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SSS.S._SSSS0SS0S._SSSS0SS0S._SSSSSSSSS.SSSSS.S._SSSSS SSS!.SS"SS#.S._S$S%SSSS&S'S(S)S*SS+S,.
SS-S.S/S0S1SS2.S3S4S5.S3S6S5.S3S7S5.S8.S9._S:S;SSSS S<S)SS=.SS"S>SS.S._S?S@SSSS&S'S(S)S*SS+S,.
SS-S.S/S0S1SS2.S3S4S5.S3S6S5.S3S7S5.S8.S9._SASBSSCSD.SS0SESFSGSH.SI._SJSKSLS0SS0S._SMSMSS0SS0S._SNSNSOSSCSP.SS0SQSRSS.SI._STSTSSUSVSW.SS0S._SXSXSYSZ0S[S\0S]S^S_S5.0S`._SaSbSS0SS0ScSdSe.SI._SfSfSOSgSD.SS0ShSiS5.ShSjS5.Sk.S9._0 SlSmSS0SS0ScSdSe.SI._SnSoSS0SS0ScSdSe.SI._SpSpSYSO0SqSrSs.S._StStSS0SS0S._SuSvSS0SS0ScSdSe.SI._SwSxSySzS{S|.SS0S}S~S.S}S~S.S}S~S.S|.S9._SSSS0SS0SSS~S.0S9._SSSS0SS0SSS~S.0S9._SSSS0SSS.S._SSSS0SSS.S._SSSS0SS0S._SSSS0SS0S._SSSS0SS0S._SSSS0SS0S._SSSSS.S._SSSS0SS0S._SSSS0SS0S._E0 SSSS0S._SSSS0SS0S._SSSSSD.SS0S._SSSS0SS0S._SSSSSSSSSSSS.	SSSSSSS.S._SSSSSSSS.SSSS.S._SSSOSSCSP.SS0SQSRSS.SI._SSSS0SS0S._SSSOSSVS.SS0S._SSSSSSUSVS.SCSSSSSS.SS0SI._SSSSS.SS0S._SSSSS.SSS.S._SSSS0SS0S._SSSSSSUS.S[S0SS0SI._SSSSCSSVS.SS0S._SSSSSSUS.S[S0SS0SI._SSSSS.SS0SS^S~S.0S9._E0 SSSS0SSS.S._SSSSCSD.SS0S._SSSS0SS0S._SSSSCSD.SS0S._SSSSCSD.SS0S._SSSSCSD.SS0S._SSSS0S._SSSSSS.SS0S._SSSYS0SS0S._SSSS0SS0S._SSSSS.SS0S._SSSSS.SSGS .S._GSGSSS0SS0S._GSGSSS0SS0S._GSGSSS0SS0S._GSGSSS0SS0S._GSGSSSUGS.SGSGS	.S._E0 GS
GS
SS0SS0S._GSGSSSCSD.SS0S._GSGSGSS0GSGSGS.S._GSGSSS0SS0S3GSS5.S3GSS5.GS.S9._GSGSSS0SS0S._GSGSSYSO0S\GSGS.GSGS0SI._GSGSGSGSGSGS.GS GS!GS".GS#GS$0SI._GS%GS%SSCGS&.SS0S._GS'GS'SS0SS0SS0SS^GS(S5.0GS)._GS*GS+GS*0_GS,GS,SS0SS0S._GS-GS-SOGS.GS/.SS\0S._GS0GS0SOGS.SVGS1.SS\0GS2S^S~S.0S`._GS3GS3SOGS.SVGS1.SS\0GS2S^S~S.0S`._GS4GS4SOGS.GS/.SS\0S._GS5GS5SOGS.GS6.SS\0S._GS7GS7GS8GS9GS:.SS\0S._E0 GS;GS;SS0SS0S._GS<GS<SS0SS0S._GS=GS>SS0SS0S^GS?GS@GSA.S^GSBGSCGSA.GSD.S`._GSEGSESSCSD.SS0SSc0SI._GSFGSGSSS.SSGS .S._GSHGSHSS0SS0ScSc0SI._GSIGSISS0SS0SS^S~S.0S9._GSJGSJSGSKGSL.SSC0S._GSMGS+GSM0_GSNGSNSS0SS0S._GSOGSOSOGSPGS.GSQGSR.SS\0S._GSSGSSSOGS.GS/.SS\0GSTSGGSUGSVGSW.SI._GSXGSXSOGS.SVGS1.SS\0GS2S^S~S.0S`._GSYGSYSYSO0S[S\0SUGSZGS[.SI._GS\GS\SSUGS.SS0S._GS]GS]SSUGS^GS_GS`GSa.SCGSbGScGSdGSe.S._GSfGSfSGSgGSh.SS0S._E0 