refactor: 训练循环改为两重迭代并统一参数命名

- 训练循环从三重(epoch→batched→batch)改为二重(epoch→batch)
- batch_size → batch_per_device, accumulation_steps → grad_accum_steps
- scheduler 移入 step block 对齐 optimizer 更新步
- GradientClippingCallback 改用 on_step_begin 避免零梯度裁剪
- 移除 _train_impl 误导性的 -> Checkpoint 标注
- total_steps 修除为向下取整并精简为一行
- warmup_steps 改为 warmup_ratio (默认0.05)
This commit is contained in:
2026-05-16 21:27:35 +08:00
parent 7dea929788
commit d7a7f570ed
14 changed files with 210 additions and 237 deletions
+19 -20
View File
@@ -30,6 +30,9 @@ classDiagram
+int n_shared_experts
+int n_activated_experts
+str moe_topk_method
+Optional[int] kv_lora_rank
+Optional[int] qk_nope_head_dim
+Optional[int] qk_rope_head_dim
+load(config_path) ModelConfig
+save(config_path)
}
@@ -41,8 +44,8 @@ classDiagram
+Callable optimizer_fn
+Callable scheduler_fn
+int n_epoch
+int batch_size
+int accumulation_steps
+int batch_per_device
+int grad_accum_steps
+float max_grad_norm
+int start_epoch
+int start_batch
@@ -69,7 +72,7 @@ classDiagram
class BaseDataset {
+int window_size
+int stride
+BaseStorage storage
+Optional[BaseStorage] storage
+load(load_path, storage_type, tokenizer)
+__getitem__(index)
+__len__()
@@ -126,8 +129,8 @@ classDiagram
}
class ResumableDistributedSampler {
+int start_epoch
+int start_iter
+int epoch
+int iter
}
class DatasetFactory {
@@ -155,7 +158,7 @@ classDiagram
+Registry _registry
+register(model_type) decorator
+get_component_class(model_type) Type
+from_pretrained(path, disable_random_init) nn.Module
+from_pretrained(path, disable_random_init, strict) nn.Module
+save_pretrained(save_directory)
+to(*args, **kwargs) Self
}
@@ -167,7 +170,7 @@ classDiagram
+ModuleList layers
+RMSNorm norm
+Linear lm_head
+forward(input_ids, input_mask, paged_cache, position_ids) Dict
+forward(input_ids, input_mask, paged_cache, position_ids) Dict[str, Tensor]
+load_state_dict(state_dict)
+state_dict()
}
@@ -185,6 +188,7 @@ classDiagram
+int n_kv_heads
+int head_dim
+int n_rep
+int layer_id
+bool use_qk_norm
+bool use_gated_attention
+Linear q_proj, k_proj, v_proj, o_proj
@@ -201,6 +205,7 @@ classDiagram
+int qk_nope_head_dim
+int qk_rope_head_dim
+int n_rep
+int layer_id
+bool use_gated_attention
+Linear q_proj, kv_a_proj, kv_b_proj
+Linear o_proj
@@ -215,6 +220,7 @@ classDiagram
}
class DeepSeekMoE {
+int dim
+int n_routed_experts
+int n_shared_experts
+int n_activated_experts
@@ -236,6 +242,7 @@ classDiagram
class RMSNorm {
+Parameter weight
+float norm_eps
+tuple normalized_shape
+forward(x) Tensor
}
@@ -299,7 +306,6 @@ classDiagram
+TrainConfig train_config
+List[TrainCallback] callbacks
+train(checkpoint)
+_build_context(checkpoint) TrainContext
+_get_default_callbacks() List[TrainCallback]
}
@@ -324,7 +330,7 @@ classDiagram
}
class BaseStrategy {
+nn.Module model
+Union[Callable, nn.Module] model
+str device
+compute_loss(batch) Tensor
}
@@ -332,7 +338,7 @@ classDiagram
class StrategyFactory {
+Registry _registry
+register(name) decorator
+create(model, train_type, device, **kwargs) BaseStrategy
+create(train_type, model, device, **kwargs) BaseStrategy
}
class SEQStrategy {
@@ -400,7 +406,7 @@ classDiagram
class GradientClippingCallback {
+float max_grad_norm
+on_step_end(context)
+on_step_begin(context)
}
class CheckpointCallback {
@@ -459,10 +465,7 @@ classDiagram
+TaskManager _task_mgr
+bool _running
+Thread _loop_thread
+int max_batch_size
+int max_seq_len
+int max_prompt_len
+int page_size
+add_task(prompt, max_tokens, temperature, top_p, top_k, stream_callback) str
+remove_task(task_id)
+start()
@@ -500,10 +503,7 @@ classDiagram
}
class Storage {
+int n_layers
+int page_size
+int head_dim
+int n_kv_heads
+Tensor k_cache
+Tensor v_cache
+write(layer_id, page_table, start_pos, k, v)
@@ -675,7 +675,6 @@ classDiagram
}
class AnthropicHandler {
+List[str] stop_sequences
+build_prompt() str
+create_response_id() str
+on_token(ctx, token, stop_checker) Optional[str]
@@ -704,7 +703,7 @@ classDiagram
namespace parallel {
class Functions {
+spawn_parallel_fn(fn, nprocs)
+spawn_parallel_fn(func, world_size, backend, master_addr, master_port, device_type, **kwargs)
+setup_parallel(rank, world_size, backend, master_addr, master_port, device_type)
+get_current_device() str
+get_world_size() int
@@ -878,4 +877,4 @@ classDiagram
8. **Scheduler**: `SchedulerFactory` creates `CosineScheduler`/`SGDRScheduler`
9. **AutoModel**: `from_pretrained()` loads `config.json` + `model.safetensors`, `_disable_random_init` replaces `nn.init.*` with no-ops
> Document Update Time: 2026-05-15
> Document Update Time: 2026-05-16