init

torchrl/envs/transforms/transforms.py

@@ -3667,13 +3667,18 @@ class CatTensors(Transform):
             the transform is used. This behaviour will only work if a parent is set.
         out_key (NestedKey): key of the resulting tensor.
         dim (int, optional): dimension along which the concatenation will occur.
-            Default is -1.
+            Default is ``-1``.
+
+    Keyword Args:
         del_keys (bool, optional): if ``True``, the input values will be deleted after
-            concatenation. Default is True.
+            concatenation. Default is ``True``.
         unsqueeze_if_oor (bool, optional): if ``True``, CatTensor will check that
             the dimension indicated exist for the tensors to concatenate. If not,
             the tensors will be unsqueezed along that dimension.
             Default is ``False``.
+        sort (bool, optional): if ``True``, the keys will be sorted in the
+            transform. Otherwise, the order provided by the user will prevail.
+            Defaults to ``True``.
 
     Examples:
         >>> transform = CatTensors(in_keys=["key1", "key2"])
@@ -3698,16 +3703,18 @@ def __init__(
         in_keys: Sequence[NestedKey] | None = None,
         out_key: NestedKey = "observation_vector",
         dim: int = -1,
+        *,
         del_keys: bool = True,
         unsqueeze_if_oor: bool = False,
+        sort: bool = True,
     ):
         self._initialized = in_keys is not None
         if not self._initialized:
             if dim != -1:
                 raise ValueError(
                     "Lazy call to CatTensors is only supported when `dim=-1`."
                 )
-        else:
+        elif sort:
             in_keys = sorted(in_keys, key=_sort_keys)
         if not isinstance(out_key, (str, tuple)):
             raise Exception("CatTensors requires out_key to be of type NestedKey")