GSiGSjSSO0SS0S._GSkGSkSS0SS0S._GSlGSlSSGSmSSGSnGSoGSp.SGSqSGSrGSs.S._GStGSuSS0SS0S._GSvGSvSYSO0SS0S._GSwGSwSSO0SS0S._GSxGSxSS0SS0S._GSyGSyGSzSQ0SS0S._GS{GS{SSCSD.SS0S._GS|GS}SSCSD.SS0S._GS~GS~SSCSD.SS0S._GSGSSGSGS.SGSQGS.GSGSGSGSGSGS.GSGSS~00GS)._GSGS+GS0_GSGSGSGSGSGSGS.GSSGS.S._GSGSSS0GSGSGS.S._GSGSSS0GSGSGS.S._GSGSSS0SS0S._E0 GSGSSS0GSGSGS.GSGS0SI._GSGSSGS0SGSGSGS.S._GSGSSSCSD.SS0S._GSGSSS0SS0S._GSGSSSGS.SS0GSGS0SI._GSGSSS0GSSGS@GSGSA.0GS._GSGSSSCSD.SS0S._GSGSSSCSD.SS0S._GSGSSS0SS0S._GSGSSS0SS0S._GSGSSS0SS0S._GSGSSS0SS0GSGS0GSS^GS?GSGSA.0GS._GSGSSSCSD.SS0S._GSGSSS0SS0S._GSGSSS0SS0GSGS0SI._GSGSSS0GSS~0GSS~0GS.GS._GSGSSGSGS.SS0S._E0 GSGSSS0SGSbGS.S._GSGSSS0SGSbGS.S._GSGSSSUGS.SS0S._GSGSSS0SGSbGS.S._GSGSSS0SGSbGS.S._GSGSSGSGS_GS`GS.SGSbGSdGScGS.S._GSGSSGSGS_GS`GS.SGSbGSdGScGS.S._GSGSSGSGSGS.SGSbGSGS.S._GSGSGSGSGSGS.GSGSGS.S._GSGSSOSSVS.SS0GSTSGGSVGS.SI._GSGSSS0S._GSGSSS0SS0S._GSGSSS0SS0S._GSGSSS0SS0S._GSGSSS0SS0S._GSGSSS0SS0GSS3S~S.0S9._GSGSSS0SS0S._E0 GSGSSSCSD.SS0S._GSGSSS~S.SS~S.GS.GS._GSGSSS~S.SS~S.GS.GS._GSGSSS~S.SS~S.GS.GS._GSGSSS0SGSGS.GSGSGS.SI._GSGSSS0SS0S._GSGSSS0SS0S._GSGSSSCSD.SS0S._GSGSSSCSD.SS0S._GSGSSSCSD.SS0S._GSGSSS0SSC0S._GSGSSS0SS0S._GSGSSS0SS0ScSdSe.SS^S~S.0GS._GSGSSS0S._GS GSSS0SS0GSS3S~S.0S9._GSGSGSSS~S.0GS._GSGSGSGSSGSGS	GS
GSGSGSS+GS.
GSGSGSGSGSGSGSGS.S._E0 GSGSSGSGSGSGSGSGSGSGSGS GS!GS".0 GS#GS$_GS%GS&_GS'GS(_GS)GS*_GS+GS,_GS-GS._GS/GS0_GS1GS2_GS3GS4_GS5GS6_GS7GS8_GS9GS:_GS;GS<_GS=GS>_GS?GS@_GSAGSB_GSCGSD_GSEGSFSCGSG.ES._GSHGSHSSSSUSVS.SCSSSSSS.S._GSIGSISGSJSVGSGSGSK.GSEGS@GS$GS&SCGSL.S._GSMGSNSGSOSSSUSVGSP.SCSSSSSS.S._GSQGSQSOGS.SVGSRGSS.S[S\0GSTSGGSUGSVGSW.SI._GSTGSTSOGS.SVGSRGSU.S\GSVGSW.S._GSXGSXSOGS.SVGSRGSS.S[S\0GSTSGGSUGSVGSW.SI._GSYGSYSSCSD.SS0S._GSZGSZSSCSD.SS0S._GS[GS[SSCSD.SS0S._GS\GS\SSCSD.SS0S._GS]GS]SGS^SVSUGS_.SS0S._GS`GS`SGSaGSbSVSSGSc.SSGSdGSeGSfGSgGShGSiGSj.S._GSkGSkSSSCGSlSUGSmGSn.SSSGSo.S._GSpGSpSGSqGSrGSsGStGSuGSvGSwGSxGS GS!GSy.SGSzGS{GS|GS}GSBGSDGS~GSGSGSGS.GSGSGSGSGS.SI._GSGSGSGSGSGSGSGSGSGSGSGSGSGSGS.GSGSGSGSGS4GSGS<GSSGS.	S._GSGSSSCSVGS.SSGS.S._E0 GSGSSSCSGSGS.GSGSGSGS.S._GSGS0 SS_GSGS_GSGS_GSGS_GSGS_GSGS_GSGS_GSGS_GSGS_GSGS_GSGS_GSGS_GSGS_GSGS_GSGS_GSGS_GSGS_GSGSGSGS.EGSFSGS.S._GSGSSGSKGSL.SS0S._GSGSSS0SS0S._GSGSSSGSGSbSVGS.GShGSdGSeGSSGS.GSGSGSVGS.SI._GSGSSSGSGSbSVSGS.SSSGSdGSeGSfGSgGShGSiGSGS.
