loss 代替 TrainContext.last_val_iter 判断新验证
- 修复 factory.py 未使用导入、evaluate_ifeval.py 多余 f 前缀
 2026-06-25 17:18:20 +08:00
ViperEkura 88ec63121d feat : GPT-2 residual scaling weight init 
- Linear: normal(0, init_std) replaces kaiming_uniform_(a=sqrt(5))
- o_proj / mlp.down: init_std = 0.02 / sqrt(2 * n_layers)
- MoE: expert down scaled by 1/sqrt(1/n_shared + 1/K)
- Embedding: normal(0, 0.02), unchanged
 2026-06-25 15:08:31 +08:00
ViperEkura 01d2da2893 feat : 训练支持 --schedule_type 及对应调度器参数 
- --schedule_type 可选 cosine/sgdr/wsd，默认 cosine
- --min_rate 统一控制最小 LR 比率
- --cycle_length / --t_mult 用于 sgdr
- --stable_steps / --decay_steps 用于 wsd，自动计算默认值
 2026-06-22 10:35:56 +08:00
ViperEkura 25d4ea3f91 refactor : 压缩测试代码，消除重复 
- fixture 替代重复实例化和 tokenizer 落盘
- parametrize 合并同构测试
- helper 消除 save_h5 + DatasetFactory.load 样板
- 净减 272 行
 2026-06-19 14:54:39 +08:00
ViperEkura 39985840c7 refactor : neftune_alpha 在 Embedding 构造时传入，由模型配置链路负责 
- BaseModelConfig 添加 neftune_alpha 字段 (默认 0.0)
- Embedding.__init__ 接受 neftune_alpha 参数，不再外部 set
- AutoRegressiveLM / EmbeddingEncoder 从 config 传入 neftune_alpha
- train.py 将 CLI 参数注入 config 后再创建模型
- TrainContextBuilder 移除 neftune 设置（不再是其职责）
 2026-06-19 14:23:27 +08:00
ViperEkura b1adc40cfb refactor : 将 config 对象直接传给 DecoderBlock，替代 16 个独立参数 
- DecoderBlock.__init__ 改为 (config, layer_id)，内部用 asdict
  展开字段给 AttnFactory/FFNFactory，factory 按 __init__ 签名自动过滤
- EncoderConfig 补充 attn_type 和 ffn_type 字段
- 314 个测试全部通过
 2026-06-19 14:15:33 +08:00
ViperEkura 7348bac6ab fix: 规范 generate.py 命令行接口 
- generate.py 清理描述文字，help 统一标注默认值
- max_tokens 默认改为 None，回退 model config max_len
- evaluate_ppl.py 同步清理描述文字
- params.md 同步 max_tokens 默认值
 2026-06-19 14:03:02 +08:00
ViperEkura 8ab7564d02 docs: 重构 README 结构，全文档添加目录导航 
- README 新增 Getting Started 端到端流程，整合快速开始与演示，去重精简
- 中文 README 同步英文版结构，预处理配置改用 seq 策略
- inference.md 补充 SSE 流式格式、错误响应、/stats 端点文档
- params.md 扩展为 CLI 参考，覆盖 server/generate/preprocess 参数表
- dataflow.md 拆分 tokenization/format detection/backend 子节，新增流程图
- architecture/training/inference/preprocessing 均添加目录导航
- 移除 README CI badge
 2026-06-19 13:53:22 +08:00
ViperEkura d096b6e29e docs: 修复文档中过时的字段、签名和缺失的类 
- BaseConfig 的 from_json/to_json → from_file/to_file
- InputConfig/ProcessingConfig/OutputConfig 字段对齐源码
- 移除不存在的 Registry 类，register() 去 category/priority
- SchedulerFactory.create 参数顺序修正
- 架构图/训练/参数文档补全 WSDScheduler
- CONTRIBUTING.md 克隆地址占位符修正
- params.md label_smoothing 默认值修正，补全 neftune_alpha
- app 类更正为 get_app 函数
 2026-06-18 18:49:46 +08:00
