tjjddlmZddlZddlZddlmZddlmZddlm Z m Z ddl m Z gdZ dejjd dfd Zdejjd dfd Zd eed eeed feed fffdZd eed efdZdeeefded efdZdejjdeeefd dfdZdejjdejjd efdZdS))AnyN)Refine)Equality)unifyVar) TensorType)check_for_type_equality convert_eqinfer_symbolic_types infer_symbolic_types_single_passsubstitute_all_typessubstitute_solution_one_typeunify_eqtracedreturnct|}|t|j}t |j|dS)z- Calls our symbolic inferencer once. N)rrefiner constraintsr graphrrmgus e/var/www/html/CA-Chatbot/venv/lib/python3.11/site-packages/torch/fx/experimental/unify_refinements.pyr r sC vAHHJJJ 1= ! !Cs+++++c^t|}|t|j}t |j|t|}|t|j}t |j||dS)z Calls our symbolic inferencer twice. This is useful when one pass is not enough to infer all the information such as the case for broadcasting. N)rrrrr rsymbolic_relationsrs rr r s vAHHJJJ 1= ! !Cs+++vAHHJJJ 1= ! !Cs+++r list_of_eq.cg}g}|D]6}||j||j7t|t|fS)za Convert equality constraints in the right format to be used by unification library. )appendlhsrhstuple)rr r!eqs rr r 4s_ C C 26 26 ::uSzz !!rcFt|\}}t||S)z@ Apply unification to a set of equality constraints )r r)rr r!s rrrAs# *%%HC c??rmappingtcNt|tr||vr||S|St|tr]g}|jD]7}||vr|||"||8tt |St|t r,g}|D]%}|t||&|St|t r9g}|D]%}|t||&t |S|S)z2 Apply the most general unifier to a type ) isinstancerrdimsrr"listr)r%r&new_typetyps rrrJsI!S <<1: H Az " "6 % %Cg~~ ----$$$$%//*** At    H HC OO8#FF G G G G Au   H HC OO8#FF G G G GXrrcd}|r>??rg1g2clt|j|jD]\}}|j|jkrdSdS)zv A check equality to be used in fixed points. We do not use graph equality but instead type equality. FT)zipr.r/)r5r6r4ms rr r sE BHbh''1 6QV  55  4r)typingrtorchtorch.fx/torch.fx.experimental.graph_gradual_typecheckerr&torch.fx.experimental.refinement_typesr!torch.fx.experimental.unificationrrtorch.fx.tensor_typer__all__fx GraphModuler r r*r"r rdictobjectrGraphr boolr rrrIs BBBBBB;;;;;;88888888++++++   ,UX-A,d,,,,!5$( "4> "eE#s(OU3PS8_4T.U " " " "hC $vv~*> 6 c    F??ffn9M?RV????*  EHN t      r