GSGSGSVGS.SI._GSGSSSSVGS.GSSGS.S._GSGSSGS.SVGS1.SGSGS.GSGSGSGS.SI._GSGSSS0SS0S._GSGSSS0SS0S._GSGSSGSGS.SS0SS^GSS5.0S9._GSGSSGSGS.SS0S._GSGSSGSGS.SS0S._GSGSSS0GSSGS@GSGSA.0GS._GSGSSS0SS0S._GSGSSGSGSSqSrGS.GSGSGSGS.GSGS$GS.SI._GSGSSS0SS0S._E0 GSGSSS0SS0S._GSGSSSCSD.SS0S._GSGSGSGSSGSGS.GSGSGSGSGS GS.S._GSGSGSGSSGSGSGS.SGSGS GS.S._GSGSSSCSD.SS0S._GSGSSSCSD.SS0S._GS	GS
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GSGSGS._GSGSGSGS._GS1GSGSGS._E0 GS7GSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GS!GSGSGS._GS$GSGSGS._GS+GSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GS=GSGSGS._GS-GSGSGS._GS.GSGSGS._E0 GS/GSGSGS._GS0GSGSGS._GS3GSGSGS._GS>GSGSGS._GS?GSGSGS._GSGSGSGS._GS@GSGSGS._GSAGSGSGS._GSGSGSGS._GSBGSGSGS._GSGSGSGS._GSDGSGSGS._GSEGSGSGS._GSFGSGSGS._GSHGSGSGS._GSJGSGSGS._GSLGSGSGS._E0 GSMGSGSGS._GSPGSGSGS._GSQGSGSGS._GSRGSGSGS._GSSGSGSGS._GSWGSGSGS._GSZGSGSGS._GS[GSGSGS._GSrGSGSGS._GSvGSGSGS._GSBGSGSGS._GSxGSGSGS._GSyGSGSGS._GSGSGSGS._GS~GSGSGS._GSGSGSGS._GSGSGSGS._E0 GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSDGSGSGS._GSGSGSGS._GSGGSGSGS._GS GSGSGS._GSHGSGSGS._GSGSGSGS._GSLGSGSGS._E0 GSGS	GSGS._GSGS
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GSeGSGS._GSGSfGSGS._GSGSgGSGS._GSGShGSGS._GSGSiGSGS._GSGSiGSGS._GSGSjGSGS._E0 GSGSkGSGS._GSGSGSGS._GSlGSGSGS._GSGSmGSGS._GSGSnGSGS._GSGSoGSGS._GSGSpGSGS._GS#GSqGSrGS._GS(GSsGSGS._GSbGStGSuGS._GS)GSvGSGS._GS,GSwGSGS._GShGSxGSyGS._GS4GSzGS{GS._GS|GS}GS~GS._GS;GSGSGS._GSGSGSGS._E0 GSoGSGSGS._GS<GSGSGS._GStGSGSGS._GSGSGSGS._GS>GSGSGS._GS?GSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GS@GSGSGS._GSAGSGSGS._GSDGSGSGS._GSEGSGSGS._GSHGSGSGS._GSpGSGSGS._GSGSGSGS._E0 GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._E0 GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGS5GS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._E0 GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GS GSGSGS._GS"GSGSGS._GS#GSGSGS._E0 GSGSGSGS._GS%GSGSGS._GS'GSGSGS._GSGSGSGS._GS(GSGSGS._GSGSGSGS._GS*GSGSGS._SJGSGSGS._GS3GSGSGS._GSGSGSGS._GSGSGSGS._GS7GSGSGS._GSGSGSGS._GSGSGSGS._GS:GSGSGS._GS<GSGSGS._GS=GSGSGS._E0 GS>GSGSGS._GS?GSGSGS._GSGGSGSGS._GSGSGSGS._GSLGSGSGS._GSGSGSGS._GSRGSGSGS._GSWGSZGSGS._GSGSGSGS._GSYGSGSGS._GS[GSGSGS._GSGSGSGS._GSGSGSGS._GS^GSGSGS._GSGSGSGS._GSGSGSGS._GS_GSGSGS._E0 GSGSGSGS._GS`GSGSGS._GSaGSGSGS._GSbGSGSGS._GSdGSGSGS._GSgGSGSGS._GSGSGSGS._GSkGSGSGS._GSmGSGSGS._GSpGSGSGS._GSrGSGSGS._GSuGSGSGS._GSwGSGSGS._G	S GSGSGS._G	SG	SGSGS._GSG	SGSGS._G	SG	SGSGS._E0 GSG	SG	SGS._GSG	SG	S	GS._G	S
G	SG	SGS._G	SG	SGSGS._G	SG	SGSGS._G	SG	SG	SGS._G	SG	SG	SGS._GSG	SGSGS._GSG	SG	SGS._GSG	SGSGS._GSG	SG	SGS._GSG	SG	SGS._G	SGSoGSGS._G	S G	S!GSGS._G	S"G	S#GSGS._GSG	S$G	S%GS._G	S&G	S'G	S(GS._E0 G	S)G	S*G	S+GS._G	S,G	S-G	S.GS._G	S/G	S0G	S1GS._G	S2G	S*G	S+GS._G	S3G	S4GSGS._GS_G	S5GSGS._SBGSGSGS._SKGS.GSGS._SxG	S6GSGS._SGSGSGS._SGSGSGS._SG	S7GSGS._GSG	S8G	S9GS._GS}GSGSGS._GSG	S:G	S;GS._GSGSGSGS._GSG	S<GSGS._E0 G	S=G	S>G	S?GS._GSGSGSGS._GSGSGSGS._GSG	S@G	SAGS._GSG	SBG	SCGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GStGSGSGS._GSuGSGSGS._GSeG	SDGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GSGSGSGS._GS=G	S6GSGS._EGSGSGS.G	SEGSGS.G	SFGSGS.GSGSGS.G	SGG	SHGS.G	SIGSGS.G	SJGSGS.G	SKG	SLGS.G	SM.ErG	gN(O	  absxXoutOut)phi_nameinputsoutputsaccuracyIndicesLabel)r   indiceslabelAccuracyCorrectTotal)r