ViperEkura d88a41f8f1 fix: 修复预处理流水线 4 个致命问题 
- pipeline: 单条数据异常不再崩溃整条流水线, 改 log warning 后跳过
- pipeline: _align_bucket 统一用 len(ids) 填充, 修复多输出模式下长度错配
- writer: BinWriter/H5Writer 写入失败自动清理残留文件并记录详细错误
- packing: BFDPacking 真正将序列打包进 bin 而非仅重排, 减少碎片
 2026-06-18 17:38:01 +08:00
ViperEkura 376e9eba80 feat: IFEval 使用 chat template 格式化 prompt，添加 model.eval() 
- generate_one 用 tokenizer.apply_chat_template 包 user 消息
- 新增 model.eval() 关闭 dropout，确保确定性输出
 2026-06-18 16:45:16 +08:00
ViperEkura a62c2e11a2 feat: IFD 默认使用 chat template，支持裸文本模式 
- 新增 _compute_ifd_with_template，用 tokenizer chat template 格式化后计算 IFD
- 默认开启 chat template，可通过 --no_chat_template 切换回裸拼接
- chat template 缺失时给出 RuntimeError 提示
 2026-06-18 16:35:05 +08:00
ViperEkura a4e5a8c81c feat: 新增 WSD 学习率调度器 
- 支持 Warmup-Stable-Decay 三段式调度
- stable 阶段保持最高 lr，decay 阶段 sqrt 衰减
- 适用于持续预训练、SFT、RLHF 场景
 2026-06-18 15:55:15 +08:00
ViperEkura 3e234c46f6 fix: 使用 threading.Event 替代裸 bool，补全公共 API 
- scheduler 停止信号改用 threading.Event，跨解释器安全
- 移除 _fatal_error 和 check_health，异常仅用 logger.error 记录
- 补全 astrai/__init__.py，暴露所有主要模块
 2026-06-18 15:38:35 +08:00
ViperEkura 7a04b1f8ce docs: replace shields.io endpoint badges with github/ direct badges 
- Switch stars/forks/release to github/ endpoints to avoid pool exhaustion
- Add CI workflow badge for tests.yml
- Delete update-badges.yml (no longer needed)
- Remove remote gh-pages branch
 2026-06-18 15:09:51 +08:00
ViperEkura a30e3d5114 fix: 修复 shields.io GitHub badge 因 token 耗尽而无法显示 
- 新增 Action 每天及 push 时同步 badges 至 gh-pages
- README 改用 endpoint 格式指向自建静态 JSON, 不依赖 shields.io GitHub token 池
- 同步更新中英两份 README
 2026-06-16 22:21:58 +08:00
ViperEkura 1818d06576 feat: 新增 IFD 数据质量评分工具, 移动 ppl 至 eval 
- 计算指令遵循难度分数用于数据筛选
- IFD = 条件交叉熵 / 无条件交叉熵
- perplexity 移至 scripts/eval/
 2026-06-16 22:03:45 +08:00
ViperEkura 4e8d1ee24e feat: 新增 IFEval 指令遵循评测 
- 实现 25 种正则约束 verifier
- 将评测脚本从 scripts/tools/ 移至 scripts/eval/
 2026-06-16 21:57:34 +08:00
ViperEkura fec376b0dd fix : 修复策略相关文件的类型注解与抽象方法体 
- 修复 strategy.py 单元素 Union 与缺失的参数/返回类型注解
- 修复 train_context.py 8 个 default=None 字段缺 Optional 标记
- 修复 sample.py/packing.py/position_id.py 方法缺参数及返回类型注解
- 修复 factory.py _resolve_type/list_registered 缺类型注解
- 修复 train_config.py 裸 dict/list 缺泛型参数
- abstractmethod body 从 ... 改为 raise NotImplementedError
- feat : checkpoint meta.json 保存 TrainConfig 超参供人工查阅
 2026-06-14 16:20:10 +08:00
ViperEkura a2512f8a5a fix : resume_dir 无权重文件时不强制加载，支持仅配置训练 
- Checkpoint.load_any 统一处理 meta.json / model.safetensors / 无文件三种情况
