ViperEkura ae9fd546ef perf: merge prefill warmup into _warmup_cuda_graphs ...

- 64-token prefill forward triggers cuBLAS auto-tuning at init
- reduces first-chat prefill from ~520ms to ~27ms
- warmup decode also drops from ~215ms to ~71ms

2026-08-08 13:10:58 +08:00

..

config

feat: add moe auxloss and metrics

2026-08-05 18:12:28 +08:00

dataset

refactor: break JsonlStore→preprocessing circular dependency

2026-08-07 23:22:32 +08:00

extension

fix: default backend race, raise on explicit fallback

2026-08-08 13:00:58 +08:00

inference

perf: merge prefill warmup into _warmup_cuda_graphs

2026-08-08 13:10:58 +08:00

model

refactor: stateless MoE routing with grouped dispatch

2026-08-05 18:42:12 +08:00

optim

fix: use torch.optim.AdamW in ManoAdamW instead of NAdamW

2026-08-01 09:20:54 +08:00

parallel

fix: broadcast ref/old model state_dict for FSDP

2026-07-31 08:32:22 +08:00

preprocessing

fix : correct prefill sampling and record alignment

2026-08-05 22:20:29 +08:00

serialization

refactor: remove H5 storage backend in favor of mmap bin

2026-07-29 12:50:27 +08:00

tokenize

refactor: simplify BaseFactory and separate ModelFactory from AutoModel

2026-07-30 09:38:20 +08:00

trainer

refactor: stateless MoE routing with grouped dispatch

2026-08-05 18:42:12 +08:00

__init__.py

refactor: centralize logging in astrai.logging, replace ASTRAI_TIMED with log level

2026-08-08 12:39:27 +08:00

factory.py

refactor: simplify BaseFactory and separate ModelFactory from AutoModel

2026-07-30 09:38:20 +08:00

logging.py

refactor: centralize logging in astrai.logging, replace ASTRAI_TIMED with log level

2026-08-08 12:39:27 +08:00

protocols.py

refactor: 重构训练后端为 Executor 模式

2026-05-24 20:35:44 +08:00

signal_handler.py

refactor: move signal_handler from parallel/ to top-level for broader reuse

2026-07-28 10:36:17 +08:00