   correcttotalacosacoshadadelta	adadelta_ParamGradAvgSquaredGradAvgSquaredUpdateLearningRateMasterParam)paramgradavg_squared_gradavg_squared_updatelearning_ratemaster_paramParamOutAvgSquaredGradOutAvgSquaredUpdateOutMasterParamOut)	param_out
moment_outinf_norm_outmaster_param_outadagradadagrad_Moment)r   r   momentr"   r#   	MomentOut)r(   r)   r+   adamadam_Moment1Moment2
Moment2MaxBeta1PowBeta2Pow
SkipUpdate)
r   r   r"   moment1moment2moment2_max	beta1_pow	beta2_powr#   skip_update
Moment1Out
Moment2OutMoment2MaxOutBeta1PowOutBeta2PowOut)r(   moment1_outmoment2_outmoment2_max_outbeta1_pow_outbeta2_pow_outr+   floatBeta1Tensor)	data_typetensor_nameBeta2TensorEpsilonTensor)beta1beta2epsilon)r   r   r	   scalaradamaxadamax_InfNorm)r   r   r"   r/   inf_normr<   r#   
InfNormOutadamwadamw_elementwise_addaddY)r   yScale_xScale_y	Scale_out)scale_xscale_y	scale_out)r   r   r	   attrssumadd_nr   add_position_encodingaddmmInput)inputr   r]   AlphaBeta)alphabetaaffine_channelScaleBias)r   scalebiasaffine_gridrj   ThetaoutputOutputoutput_shapeintOutputShape)r   r   r	   	int_array
reduce_allalldimkeep_dim)axiskeepdimallcloseOtherzstd::stringRtolAtol)rtolatolreduce_amaxamaxreduce_aminaminanchor_generatorAnchors	Variances)anchorsvariances_outangle
reduce_anyanyrangearangeStartEndStep)startendstepdoubleTrue)rK   support_tensorarg_maxargmaxr   int64_targ_minargminargsort)r   r   tensor_array_to_tensorarray_to_tensorOutIndex)r   	out_index
as_complexas_realasinasinhassertCondData)conddata)r   r   assign
assign_posassign_value)r   r	   atanatan2X1X2atanhattention_lstmC0H0AttentionWeightAttentionBiasAttentionScalarAttentionScalarBias
LSTMWeightLSTMBias)	r   c0h0attention_weightattention_biasattention_scalarattention_scalar_biaslstm_weight	lstm_biasHiddenCellAttentionedXAttentionFCOutLSTMXLSTMOUT)hiddencellattentioned_xattention_fc_outlstm_xlstm_outaucPredictStatPosStatNegInsTagWeight)r   r   stat_posstat_negins_tag_weightAUC
StatPosOut
StatNegOut)r   stat_pos_outstat_neg_outbaddbmmbarrierbatch_fcW)rj   wrs   
batch_normMeanVariance)r   meanvariancerr   rs   MeanOutVarianceOut	SavedMeanSavedVarianceReserveSpace)r   mean_outvariance_out
saved_meansaved_variancereserve_spacedata_formatdata_layoutbce_loss)rj   r   beam_search_decodeIdsScores)idsscoresSentenceIdsSentenceScores)sentence_idssentence_scores	bernoullibicubic_interp_v2bicubic_interpOutSize
SizeTensor)r   out_sizesize_tensorscale_tensorbilinear_tensor_productbilinearWeight)r   r]   weightrs   bilinear_interp_v2bilinear_interpbincountWeights)r   weights	minlengthbipartite_matchdist_matDistMatColToRowMatchIndicesColToRowMatchDist)col_to_row_match_indicescol_to_row_match_distbitwise_andbitwise_not