- train_context.py 调用简化为单一路径，移除 load_model_weights 直接依赖
 2026-06-13 15:40:14 +08:00
ViperEkura 457e16ea3c fix : val_loss 默认改为 None，日志跳过空值；val_dataloader 补 Optional 注解 2026-06-13 14:24:13 +08:00
ViperEkura daf627a6de fix : _save_log 前确保日志目录存在，防止跨进程反序列化后目录丢失 2026-06-12 15:39:54 +08:00
ViperEkura 445378667f feat : NEFTune 噪声注入 + label_smoothing 默认值修正 
- Embedding.forward 训练时注入 randn 噪声，缩放系数 neftune_noise_alpha / sqrt(seq_len)
- TrainConfig.neftune_alpha 通过 config 传递（默认 0=关闭）
- TrainContextBuilder 将 config.neftune_alpha 写入 embed_tokens
- --neftune_alpha CLI 参数（典型值 5.0）
- label_smoothing 默认值 0.05 -> 0.0
 2026-06-11 15:32:43 +08:00
ViperEkura 6ae1828449 refactor : 清理工厂和配置系统中的死代码与冗余抽象 
- 删除 Registry 中未使用的 category/priority 字段，_entries 简化为直接存储类引用
- 修正 __init_subclass__ 避免叶子类（AutoRegressiveLM 等）创建空注册表
- 删除 5 个工厂的薄 create() 覆写，统一使用 BaseFactory.create(name, *args, **kwargs)
- 删除 3 处零调用的 available_types/available_strategies 别名死代码
- 删除零调用的 BaseModelConfig.to_file 死代码
- 将 BaseConfig.from_json/to_json 重命名为 from_file/to_file，消除与子类重复
- 移除两个 inference builder 中总是被覆写的 prompt_tokens=0
 2026-06-07 11:39:50 +08:00
ViperEkura e7b18b7c03 refactor : BaseFactory 基类类型自动推导 + 移除冗余代码 
- _validate_component 从 BaseFactory[T] 泛型参数自动解析基类类型，9 个子类覆写移除
- Registry 类内联到 BaseFactory._entries，移除未用的 list_by_category/list_by_priority
- _component_base 在 __init_subclass__ 时立即解析
- 数据集 4 个子类冗余 __init__ 移除
 2026-06-06 21:23:41 +08:00
ViperEkura 9e31d4ef2b feat : BaseToolParser.feed 增加可选 token_ids 参数 
- format_chunk ABC 改为 (token, **kwargs)，body/token_ids 通过 kw 传入
- ProtocolHandler._handle_stream 逐 token encode 并透传
- Anthropic builder 用 **kwargs 吸收不使用的参数，零变更
- 新增 3 个 token_ids 参数测试
 2026-06-06 11:19:30 +08:00
ViperEkura 52aa4d01d5 feat : 推理层增加 vLLM 风格工具调用解析 
- 新增 BaseToolParser 抽象基类，定义 feed/parse_complete 流式接口
- 新增 SimpleJsonToolParser，解析 {"name":"...","arguments":{...}} 格式
- 新增 ToolParserFactory，基于 BaseFactory 实现可插拔注册
- 集成 parser 到 OpenAIResponseBuilder，支持流式/非流式工具调用
- 扩展 ChatMessage 和 ChatCompletionRequest，增加 tools/tool_choice 字段
- 重构 format_chunk 接口，传入累积文本支持全量重新解析
- 新增 74 个单元测试，覆盖扫描/查找/流式解析/完整解析/工厂
 2026-06-06 08:54:10 +08:00
ViperEkura 986be957ec refactor : on_batch_begin 移入 accumulate 上下文 2026-06-06 01:19:21 +08:00
ViperEkura cf9c60841b docs : 按代码反向修正所有文档错误 
- 更新预处理模块目录结构和类名（SectionedMaskBuilder）
- 修正 ResponseBuilder.prepare 签名（tokenizer → engine）
- 补全缺失的 CLI 参数、配置字段和数据键名
- 修正 README 中 download.py 的描述
 2026-06-06 01:06:30 +08:00
ViperEkura 31bc7f5c2a refactor : pipeline 策略化拆分，消除 _flush if/else 
