[CI] Bump tvm-ffi submodule to latest main

include/tvm/runtime/device_api.h

@@ -25,6 +25,7 @@
 #define TVM_RUNTIME_DEVICE_API_H_
 
 #include <tvm/ffi/any.h>
+#include <tvm/ffi/device.h>
 #include <tvm/ffi/error.h>
 #include <tvm/ffi/optional.h>
 #include <tvm/ffi/string.h>

include/tvm/script/printer/ir_docsifier.h

@@ -19,6 +19,7 @@
 #ifndef TVM_SCRIPT_PRINTER_IR_DOCSIFIER_H_
 #define TVM_SCRIPT_PRINTER_IR_DOCSIFIER_H_
 
+#include <tvm/ffi/device.h>
 #include <tvm/ffi/reflection/access_path.h>
 #include <tvm/ffi/reflection/registry.h>
 #include <tvm/ir/module.h>

python/tvm/ir/module.py

@@ -40,6 +40,12 @@ class IRModule(Node, Scriptable):
         Map of global var to BaseFunc
     """
 
+    # Opt into a per-instance ``__dict__``: ``IRModule`` stores the Python-only
+    # ``pyfuncs`` mapping. The base ``Object`` metaclass otherwise injects
+    # ``__slots__ = ()`` (required by the tvm-ffi lifetime model), which would
+    # forbid setting attributes.
+    __slots__ = ("__dict__",)
+
     def __init__(self, functions=None, attrs=None, global_infos=None):
         if functions is None:
             functions = {}

python/tvm/relax/expr.py

@@ -589,6 +589,12 @@ def __init__(self, blocks: list[BindingBlock], body: Expr, span: Span | None = N
 class Function(BaseFunc, Scriptable):
     """A Relax function."""
 
+    # Opt into a per-instance ``__dict__``: callers attach ``__name__`` to the
+    # function (e.g. DataflowBlockRewrite.mutated_root_fn). The base ``Object``
+    # metaclass otherwise injects ``__slots__ = ()`` (required by the tvm-ffi
+    # lifetime model), which would forbid setting attributes.
+    __slots__ = ("__dict__",)
+
     params: list[Var]
     body: Expr
     ret_ty: Type

python/tvm/runtime/_tensor.py

@@ -75,6 +75,12 @@ class Tensor(tvm_ffi.core.Tensor):
     how can we use TVM in existing project which might have their own array containers.
     """
 
+    # Keep the same instance layout as ``tvm_ffi.core.Tensor``: the FFI runtime
+    # registers ``ffi.Tensor`` to its base wrapper and rejects re-registration
+    # with a larger wrapper (a subclass without ``__slots__`` would add
+    # ``__dict__``/``__weakref__`` and grow ``__basicsize__``).
+    __slots__ = ()
+
     def __setitem__(self, in_slice, value):
         """Set ndarray value"""
         if (

python/tvm/runtime/script_printer.py

@@ -118,6 +118,12 @@ def _relax_script(obj: Object, config: PrinterConfig) -> str:
 class Scriptable:
     """A base class that enables the script() and show() method."""
 
+    # Empty slots so this mixin does not add ``__dict__``/``__weakref__`` to the
+    # FFI object subclasses that combine it with a slotted ``Object``/``Node``.
+    # The tvm-ffi lifetime model rejects registering a wrapper whose instance
+    # layout is larger than the base wrapper already registered for the type.
+    __slots__ = ()
+
     def script(
         self,
         *,

python/tvm/te/tensor.py

@@ -199,6 +199,12 @@ def astype(self, dtype, span=None):
 class TensorOpBase:
     """Operator overloads for whole TE Tensor values."""
 
+    # Empty slots so this mixin does not add ``__dict__``/``__weakref__`` to the
+    # FFI object subclasses that combine it with a slotted ``Object``/``Node``.
+    # The tvm-ffi lifetime model rejects registering a wrapper whose instance
+    # layout is larger than the base wrapper already registered for the type.
+    __slots__ = ()
+
     def __add__(self, other):
         return _te_tensor_overload.__add__(self, other)
 

python/tvm/tirx/expr.py

@@ -86,6 +86,12 @@ def _is_scalar_operand(value):
 class ExprOp:
     """Operator overloading for Expr like expressions."""
 
+    # Empty slots so this mixin does not add ``__dict__``/``__weakref__`` to the
+    # FFI object subclasses that combine it with a slotted ``Object``/``Expr``.
+    # The tvm-ffi lifetime model rejects registering a wrapper whose instance
+    # layout is larger than the base wrapper already registered for the type.
+    __slots__ = ()
+
     # TODO(tkonolige): use inspect to add source information to these objects
 
     def expr_ty(self) -> ir.PrimType:

python/tvm/tirx/function.py

@@ -60,6 +60,12 @@ class PrimFunc(BaseFunc, Scriptable):
         The location of this itervar in the source code.
     """
 
+    # Opt into a per-instance ``__dict__``: the TVMScript parser attaches
+    # ``__name__`` to the parsed function. The base ``Object`` metaclass
+    # otherwise injects ``__slots__ = ()`` (required by the tvm-ffi lifetime
+    # model), which would forbid setting attributes.
+    __slots__ = ("__dict__",)
+
     def __init__(self, params, body, ret_type=None, buffer_map=None, attrs=None, span=None):
         # Legacy compatibility: expand body-carrying leaf stmt wrappers
         # (e.g. DeclBuffer/AllocBuffer forms) into SeqStmt form.

python/tvm/tirx/stmt.py

@@ -342,6 +342,12 @@ class AllocBuffer(Stmt):
         The location of this AllocBuffer in the source code.
     """
 
+    # Opt into a per-instance ``__dict__``: the legacy ``body`` is carried on the
+    # Python side only. The base ``Object`` metaclass otherwise injects
+    # ``__slots__ = ()`` (required by the tvm-ffi lifetime model), which would
+    # forbid setting attributes.
+    __slots__ = ("__dict__",)
+
     buffer: Buffer
     span: Span | None
 
@@ -434,6 +440,12 @@ class DeclBuffer(Stmt):
         The location of this DeclBuffer in the source code.
     """
 
+    # Opt into a per-instance ``__dict__``: the legacy ``body`` is carried on the
+    # Python side only. The base ``Object`` metaclass otherwise injects
+    # ``__slots__ = ()`` (required by the tvm-ffi lifetime model), which would
+    # forbid setting attributes.
+    __slots__ = ("__dict__",)
+
     buffer: Buffer
     span: Span | None