U qhD@slddlmZddlZddlmZddZGdddeZGdd d eZGd d d eZ Gd d d eZ dS)) annotationsN)OpRunc Cst|tjr.|jdkr&td|d|d}t|}t|jdkr|dkrt|jddddf}|dkrtj |||dd}|ddd|f}||t |||ff}nFtj | ||dd}|ddd|f}||t |||f f}|||f}||fStj ||d}tj ||d}|rPtj ||d}tj ||d}t|}tj |||d} tj |||d} | | fS) zSee function `_kneighbors_reduce_func `_. zk must be an integer not .rN)axisZkthr) isinstancenpZndarraysize RuntimeErrorintlenshapeZarangeZ argpartitionZargsortsortZflipZtake) XkrlargestZ sample_rangeZsorted_indicesZsorted_distancesZ sorted_valuesZarkZtopk_sorted_indicesZtopk_sorted_valuesr>/tmp/pip-unpacked-wheel-xnis5xre/onnx/reference/ops/op_topk.pytopk_sorted_implementation s:    rc@seZdZdddZdS) _CommonTopKrcCsD|d}|dkr|n |t|j}t||||\}}||tjfS)Runtime for operator *TopK*. The implementation is not the most efficient as it sorts everything then extracts the top *k* values. .. warning:: ONNX specifications may be imprecise in case of negative value for axis. The implementation follows what `onnxruntime` does in `top_k.cc `_. r)rrrZastyper Zint64)selfdatainkrrrrZsortirrr _common_run5s z_CommonTopK._common_runN)r)__name__ __module__ __qualname__rrrrrr4src@seZdZdddZdS)TopK_1NcCstj|||g|dSrrrr)rrrrrrr_runHs z TopK_1._run)NNrrrr#rrrrr Gsr c@seZdZdddZdS)TopK_10NcCstj||||dSr!r")rrrrrrrr#Xs z TopK_10._run)Nr$rrrrr%Wsr%c@seZdZdddZdS)TopK_11NcCs$|dkrtdtj|||||dS)aRuntime for operator *TopK*. The implementation is not the most efficient as it sorts everything then extracts the top *k* values. .. warning:: ONNX specifications may be imprecise in case of negative value for axis. The implementation follows what `onnxruntime` does in `top_k.cc `_. )Trz.TopK does not implement anything for sorted=0.)rr)r rr)rrrrrsortedrrrr#hsz TopK_11._run)NNNr$rrrrr&gsr&) __future__rZnumpyr Zonnx.reference.op_runrrrr r%r&rrrrs  )