i0ddlZddlZejjddZej dejj eddejj edddejd ed ejfd Z d Z y) NexportFRAGMENTzLaccess_subclass_inner_tensor(Tensor src_subclass_tensor, str attr) -> Tensoraccess_subclass_inner_tensorAutogradPythonsrc_subclass_tensorattrreturncddlm}||sJt||d}|t|tj st d|d||S)Nr)is_traceable_wrapper_subclassz Attribute z% is not a tensor or doesn't exist in )torch.utils._python_dispatchr getattr isinstancetorchTensor RuntimeError)rr r vals Q/var/www/html/engine/venv/lib/python3.12/site-packages/torch/export/custom_ops.py_access_subclass_inner_tensorrs_K ()< == = %tT 2C {*S%,,7CDWCX Y   Jc|jdd\}}tj|}t||}t |dsJ|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. .apply)rsplit importlib import_modulerhasattrr)function_cls_nameargskwargs module_name class_namemodule function_clss r._call_custom_autograd_function_in_pre_dispatchr& sa066sA>K $ $[ 1F6:.L < )) ) <  t .v ..r) rrlibraryLibrarylibdefineimplrstrrr&rrr.s  mmHj1 R C7DC7B  -0  \\ CE /r