+ j ^RIt^RIHt^RIHt^RIHt^RItRP4t !RR]PP4t RR lt R R lt]P!4t]R R l4tRRltR#)N) Generator)contextmanager)Anya This is used when dynamo traces torch.nn.Parameter, which normally would not trace properly with AOTAutograd. We instead create a placeholder torch.nn.Parameter before the graph, which becomes a graph arg and has no storage backing it. At the point in the graph where the parameter actually should be created we mutate this sacrificial placeholder into it. This allows gradients to flow into the parameter as if it were an input to the graph (which is the only thing we are allowed to compute gradients on). cXa]tRt^to]V3RlRl4t]V3RlRl4tRtVtR#)TracableCreateParametercZ<V^8dQhRS[RS[RS[RS[PP/#)ctxtensor placeholderreturn)rtorchnn Parameter)format __classdict__s"b/home/luca/screen-checking/.venv/lib/python3.14/site-packages/torch/_dynamo/create_parameter_op.py __annotate__$TracableCreateParameter.__annotate__s3((S(#(C(EHHAc$V^8dQhR\/#)r r )r9)rs"rrrEs==4=rc$\\RR4#)rBT)rCrDr#rr!can_convert_to_tracable_parameterrIEs 45t <rSsn%%  EG enn55  33=r