fixes #5509

Signed-off-by: Wenqi Li <wenqil@nvidia.com>

Author: wyli

monai/data/meta_tensor.py

@@ -523,10 +523,11 @@ def ensure_torch_and_prune_meta(
             By default, a `MetaTensor` is returned.
             However, if `get_track_meta()` is `False`, a `torch.Tensor` is returned.
         """
-        img = convert_to_tensor(im)  # potentially ascontiguousarray
+        tracking_meta = get_track_meta() and meta is not None
+        img = convert_to_tensor(im, track_meta=tracking_meta)  # potentially ascontiguousarray
 
         # if not tracking metadata, return `torch.Tensor`
-        if not get_track_meta() or meta is None:
+        if not tracking_meta:
             return img
 
         # remove any superfluous metadata.
@@ -540,7 +541,7 @@ def ensure_torch_and_prune_meta(
             meta = monai.transforms.DeleteItemsd(keys=pattern, sep=sep, use_re=True)(meta)
 
         # return the `MetaTensor`
-        return MetaTensor(img, meta=meta)
+        return img.copy_meta_from(meta)
 
     def __repr__(self):
         """

monai/transforms/inverse.py

@@ -170,6 +170,8 @@ def track_transform_tensor(
 
         if not (get_track_meta() and transform_info and transform_info.get(TraceKeys.TRACING)):
             if isinstance(data, Mapping):
+                if not isinstance(data, dict):
+                    data = dict(data)
                 data[key] = data_t.copy_meta_from(out_obj) if isinstance(data_t, MetaTensor) else data_t
                 return data
             return out_obj  # return with data_t as tensor if get_track_meta() is False
@@ -202,15 +204,14 @@ def track_transform_tensor(
         else:
             out_obj.push_applied_operation(info)
         if isinstance(data, Mapping):
+            if not isinstance(data, dict):
+                data = dict(data)
             if isinstance(data_t, MetaTensor):
                 data[key] = data_t.copy_meta_from(out_obj)
             else:
-                # If this is the first, create list
                 x_k = TraceableTransform.trace_key(key)
                 if x_k not in data:
-                    if not isinstance(data, dict):
-                        data = dict(data)
-                    data[x_k] = []
+                    data[x_k] = []  # If this is the first, create list
                 data[x_k].append(info)
             return data
         return out_obj