fix a bug

internlm/train/training_internlm.py

@@ -33,7 +33,7 @@ from internlm.data.packed_dataset import (
     PackedDatasetWithoutCuSeqlen,
     get_packed_dataset_without_short_length,
 )
-from internlm.data.utils import DATASET_TYPE_IDS_MAP, unpack_data
+from internlm.data.utils import get_dataset_type_ids_map, unpack_data
 from internlm.model.embedding import Embedding1D
 from internlm.model.linear import (
     FeedForward,
@@ -133,7 +133,7 @@ def wrap_FSDP_model(model: Union[nn.Module, nn.ModuleList]):
 
         # wrap the model
         grp = gpc.get_group(ParallelMode.ZERO1)
-        model = FSDP(
+        model = FSDP(  # pylint: disable=unexpected-keyword-arg
             module=model,
             process_group=grp,
             sharding_strategy=ShardingStrategy.FULL_SHARD,
@@ -219,11 +219,11 @@ def get_train_data_loader(
 
     # Get the dataset types
     dataset_types = None
-    dataset_types = list(DATASET_TYPE_IDS_MAP.keys())
     data_cfg = gpc.config.data
 
     # Get the sample weight dictionary
     train_folder = data_cfg.train_folder
+    dataset_types = list(get_dataset_type_ids_map(train_folder).keys())
 
     if not train_folder:
         train_ds = RandomDataset(num_samples=1000000, max_len=data_cfg.seq_len)