fix(dataset): 修复分片数据集时未正确计算样本数的问题

src/model/preprocessed_dataset.py

@@ -81,12 +81,17 @@ class PreProcessedDataset(Dataset):
         with open(self.data_dir / "metadata.json", "r", encoding="utf-8") as f:
             self.metadata = json.load(f)
 
-        self.num_samples = self.metadata["num_samples"]
         self.max_seq_length = self.metadata["max_seq_length"]
         self._shard_size: Optional[int] = self.metadata.get("shard_size")
-        self._num_shards: Optional[int] = self.metadata.get("num_shards")
 
-        if self._shard_size is not None and self._num_shards is not None:
+        if self._shard_size is not None:
+            shard_files = sorted(self.data_dir.glob("shard_*.npz"))
+            self._num_shards = len(shard_files)
+            if self._num_shards == 0:
+                raise FileNotFoundError(
+                    f"No shard_*.npz files found in {self.data_dir}"
+                )
+            self.num_samples = self._num_shards * self._shard_size
             self._is_sharded = True
             self._cache = _ShardCache(max_size=max_cache_shards)
             logger.info(
@@ -94,6 +99,7 @@ class PreProcessedDataset(Dataset):
                 f"{self._num_shards} shards, shard_size={self._shard_size:,}"
             )
         else:
+            self.num_samples = self.metadata["num_samples"]
             self._is_sharded = False
             self._load_single_files()
             logger.info(