bitwise_orbitwise_xorbmm
bn_act_xpu)r   rd   	box_coderPriorBoxPriorBoxVar	TargetBox)	prior_boxprior_box_var
target_box
output_box	OutputBoxbroadcast_tensorsc_concatc_embedding)r  r   c_softmax_with_cross_entropyLogits)logitsr   SoftmaxLoss)softmaxlossc_splitcastceilcelucheck_finite_and_unscalecheck_finite_and_unscale_)r   rr   FoundInfinite)r   found_infinitecholeskycholesky_solveclass_center_sampler   RemappedLabelSampledLocalClassCenter)remapped_labelsampled_local_class_centerclipMinMax)minmaxclip_by_normcoalesce_tensorFusedOutput)rv   fused_outputsize_of_dtypeuser_defined_size_of_dtypecollect_fpn_proposalsMultiLevelRoisMultiLevelScoresMultiLevelRoIsNum)multi_level_roismulti_level_scoresmulti_level_rois_numFpnRoisRoisNum)fpn_roisrois_numpost_nms_topnpost_nms_topNcomplex)realimagconcat
AxisTensor)r   r   r	   rd   rR   conditional_blockr   conjconv2dFilter)rj   filterconv2d_transpose)r   rf  rs   output_sizeconv2d_transpose_biasconv3dconv3d_transpose)r   rf  correlationInput1Input2)input1input2coscoshcrop_tensorcropShapeShapeTensor)rK   rL   tensors_nameOffsetsOffsetsTensor)shapeoffsetscrosssoftmax_with_cross_entropycross_entropy_with_softmaxcumprodcumsumcvmCVM)r   r  	data_normdecode_jpegdeformable_convOffsetMask)r   offsetrf  maskdepthwise_conv2dScale_inScale_in_eltwiseScale_weights)scale_inrc   scale_in_eltwisescale_weightsdepthwise_conv2d_transpose
dequantizeShift)rr   shiftdequantize_abs_maxdequantize_linear	ZeroPointInAccumInState)r   rr   
zero_pointin_accumin_stateOutScaleOutAccumOutState)r]   	out_scale	out_accum	out_statedequantize_logDict)r   dictdeterminantdetdgc_clip_by_normdgc_momentumVelocitycurrent_stepnranks)r   r   velocityr"   r#   current_step_tensornranks_tensorVelocityOutGrad_out)r(   velocity_outr+   grad_outdiag_v2diag
diag_embeddiagonaldigamma	dirichletrm   distelementwise_divdividedotdropoutSeed)r   seed_tensor)r   r  dropout_probis_testdropout_implementationseedfix_seed)pr  moder  r  r  r   
dropout_ndedit_distanceHypsRefs
HypsLength
RefsLength)hypsrefs
hypslength
refslengthSequenceNum)sequencenumr   eigEigenvaluesEigenvectors)out_wout_veigheigvalseigvalsh)eigenvalueseigenvectorsuploUPLOeinsumOperands
InnerCacheXShape)r   inner_cachexshapeelementwise_powelulookup_table_v2	embedding)r   r  sparse	is_sparseemptyrz  ShapeTensorList)r   r	   r{   equal	equal_allerferfinvexp	expand_v2expandexpand_shapes_tensor)r   r   r	   rd   r{   expand_as_v2	expand_asexpm1exponentialexponential_lamlambdaeye)num_rowsnum_columns)r   r	   rR   $fake_channel_wise_dequantize_max_absScales)r   scales"fake_channel_wise_quantize_abs_max)r   r  -fake_channel_wise_quantize_dequantize_abs_maxfake_dequantize_max_absfake_quantize_abs_max fake_quantize_dequantize_abs_max/fake_quantize_dequantize_moving_average_abs_maxInScale)r   in_scaler  r  )r   r  r  r  $fake_quantize_moving_average_abs_maxfake_quantize_range_abs_maxIter)r   r
  iter	OutScales)r   r  
out_scalesfaster_tokenizerVocabTextTextPair)vocabtext	text_pairInputIds