- PackingStrategy / PositionIdStrategy / StoreWriter 独立文件 + Factory
- Pipeline._flush 零 if/else，纯编排
- SectionRenderer 从 SectionedMaskBuilder 分离
- OutputConfig.position_ids_mode 默认改为 ""none""
 2026-06-06 00:45:33 +08:00
ViperEkura 3057741de9 refactor : 合并 data config docstring 并实现 BFD 打包策略 
- 将 ProcessingConfig/OutputConfig 参数描述合并到类级 docstring

- Pipeline 支持 packing_strategy/truncation_mode，新增 bfd 打包
 2026-06-05 17:41:51 +08:00
ViperEkura acd1103bd0 fix : 使用 bool 注意力掩码并支持打包 SFT 文档边界阻断 
- 简化 process_attention_mask，通过广播返回 bool 掩码
- 新增 make_doc_boundary_mask 生成块对角因果掩码
- SFT strategy 传入文档边界掩码
 2026-06-05 17:02:28 +08:00
ViperEkura dc7d2cfbca refactor : FastAPI 懒加载单例，消除模块级副作用 
- import astrai.inference 不再在模块加载时创建 FastAPI 实例
- 路由移至 APIRouter；get_app() 首次调用时懒构造单例
- _create_engine 和 run_server 的 param_path 改为必填
- 更新测试改用 get_app() 替代模块级 app
 2026-06-04 15:52:27 +08:00
ViperEkura b36a78c612 test : SFT 测试数据补全 position_ids 字段 
- dummy_data 添加 position_ids 匹配 required_keys
 2026-06-04 14:01:04 +08:00
ViperEkura 985d940db6 feat : 数据流水拼接策略支持 position_ids 预计算 
- OutputConfig.position_ids_mode 三种模式控制边界策略
- pipeline._flush() 按配置生成扁平 position_ids 数组
- SFTDataset 在 __getitem__ 中返回 position_ids
- SFTStrategy 将 position_ids 传入 model.forward()
 2026-06-04 13:56:19 +08:00
ViperEkura 5e73ca20aa feat : train CLI 新增 val_split/val_step/metrics/log 参数 
- --val_split 从训练集按比例切分验证集
- --val_step 控制验证间隔 optimizer step 数
- --metrics 自定义日志指标列表，默认 loss lr
- --log_dir / --log_interval 控制日志输出目录和频率
 2026-06-03 14:31:22 +08:00
ViperEkura 438dc10391 fix : MMLU eval 使用 chat template 格式匹配 SFT 训练数据 
- 原 prompt 为纯文本格式，与 SFT chat template 不匹配导致模型输出随机
- 新增 apply_chat() 将 MMLU prompt 包装为 user/assistant 对话格式
- choice_text 改为单字母（去掉空格前缀）适配模板输出
- 5-shot 时 few-shot 示例作为独立 user/assistant 轮次插入
 2026-06-03 11:59:42 +08:00
ViperEkura 615ba5d8ef feat : 新增 HumanEval pass@k 代码生成评测 
- InferenceEngine.generate() 批量生成 n 个补全
- 正则提取函数体 + 停止符截断
- multiprocessing sandbox 执行 + timeout 保护
- 标准无偏 pass@k 公式 (1, 10, 100)
 2026-06-03 10:52:32 +08:00
ViperEkura 02a7cb9fa0 feat : preprocessing 支持 DPO/GRPO 多输出格式 
- InputConfig 新增 sources 字段驱动多输出映射
- SectionedMaskBuilder 提取 _process_sections/_build_multi 模板方法
- Pipeline 泛化 accumulate 逻辑处理多 key 结果
- 测试拆分为 config/builder/pipeline 三文件，纯函数风格
 2026-06-03 10:32:10 +08:00
ViperEkura 9fe2121743 feat : TrainConfig 支持 val_split 从训练集自动切分验证集 
- val_split 比例从 dataset 中划出验证集，用 random_seed 固定随机切分
- 若 val_dataset 已显式设置则跳过自动切分
 2026-06-02 20:33:40 +08:00
