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docs: fix stale docs and align with code

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- update cuda_kernels layout, arch flags, and add FP8 section
- fix install docs: kernels auto-build when nvcc + CUDA detected
- mark ignored OpenAI request params and complete KVCache fields
- add docker docs to indexes and astrai.optim to module overview
- refresh document update timestamps
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ViperEkura
2026-08-23 14:23:28 +08:00
parent 75304d084d
commit 10fec8dca1
10 changed files with 134 additions and 58 deletions
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docs/developer/architecture.md
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@@ -1437,7 +1437,8 @@ classDiagram
| **astrai.tokenize** | AutoTokenizer, ChatTemplate | Tokenizer and chat template |
| **astrai.trainer** | Trainer, TrainContext, TrainContextBuilder, BaseStrategy–GRPOStrategy, StrategyFactory, BaseScheduler–WSDScheduler, SchedulerFactory, TrainCallback(Protocol)–MetricCallback, CallbackFactory, RawRollout, RolloutResult, BaseRewardModel, RolloutGenerator, RolloutRunner | Training workflow |
| **astrai.inference** | InferenceEngine, InferenceScheduler, Executor, InferenceWorkspace, PagePool, KVStorage, ReqToTokenPool, KVCache, Allocator, RadixCache, Task, TaskManager, TaskStatus, StreamDecoder, GenerateResult, BaseSamplingStrategy–SamplingPipeline, FrequencyPenaltyStrategy, ProtocolHandler, ResponseBuilder, OpenAIResponseBuilder, AnthropicResponseBuilder, StopChecker, GenContext, StopInfo, ChatMessage, FunctionDef, ToolDef, ChatCompletionRequest, AnthropicMessage, MessagesRequest, BaseToolParser, ToolParserFactory, SimpleJsonToolParser | Inference service |
| **astrai.extension** | `backend` policy package, `ops` kernel-wrapper package, AttentionBackend, TorchNativeBackend, CudaBackend, FlashAttnBackend, attention, attn_backend, ATTN_BACKEND, apply_rotary_emb, is_available | Stable API over attention/rotary execution policy and optional CUDA kernels |
| **astrai.extension** | `backend` policy package, `ops` kernel-wrapper package, `fp8.py` FP8 strategy layer, AttentionBackend, TorchNativeBackend, CudaBackend, FlashAttnBackend, attention, attn_backend, ATTN_BACKEND, apply_rotary_emb, is_available | Stable API over attention/rotary/FP8 execution policy and optional CUDA kernels |
| **astrai.optim** | OptimizerFactory, MuonAdamW, NoraNadamW, ManoAdamW, composite_step/composite_zero_grad/composite_state_dict, partition_optimizer_parameters | Built-in optimizers (`muon_adamw` / `nora_nadamw` / `mano_adamw`) with shared composite-optimizer helpers |
| **astrai.parallel** | spawn_parallel_fn, setup_parallel, get_rank/get_world_size/get_current_device, only_on_rank, LaunchStrategy, TorchrunStrategy, LocalStrategy, BaseExecutor, ExecutorFactory, NoneExecutor, DDPExecutor, FSDPExecutor, GradientState, AccumOptimizer, AccumScheduler | Distributed parallel & gradient accumulation |
| **astrai.factory** | BaseFactory | Component registration |
| **astrai.protocols** | OptimizerProtocol, SchedulerProtocol | Structural subtyping for optimizer/scheduler wrappers |
@@ -1461,6 +1462,7 @@ classDiagram
| **Storage** | `Store`, `MmapStore`, `JsonlStore` | Format-agnostic data access with multi-segment support |
| **Producer-Consumer** | `InferenceScheduler`, `Task`, queues | Continuous batching |
| **Model Registry** | `ModelFactory`, `AutoRegressiveLM`, `EmbeddingEncoder` | Model-type dynamic loading |
| **Optimizer Routing** | `OptimizerFactory`, `MuonAdamW`, `NoraNadamW`, `ManoAdamW` | Route parameter groups (matrices vs. embeddings/heads/norms) through different optimizers |
## Core Relationships
@@ -1476,4 +1478,4 @@ classDiagram
10. **AutoModel**: `from_pretrained()` loads `config.json` + `model.safetensors`, `_disable_random_init` replaces `nn.init.*` with no-ops
11. **Protocols**: `OptimizerProtocol` / `SchedulerProtocol` — structural subtyping for `AccumOptimizer` / `AccumScheduler` wrappers
> Document Update Time: 2026-08-16
> Document Update Time: 2026-08-22