SegmentIds)	input_idssegment_idsfc)r  rc   r  feedfetch_barrierfft_c2cfft_c2rfft_r2cfill_anyfillvaluefill_diagonalfill_diagonal_tensorflash_attn_unpadded)max_seqlen_qmax_seqlen_k)r   rR   flash_attn_v3_varlenflash_attn_varlen_qkvpackedflatten_contiguous_rangeflatten)r   r  
start_axis	stop_axis)r.  r/  flipfloorelementwise_floordivfloor_divideelementwise_fmaxfmaxelementwise_fminfminfoldframefrobenius_normfill_constantfullfill_any_like	full_likefull_with_tensor)r   r{   
fused_adamfused_adam_ParamsGradsMoments1Moments2Moments2Max	Beta1Pows	Beta2PowsMasterParams)
paramsgradsr"   moments1moments2moments2_max
beta1_pows
beta2_powsmaster_paramsr>   	ParamsOutMoments1OutMoments2OutMoments2MaxOutBeta1PowsOutBeta2PowsOutMasterParamsOut)
params_outmoments1_outmoments2_outmoments2_max_outbeta1_pows_outbeta2_pows_outmaster_params_outfused_attentionLnScaleLnBiasQKVWQKVBiasCacheKVSrcMask
OutLinearWOutLinearBiasLn2ScaleLn2Bias)r   ln_scaleln_bias
qkv_weightqkv_biascache_kvsrc_maskout_linear_weightout_linear_bias
ln_scale_2	ln_bias_2ln_meanLnMeanln_var
LnVarianceln_outLnOutqkv_outQKVOutqkv_bias_out
QKVBiasOuttranspose_out_2TransposeOut2qk_outQKOutqktv_outQKTVOutsoftmax_out
SoftmaxOutattn_dropout_mask_outAttnDropoutMaskOutattn_dropout_outAttnDropoutOutsrc_mask_out
SrcMaskOutfmha_outFMHAOutout_linear_outOutLinearOutdropout_mask_outDropoutMaskOut	ln_mean_2Ln2Meanln_var_2Ln2VarianceBiasDropoutResidualOut
CacheKVOut)bias_dropout_residual_outcache_kv_outr   fused_batch_norm_act&fused_bias_dropout_residual_layer_normResidual)r   residualrs   rk  rl  )r  r  ru  ln_variancer]   fused_bn_add_activationfused_bn_add_activation_Z)r   zr   r   rr   rs   fused_conv2dResidualData)rj   rf  rs   residual_paramfused_conv2d_add_act)rj   rf  rs   residual_dataOutputs)rv   r	   fused_conv3dfused_elementwise_addfused_elementwise_divfused_elementwise_mulfused_elementwise_sub!fused_embedding_eltwise_layernormEmbs)r   embsrs   rr   fused_embedding_fc_lstm
EmbeddingsWeightH)r   
embeddingsweight_hrs   r   r   XXBatchedInputBatchedHiddenBatchedCellReorderedH0ReorderedC0)r   r   xxbatched_inputbatched_hiddenbatched_cellreordered_h0reordered_c0fused_fc_elementwise_layernormBias0Bias1)r   r   r]   bias0rr   bias1)r   r   r   fused_feedforwardDropout1SeedDropout2SeedLinear1WeightLinear1BiasLinear2WeightLinear2BiasLn1ScaleLn1Bias)r   dropout1_seeddropout2_seedlinear1_weightlinear1_biaslinear2_weightlinear2_bias	ln1_scaleln1_bias	ln2_scaleln2_biasDropout1MaskDropout2MaskLn1MeanLn1Variance
Linear1OutLn1OutDropout1OutDropout2Out)r   dropout1_maskdropout2_maskln1_meanln1_varianceln2_meanln2_variancelinear1_outln1_outdropout1_outdropout2_outr  r  dropout1_ratedropout2_rate)dropout1_seed_valdropout2_seed_valdropout1_probdropout2_probfused_gate_attentionQueryKeyQueryWeight	KeyWeightValueWeight	QKVWeightNonbatchedBias
GateWeightGateBiasOutLinearWeight)querykeyquery_weight
key_weightvalue_weightrm  nonbatched_biasrp  gate_weight	gate_biasrq  rr  QueryTransposeOutKeyTransposeOutValueTransposeOutQKVTransposeOut
