o ei@snddlZddlZejddZedejeddejedddejd ed ejfd d Z d dZ dS)NexportFRAGMENTzLaccess_subclass_inner_tensor(Tensor src_subclass_tensor, str attr) -> Tensoraccess_subclass_inner_tensorAutogradPythonsrc_subclass_tensorattrreturncCs^ddlm}||stdt|t||d}|dus#t|tjs-td|d||S)Nr)is_traceable_wrapper_subclasszIExpected src_subclass_tensor to be a traceable wrapper subclass, but got z Attribute z% is not a tensor or doesn't exist in ) torch.utils._python_dispatchr AssertionErrortypegetattr isinstancetorchTensor RuntimeError)rrr valra/var/www/addictedbytheproject.nl/epg/venv/lib/python3.10/site-packages/torch/export/custom_ops.py_access_subclass_inner_tensors  rcOsN|dd\}}t|}t||}t|dstd|d|j|i|S)a] Import a custom autograd function by string name and call it. This is pretty bad because: 1) There is no schema Ideally we should automatically wrap custom autograd functions with a custom op, but that is too much work because we need to schematize custom autograd functions. For now, we just hackily put it in the IR. .applyzExpected function class z to have 'apply' method)rsplit importlib import_modulerhasattrr r)function_cls_nameargskwargs module_name class_namemodule function_clsrrr._call_custom_autograd_function_in_pre_dispatch$s    r%) rrlibraryLibrarylibdefineimplrstrrr%rrrrs