o e«Ïi: ã@sdddlmZddlmZmZddlmZdd„Zdd„Zdd „Z d d „Z d d „Z dd„Z dd„Z dS)é)ÚRefine)ÚunifyÚVar)Ú TensorTypecCs*t|ƒ}| ¡t|jƒ}t|j|ƒdS)z- Calls our symbolic inferencer once. N)rÚrefineÚunify_eqÚ constraintsÚsubstitute_all_typesÚgraph©ÚtracedÚrÚmgu©rúq/var/www/addictedbytheproject.nl/epg/venv/lib/python3.10/site-packages/torch/fx/experimental/unify_refinements.pyÚ infer_symbolic_types_single_passs rcCsXt|ƒ}| ¡t|jƒ}t|j|ƒt|ƒ}| ¡t|jƒ}t|j|ƒ| ¡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 r Úsymbolic_relationsr rrrÚinfer_symbolic_typess     rcCs:g}g}|D]}| |j¡| |j¡qt|ƒt|ƒfS)za Convert equality constraints in the right format to be used by unification library. )ÚappendÚlhsÚrhsÚtuple)Ú list_of_eqrrÚeqrrrÚ convert_eq%s  rcCst|ƒ\}}t||ƒS)z@ Apply unification to a set of equality constraints )rr)rrrrrrr2s  rcCsÆt|tƒr||vr ||S|St|tƒr3g}|jD]}||vr'| ||¡q| |¡qtt|ƒƒSt|tƒrIg}|D] }| t||ƒ¡q<|St|tƒrag}|D] }| t||ƒ¡qRt|ƒS|S)z2 Apply the most general unifier to a type )Ú isinstancerrÚ__args__rrÚlistÚsubstitute_solution_one_type)ÚmappingÚtÚnew_typeÚtyprrrr;s,       rcCspd}|r)d}|D]}||}|||vr||}||||<|||kr&d}q|s|jD] }t||jƒ|_q,dS)zž Apply the most general unifier to all types in a graph till reaching a fixed point. If the input and output graph are the same, we converge. TFN)ÚnodesrÚtype)r rÚflagÚkÚold_mapping_valÚnew_keyÚnrrrr ^s   €ø ÿr cCs.t|j|jƒD] \}}|j|jkrdSqdS)zv A check equality to be used in fixed points. We do not use graph equality but instead type equality. FT)Úzipr#r$)Úg1Úg2r)ÚmrrrÚcheck_for_type_equalityss  ÿr.N)Ú/torch.fx.experimental.graph_gradual_typecheckerrÚ!torch.fx.experimental.unificationrrÚtorch.fx.tensor_typerrrrrrr r.rrrrÚs     #