SoftmaxLseGateOut)	query_transpose_outkey_transpose_outvalue_transpose_outqkv_transpose_outr  softmax_lser  gate_outr   fused_gemm_epilogue)r   r]   rs   )r   r   fused_gemm_epilogue_gradDOut)r   r]   r   out_gradDXDYDBias)x_grady_grad	bias_gradfused_multi_transformer_int8rk  rl  qkv_wrn  ro  	time_stepTimeSteprp  out_linear_wrr  ffn_ln_scale
FFNLnScaleffn_ln_bias	FFNLnBiasffn1_weight
FFN1Weight	ffn1_biasFFN1Biasffn2_weight
FFN2Weight	ffn2_biasFFN2Biasqkv_out_scaleQKVOutScaleOutLinearOutScaleFFN1OutScaleFFN2OutScale)out_linear_out_scaleffn1_out_scaleffn2_out_scale)r  r   fused_seqpool_cvmfused_transpose
fusion_gruWeightX)r   r   weight_xr  rs   
BatchedOut)r  r  r  batched_outr   
Scale_data
Shift_data)
scale_data
shift_datar  fusion_lstm)r   r   r9  r  rs   r   CheckedCell)
r   r   r   r  r  r  r  r  r  checked_cellfusion_repeated_fc_relu)r   r   rs   ReluOut)relu_outr   fusion_seqconv_eltadd_reluColMat)r   col_matcontextLengthcontextStartcontextStride)context_lengthcontext_startcontext_stridefusion_seqpool_concatfusion_transpose_flatten_concatgatherIndex)r   indexAxis	gather_ndgather_treeParents)r   parentsgaussian_randomgaussiangelugenerate_proposals_v2generate_proposals
BboxDeltasImShape)r   bbox_deltasim_shaper   	variancesRpnRoisRpnRoiProbs
RpnRoisNum)rpn_roisrpn_roi_probsrpn_rois_numpre_nms_topN)pre_nms_top_npost_nms_top_nglobal_gatherglobal_scattergrad_addgraph_khop_samplerRowCol_PtrEids)rowcolptrr   eidsOut_SrcOut_DstSample_Index	Reindex_XOut_Eids)out_srcout_dstsample_index	reindex_xout_eidsgraph_sample_neighborsPerm_Buffer)rs  rt  r   ru  perm_buffer	Out_Count)r   	out_countr  greater_equalgreater_thangrid_samplergrid_sampleGrid)r   grid
group_norm)r]   r   r   gumbel_softmaxhard_shrink
hardshrinkhard_sigmoidhardsigmoid
hard_swish	hardswishbreluhardtanhhashruntime_shape&ALL_KERNELS_MUST_COMPUTE_RUNTIME_SHAPEelementwise_heaviside	heaviside
hinge_lossLabels)r1  labelsr5  	histogram)rj   r  hierarchical_sigmoidhsigmoid_loss	PathTablePathCode)r   r   r   rs   pathcodePreOutW_Out)r   pre_outw_out
huber_loss)r   r  im2sequencer_  	increment	index_addAddValue)r   rS  	add_valueindex_elementwise_getrS  
input_dimsinput_strides
index_dimsindex_stride)r   rS  r  r  r  r  slice_offset
accumulateis_combined)r  r  r  index_elementwise_put!index_elementwise_put_with_tensorindex_sampleindex_selectinstance_norm)r]   r   r   inverseis_emptyiscloseisfinite_v2isfiniteisinf_v2isinfisnan_v2isnan
kldiv_lossTarget)r   r   kronkthvaluel1_normlabel_smooth	PriorDist)r   
prior_distlamblamb_)	r   r   r"   r9   r:   r<   r=   r#   r>   )r(   rD   rE   rG   rH   master_param_outs
layer_norm
leaky_relunegative_slopelegacy_bilinear_interplegacy_expandexpand_timesExpandTimesexpand_times_tensorlegacy_generate_proposalsImInfo)r   r`  im_infor   rb  matmullegacy_matmulDDXDDY)r   r]   r  x_grad_grady_grad_grad)r   r  r  transpose_Xtranspose_Y)transpose_xtranspose_ynearest_interplegacy_nearest_interpreshapelegacy_reshapelerp)r   r]   r  
