[to #42322933] fix bug: run failed in tensor_utils.py

1. 修复default data collator的输入类型为tuple时运行会失败的问题
2. 修复default data collator的输入类型为dict时不兼容BatchEncoding的问题
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9403517

    * fix bug: 1. run failed when datatype is tuple 2. change type checking from dict to Mapping to fit transformers.datasets.BatchEncoding

modelscope/utils/tensor_utils.py

@@ -1,5 +1,6 @@
 # Copyright (c) Alibaba, Inc. and its affiliates.
 # Part of the implementation is borrowed from huggingface/transformers.
+from collections.abc import Mapping
 
 
 def torch_nested_numpify(tensors):
@@ -31,7 +32,7 @@ def torch_default_data_collator(features):
     #     features = [vars(f) for f in features]
     first = features[0]
 
-    if isinstance(first, dict):
+    if isinstance(first, Mapping):
         batch = {}
         # Special handling for labels.
         # Ensure that tensor is created with the correct type
@@ -65,9 +66,9 @@ def torch_default_data_collator(features):
         batch = []
         for idx in range(len(first)):
             if isinstance(first[idx], torch.Tensor):
-                batch.append(torch.stack([f[k] for f in features]))
+                batch.append(torch.stack([f[idx] for f in features]))
             else:
-                batch.append(torch.tensor([f[k] for f in features]))
+                batch.append(torch.tensor([f[idx] for f in features]))
     else:
         if isinstance(first, torch.Tensor):
             batch = torch.stack(features)