ViperEkura 0422d6d38e refactor : 移除 LocalStrategy._clear_env 冗余清理 
- setup_parallel 已覆盖所有环境变量写入，无需前置清空
 2026-06-02 11:40:45 +08:00
ViperEkura 9b416c1bbb refactor : 并行启动 Strategy 模式重构，local_rank 解耦 
- setup_parallel 接收 local_rank 参数，不再读环境变量推导
- TorchrunStrategy 从 env 读取 LOCAL_RANK，LocalStrategy 用 rank
- _detect_launcher() 分级检测替代内联 RANK 检查
- _run_single_rank 统一入口，消除 _run_single/_run_multi 重复
- 优雅退出：except BaseException 终止子进程并 re-join
- gradient_checkpointing_modules 判定提取到外部变量
 2026-06-02 11:22:24 +08:00
ViperEkura 01ce1fb9e3 refactor : Pipeline 去除去重，ids 重命名为 sequence，泛型透传 
- 移除 Pipeline 内置去重逻辑及 dedup_signature 工具函数
- 删除 ProcessingConfig.deduplicate 字段
- builder 返回 'sequence' 替代 'ids'，与 dataset 层统一
- pipeline 纯透传，泛型处理任意 key 补齐默认值
 2026-05-31 15:14:27 +08:00
ViperEkura 14f83cbdac perf : 预编译 Jinja2 Template，避免每次 render 重新构建 2026-05-31 14:50:16 +08:00
ViperEkura dbe5891201 refactor : 统一 SectionedMaskBuilder，支持可配置 dtype 
- 三合一 MaskBuilder，移除 chat/instruction/text，统一为 sections 配置
- OutputConfig 增加 dtype 字段 (per-key，默认 int32)
- 移除 from __future__ import annotations
- 测试适配新配置格式
 2026-05-31 14:24:10 +08:00
ViperEkura 2a65c3314c fix : 修复 created 时间戳、bin 多 shard 覆盖与文档遗漏 
- openai.py/anthropic.py: created 从 0 改为 int(time.time())
- openai.py: ChatCompletionRequest 不支持参数非默认值时 warning
- pipeline.py: bin 多 shard 使用子目录避免静默覆盖
- storage.py: MmapStore/detect_format 支持多 shard 聚合加载
- architecture.md: mermaid 类图新增 Pipeline 类
- preprocessing.md: 新增多 shard 输出布局与 Python API 示例
- protocol.py: docstring "6 methods" 改为 "5 methods"
 2026-05-30 23:03:42 +08:00
ViperEkura 1c2ff05a6d docs : 三轮深度验证修复文档与代码不一致 
- architecture.md: 修正 unwrap_model 返回类型、Config Optional 标注、方法签名错误、类名错误
- training.md: 补充 on_error 回调、修正训练循环顺序、补全策略参数、model.safetensors
- inference.md: 修正 GenerationRequest 参数顺序、async 语法、KVCache 描述、temperature 约束
- dataflow.md: 补充 Store.load/fetch 流程、修正可选参数默认值
- README/params: 多 GPU 示例补全 --parallel_mode、文档表补充 preprocessing.md
- preprocessing.md: Chat 模式算法补全 BOS token 步骤
 2026-05-30 21:41:06 +08:00
ViperEkura 31ae2deeba refactor : BaseConfig 提供 from_json/to_json，嵌套 config 自动反序列化 
- from_json/to_json 上提至 BaseConfig，所有子类自动继承
- _coerce 新增 dict 到 BaseConfig 子类的递归反序列化，消除子类 from_dict 重载
- PipelineConfig 等子类仅声明字段，零样板代码
- 测试 tokenizer 改为自包含 BPE（含 chat template），不依赖 params/ 目录
- 特殊 token 改用 ASCII 字符，兼容所有平台
 2026-05-30 21:04:19 +08:00
ViperEkura 69207e2c57 refactor : 基于声明式 JSON 配置的预处理管线重构 
- 用工厂注册的 MaskBuilder（chat/instruction/text）替换硬编码的 _transform_* 方法
- mask 规则以 role-to-action 映射声明在配置中，与 chat_template 完全解耦
