amend

tensordict/_td.py

@@ -182,6 +182,8 @@ class TensorDict(TensorDictBase):
     """
 
     _td_dim_names = None
+    _is_shared = False
+    _is_memmap = False
 
     def __init__(
         self,
@@ -190,11 +192,7 @@ def __init__(
         device: DeviceType | None = None,
         names: Sequence[str] | None = None,
         _run_checks: bool = True,
-        _is_shared: bool | None = False,
-        _is_memmap: bool | None = False,
     ) -> None:
-        self._is_shared = _is_shared
-        self._is_memmap = _is_memmap
         if device is not None and isinstance(device, (int, str)):
             device = torch.device(device)
         self._device = device
@@ -210,8 +208,6 @@ def __init__(
                             batch_size=self._batch_size,
                             device=self._device,
                             _run_checks=_run_checks,
-                            _is_shared=_is_shared,
-                            _is_memmap=_is_memmap,
                         )
                     _tensordict[key] = value
             self._td_dim_names = names
@@ -1771,13 +1767,13 @@ def is_contiguous(self) -> bool:
         return all([value.is_contiguous() for _, value in self.items()])
 
     def clone(self, recurse: bool = True) -> T:
-        if recurse:
-            def func(x):
-                return x.clone()
-        else:
-            def func(x):
-                return x
-        return self._fast_apply(func, call_on_nested=False)
+        return TensorDict(
+            source={key: _clone_value(value, recurse) for key, value in self.items()},
+            batch_size=self.batch_size,
+            device=self.device,
+            names=copy(self._td_dim_names),
+            _run_checks=False,
+        )
 
     def contiguous(self) -> T:
         if not self.is_contiguous():
@@ -1792,8 +1788,6 @@ def empty(self, recurse=False) -> T:
                 source={},
                 names=self._td_dim_names,
                 _run_checks=False,
-                _is_memmap=False,
-                _is_shared=False,
             )
         return super().empty(recurse=recurse)
 
@@ -1834,8 +1828,6 @@ def select(self, *keys: NestedKey, inplace: bool = False, strict: bool = True) -
             # names=self.names if self._has_names() else None,
             names=self._td_dim_names,
             _run_checks=False,
-            _is_memmap=self._is_memmap,
-            _is_shared=self._is_shared,
         )
         if inplace:
             self._tensordict = out._tensordict