o iO @sdddlmZddlmZmZddlmZddZddZdd Z d d Z d d Z ddZ ddZ dS))Refine)unifyVar) TensorTypecCs*t|}|t|j}t|j|dS)z- Calls our symbolic inferencer once. N)rrefineunify_eq constraintssubstitute_all_typesgraphtracedrmgurd/home/ubuntu/veenaModal/venv/lib/python3.10/site-packages/torch/fx/experimental/unify_refinements.py infer_symbolic_types_single_passs rcCsXt|}|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 braodcasting. N)rrrrr r symbolic_relationsr rrrinfer_symbolic_typess     rcCs:g}g}|D]}||j||jqt|t|fS)za Convert equality constraints in the right format to be used by unification library. )appendlhsrhstuple) list_of_eqrreqrrr convert_eq%s  rcCst|\}}t||S)z@ Apply unification to a set of equality constraints )rr)rrrrrrr2s  rcCst|tr||vr||S|St|tr7g}|jD]}||vr+|||q||qtt|St|trMg}|D] }|t||q@|St|treg}|D] }|t||qVt|S|S)z2 Apply the most general unifier to a type ) isinstancerkeysr__args__rrlistsubstitute_solution_one_type)mappingtnew_typetyprrrr;s,         rcCstd}|r+d}|D] }||}|||vr ||}||||<|||kr(d}q|s|jD] }t||j|_q.dS)z 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)rnodesrtype)r r flagkold_mapping_valnew_keynrrrr ^s   r cCs.t|j|jD] \}}|j|jkrdSqdS)zv A check equality to be used in fixed points. We do not use graph equality but instead type equality. FT)zipr$r%)g1g2r*mrrrcheck_for_type_equalityss  r/N)/torch.fx.experimental.graph_gradual_typecheckerr!torch.fx.experimental.unificationrrtorch.fx.tensor_typerrrrrrr r/rrrrs     #