- 单次编码 + role-span 追踪替代两次编码 + 长度差计算 mask 的方式
- 支持多轮对话训练：所有 assistant 轮次参与训练，而非仅最后一轮
- 新建 astrai.preprocessing 包（builder.py + pipeline.py），删除 astrai/preprocess.py
- CLI 精简为 --config 参数，所有参数通过 PipelineConfig JSON 配置
- 新增 PipelineConfig、InputConfig、ProcessingConfig、OutputConfig dataclass
- 文档：assets/docs/preprocessing.md
- 27 个测试覆盖 mask builder、pipeline、配置序列化、工厂注册
 2026-05-30 20:45:09 +08:00
ViperEkura 138c5bcc08 feat : 添加 JSONL 预处理管线 
- Pipeline 模板, Reader 加 transform 加 Writer 可组合
- 自动检测 JSONL 格式, 支持 messages 文本 prompt 加 response 三种
- chat 数据通过 apply_chat_template 适配, 自动生成 loss_mask
- 输出对齐 Store 和 DatasetFactory, 直接用于训练
- 默认 bin 格式, CLI 入口 scripts/tools/preprocess.py
 2026-05-30 17:12:42 +08:00
ViperEkura a923e0a23a fix : 修复 MMLU 评测脚本数据源和依赖 
- 数据源改为 Berkeley data.tar（GitHub zip 不含数据文件）
- urllib 替换为 requests，支持代理下载
- zip 解压替换为 tar，增加目录 flatten 逻辑
- 添加 model.eval() 确保推理模式正确
 2026-05-30 16:51:24 +08:00
ViperEkura f521a30b22 fix : FSDP 优化器顺序、温度除零、调度器静默死亡、ref模型设备 
- executor: use_orig_params 硬编码 True，FSDP 不替换 Parameter 对象
- strategy: DPO/GRPO ref 模型创建后移到 device
- sample: TemperatureStrategy clamp 1e-8，engine 验证改为 >0
- scheduler: 异常不 re-raise 避免 daemon 静默死亡，stop() 发回调给 waiting 任务
 2026-05-29 21:57:44 +08:00
ViperEkura d4451f6afb fix : 并行训练 state_dict 收集与训练/推理并发缺陷 
- FSDPExecutor: unwrap_model 返回全量 state_dict (state_dict_type FULL)；use_orig_params=True
- DDPExecutor/BaseExecutor: unwrap_model 统一返回 model.module.state_dict() / model.state_dict()
- CheckpointCallback: 走 executor.unwrap_model 拿完整 state_dict
- strategy.py: 移除 FSDP/DDp 依赖；create_ref_model(model_fn, state_dict) 纯函数
- TrainContextBuilder: 传递 model_fn + executor 到 strategy
- GRPOStrategy.sync_ref_model: 通过 executor.unwrap_model 获取完整权重
- TaskManager.wait_for_tasks: 锁内检查队列，消除 clear/set 竞态
- ProtocolHandler: stop token 不再计入 completion_tokens（流式/非流式）
 2026-05-29 21:12:52 +08:00
ViperEkura a3275423a4 release : v1.3.7 
Features
- FSDP parallel backend with zero-redundancy sharded training
- LoRA fine-tuning module with low-rank adapter injection and persistence
- NTK-Aware RoPE dynamic scaling, extending context window limit
- MMLU evaluation script for standardized model knowledge assessment
- load_json/load_safetensors broadcast mechanism for cross-node distributed loading

Refactors
- Storage layer refactored to Store pattern, removed Fetcher layer, supporting multi-segment data with explicit length
- Training backend refactored to Executor pattern (none/ddp/fsdp), decoupling parallel logic
