fix : 修正类型标注与统一 CLI 参数命名

- AutoRegressiveLM.forward 返回类型标注 -> Dict[str, Tensor]
- EmbeddingEncoder 移除冗余 position_ids 自动创建
- CLI 脚本模型目录参数统一为 --param_path

astrai/model/encoder.py

@@ -68,9 +68,6 @@ class EmbeddingEncoder(AutoModel):
 
         x = self.embed_tokens(input_ids)
 
-        if position_ids is None:
-            position_ids = torch.arange(S, device=x.device).unsqueeze(0).expand(B, -1)
-
         rotary_emb = self.rotary_embedding(x, position_ids)
         attn_mask = process_attention_mask(x, position_ids, input_mask, is_causal=False)
 

astrai/model/transformer.py

@@ -1,4 +1,4 @@
-from typing import Any, Mapping, Optional
+from typing import Any, Dict, Mapping, Optional
 
 import torch
 import torch.nn as nn
@@ -136,7 +136,7 @@ class AutoRegressiveLM(AutoModel):
         input_mask: Optional[Tensor] = None,
         paged_cache: Optional[KvcacheView] = None,
         position_ids: Optional[Tensor] = None,
-    ) -> Tensor:
+    ) -> Dict[str, Tensor]:
         assert input_ids.ndim == 2
 
         x = self.embed_tokens(input_ids)

scripts/tools/evaluate_mmlu.py

@@ -197,7 +197,7 @@ def evaluate_subject(
 def main():
     parser = argparse.ArgumentParser(description="MMLU evaluation")
     parser.add_argument(
-        "--model_dir", type=str, default="./params", help="Model directory"
+        "--param_path", type=str, default="./params", help="Model directory"
     )
     parser.add_argument(
         "--data_dir", type=str, default="./mmlu_data", help="MMLU data directory"
@@ -228,8 +228,8 @@ def main():
     if args.download or not os.path.exists(args.data_dir):
         download_mmlu(args.data_dir)
 
-    model = AutoModel.from_pretrained(args.model_dir)
-    tokenizer = AutoTokenizer.from_pretrained(args.model_dir)
+    model = AutoModel.from_pretrained(args.param_path)
+    tokenizer = AutoTokenizer.from_pretrained(args.param_path)
     device = args.device
     dtype = getattr(torch, args.dtype)
     model.to(device=device, dtype=dtype)

scripts/tools/perplexity.py

@@ -10,11 +10,11 @@ from astrai.tokenize import AutoTokenizer
 
 
 def process_file(
-    model_dir: str, input_file: str, output_file: str, batch_size: int, text_key: str
+    param_path: str, input_file: str, output_file: str, batch_size: int, text_key: str
 ):
     # Load model and tokenizer
-    model = AutoModel.from_pretrained(model_dir)
-    tokenizer = AutoTokenizer.from_pretrained(model_dir)
+    model = AutoModel.from_pretrained(param_path)
+    tokenizer = AutoTokenizer.from_pretrained(param_path)
     model.to(device="cuda", dtype=torch.bfloat16)
 
     with open(input_file, "r", encoding="utf-8") as f:
@@ -88,7 +88,7 @@ def process_file(
 if __name__ == "__main__":
     parser = argparse.ArgumentParser(description="Run perplexity with a Khaosz model.")
     parser.add_argument(
-        "--model_dir", type=str, required=True, help="Path to the model directory."
+        "--param_path", type=str, required=True, help="Path to the model directory."
     )
     parser.add_argument(
         "--input_file", type=str, required=True, help="Path to the input file."

scripts/tools/server.py

@@ -18,7 +18,7 @@ def main():
         "--reload", action="store_true", help="Enable auto-reload for development"
     )
     parser.add_argument(
-        "--param-path",
+        "--param_path",
         type=Path,
         default=None,
         help="Path to model parameters (default: project_root/params)",