init

tensordict/persistent.py

@@ -124,9 +124,7 @@ class PersistentTensorDict(TensorDictBase):
 
     """
 
-    def __new__(cls, *args, **kwargs):
-        cls._td_dim_names = None
-        return super().__new__(cls, *args, **kwargs)
+    _td_dim_names = None
 
     def __init__(
         self,

tensordict/tensordict.py

@@ -354,17 +354,14 @@ class TensorDictBase(MutableMapping):
     )
     KEY_ERROR = 'key "{}" not found in {} with ' "keys {}"
 
-    def __new__(cls, *args: Any, **kwargs: Any) -> T:
-        self = super().__new__(cls)
-        self._safe = kwargs.get("_safe", False)
-        self._lazy = kwargs.get("_lazy", False)
-        self._inplace_set = kwargs.get("_inplace_set", False)
-        self.is_meta = kwargs.get("is_meta", False)
-        self._is_locked = kwargs.get("_is_locked", False)
-        self._cache = None
-        self._last_op = None
-        self.__last_op_queue = None
-        return self
+    _safe = False
+    _lazy = False
+    _inplace_set = False
+    is_meta = False
+    _is_locked = False
+    _cache = None
+    _last_op = None
+    __last_op_queue = None
 
     def __getstate__(self) -> dict[str, Any]:
         state = self.__dict__.copy()
@@ -4077,26 +4074,11 @@ class TensorDict(TensorDictBase):
 
     """
 
-    __slots__ = (
-        "_tensordict",
-        "_batch_size",
-        "_is_shared",
-        "_is_memmap",
-        "_device",
-        "_is_locked",
-        "_td_dim_names",
-        "_lock_id",
-        "_locked_tensordicts",
-        "_cache",
-        "_last_op",
-        "__last_op_queue",
-    )
-
-    def __new__(cls, *args: Any, **kwargs: Any) -> TensorDict:
-        cls._is_shared = False
-        cls._is_memmap = False
-        cls._td_dim_names = None
-        return super().__new__(cls, *args, _safe=True, _lazy=False, **kwargs)
+    _is_shared = False
+    _is_memmap = False
+    _td_dim_names = None
+    _safe = True
+    _lazy = False
 
     def __init__(
         self,
@@ -5001,11 +4983,12 @@ def _nested_keys(
         )
 
     def __getstate__(self):
-        return {
-            slot: getattr(self, slot)
-            for slot in self.__slots__
-            if slot not in ("_last_op", "_cache", "__last_op_queue")
+        result = {
+            key: val
+            for key, val in self.__dict__.items()
+            if key not in ("_last_op", "_cache", "__last_op_queue")
         }
+        return result
 
     def __setstate__(self, state):
         for slot, value in state.items():
@@ -5790,10 +5773,11 @@ class SubTensorDict(TensorDictBase):
 
     """
 
-    def __new__(cls, *args: Any, **kwargs: Any) -> SubTensorDict:
-        cls._is_shared = False
-        cls._is_memmap = False
-        return super().__new__(cls, _safe=False, _lazy=True, _inplace_set=True)
+    _is_shared = False
+    _is_memmap = False
+    _safe = False
+    _lazy = True
+    _inplace_set = True
 
     def __init__(
         self,
@@ -6414,9 +6398,9 @@ def __torch_function__(
         else:
             return super().__torch_function__(func, types, args, kwargs)
 
-    def __new__(cls, *args: Any, **kwargs: Any) -> LazyStackedTensorDict:
-        cls._td_dim_name = None
-        return super().__new__(cls, *args, _safe=False, _lazy=True, **kwargs)
+    _td_dim_name = None
+    _safe = False
+    _lazy = True
 
     def __init__(
         self,
@@ -8162,8 +8146,8 @@ def _repr_exclusive_fields(self):
 class _CustomOpTensorDict(TensorDictBase):
     """Encodes lazy operations on tensors contained in a TensorDict."""
 
-    def __new__(cls, *args: Any, **kwargs: Any) -> _CustomOpTensorDict:
-        return super().__new__(cls, *args, _safe=False, _lazy=True, **kwargs)
+    _safe = False
+    _lazy = True
 
     def __init__(
         self,