- Inference protocol layer refactored to Strategy/Builder pattern with independent OpenAI/Anthropic responders
- Unified serialization layer, eliminating scattered I/O paths
- Removed JSONStore from data pipeline, unified to H5/Bin dual format
- Simplified _disable_random_init, moved scheduler into sync block
- Removed -> None return annotations, split FSDP parameters

Fixes
- Disabled DDP static_graph to prevent no_sync/backward conflict under PyTorch 2.7.1
- Checkpoint resume restores optimizer/scheduler state and sampler remaining length
- Unwrap DDP/FSDP on checkpoint save to avoid module. prefix
- start_epoch/start_batch determined by user args, no longer overridden by checkpoint
- Left padding in perplexity.py causing incorrect PPL with batch>1
- Storage multi-segment bug, switched JSON to JSONL
- Early abort on task_extend failure after decode, notify waiting tasks on scheduler crash

Docs
- Synced architecture/training/inference/dataflow/params docs to actual code

Tests
- Completed inference protocol layer unit test coverage
- Added LoRA module tests
- Filled storage layer test gaps
 2026-05-29 17:46:03 +08:00
ViperEkura b37c3d000c docs : 同步文档与实际代码 
- 移除 JSONStore 引用（该类不存在）
- 修正 Store.load() 和 DatasetFactory.load() 签名（无 tokenizer 参数）
- 修正 TrainContextBuilder.with_resume_dir() 命名
- 修正 Checkpoint config 字段和 meta.json 描述
- 修正 ProtocolHandler.handle() 异步签名
- 修正采样继承图（平行子类，非线性）
- 修正训练循环：回调移入 accumulate 块内
- 更新文档日期至 2026-05-28
 2026-05-28 21:01:47 +08:00
ViperEkura 6031020e37 feat : load_json/load_safetensors 支持 broadcast，跨节点分布式加载 
- load_json/load_safetensors/load_state_dict 新增 broadcast 参数
- broadcast=True 时 rank-0 读取后 broadcast_object_list 分发到所有 rank
- load_state_dict 改为逐张量 broadcast，避免大模型 pickle 内存瓶颈
- 删除 _get_meta/_get_config wrapper，Checkpoint.load 直接调用 load_json
- 参数注解 str | Path 统一为 Union[str, Path]
 2026-05-28 20:44:58 +08:00
ViperEkura c424dfc293 feat : checkpoint 支持保存 config.json 
- Checkpoint.save 写入独立的 config.json（模型架构参数）
- Checkpoint.load 读取 config.json，恢复时覆盖 context.model_config
- TrainContext 新增 model_config 字段，builder 从 resume_dir/config.json 加载
- BaseConfig.to_dict 支持 tuple 和嵌套 dataclass（如 LoRAConfig）
- 删除 _get_meta/_get_config wrapper，直接使用 load_json
 2026-05-28 20:21:51 +08:00
ViperEkura 3a28e52e98 fix : start_epoch/start_batch 由用户参数决定，不再被 checkpoint 覆盖 2026-05-28 18:24:22 +08:00
ViperEkura e371908b54 fix : 保存 checkpoint 时 unwrap DDP/FSDP 避免 module. 前缀 
- 移除 state_dict_fn 参数
- _save_checkpoint 中先 unwrap_model 再 state_dict()
 2026-05-28 18:10:04 +08:00