less_equal	less_thanlgammalinear_interp_v2linear_interplinspaceStopNum)r   stopnumber	lod_resetloglog10log1plog2log_loss	Predictedlog_softmaxlogcumsumexplogical_andlogical_not
logical_orlogical_xorlogit
logsigmoid	logsumexplookup_table)r   r   lrnMidOut)r   mid_outlstsqSolution	ResidualsRankSingularValues)solution	residualsranksingular_valuesrcond	lu_unpackPivotsPmatLU)pmatlumargin_cross_entropymasked_select)r   r  match_matrix_tensor)r   r]   r   Tmp)r   tmp	matmul_v2trans_xtrans_ymulmatmul_with_flatten
matrix_nmsBBoxes)bboxesr   )r   rS  roisnummatrix_powermatrix_rank	TolTensor)r   
tol_tensor
reduce_maxrI  max_pool2d_with_indexkernel_sizeksizemax_pool3d_with_indexelementwise_maxmaximummaxoutreduce_meanr   mean_allmemory_efficient_attentionmerge_selected_rowsmerged_adam_)	r   r   r"   r9   r:   r;   r<   r=   r#   merged_momentummerged_momentum_)r   r   r  r"   r#   )r(   r  r+   meshgrid
reduce_minrH  elementwise_minminimummish	threshold)r   r  r  momentum	momentum_moving_average_abs_max_scale)r   r  r  	multi_dot	multi_gru)r   r9  r  rs   r  r   )r>  r?  multiclass_nmsmulticlass_nms3)r%  r   rZ  
NmsRoisNum)r   rS  nms_rois_nummultihead_matmulBiasQK)rj   r   rs   bias_qktranspose_Qtranspose_Ktranspose_V)transpose_qtranspose_ktranspose_vmultinomialnum_samples	multiplex)r   rS  elementwise_mulmultiplymvVec)r   vec	nanmedianMedianIndex)r   mediansrK   nearest_interp_v2nll_loss)rj   r   r  Total_weight)r   total_weightnmsBoxesKeepBoxesIdxsiou_thresholdwhere_indexnonzero	condition	ConditionnormNorm)r   ri  	not_equalsizenumel
one_hot_v2one_hotdepthdepth_tensoroverlap_addp_normpad	pad_valuepad2dpad3dpaddingsPaddingspartial_allgatherpartial_concatpartial_recvpartial_sumpixel_shufflepixel_unshufflepoissonpool2dpool3dpowr]   factorFactorTensorprelu)r   rm   printinInr'  Image)rj   image)r   varreduce_prodprod
psroi_poolROIs)r   boxes	boxes_numput_along_axisValue)arrr   valuesResultReduceInclude_self)r   reduceinclude_selfpylayerqrQR)qrquantize)rr   r  r  quantize_linearrandintrandpermrange_v2r^  
reciprocalrelurelu6elementwise_mod	remainderrenormrepeat_interleaveRepeats)repeatsr   #repeat_interleave_with_tensor_indexRepeatTensor)r   r  
requantizeShift_in	Shift_out)r  rc   shift_in	shift_outreshape2resnet_basic_blockfilter1Filter1scale1Scale1r  mean1Mean1var1Var1filter2Filter2scale2Scale2bias2Bias2mean2Mean2var2Var2filter3Filter3scale3Scale3bias3Bias3mean3Mean3var3Var3conv1Conv1saved_mean1
SavedMean1saved_invstd1SavedInvstd1	mean1_outMean1Outvar1_outVar1Outconv2Conv2conv2_input
Conv2Inputsaved_mean2
SavedMean2saved_invstd2SavedInvstd2	mean2_outMean2Outvar2_outVar2Outconv3Conv3saved_mean3
SavedMean3saved_invstd3SavedInvstd3	mean3_outMean3Outvar3_outVar3Out	MaxInput1
MaxFilter1	MaxInput2
MaxFilter2	MaxInput3
MaxFilter3)
max_input1max_filter1
max_input2max_filter2
max_input3max_filter3resnet_unitFilterXScaleXBiasXMeanXVarXFilterZScaleZBiasZMeanZVarZ)r   filter_xra   bias_xmean_xvar_xr  filter_zscale_zbias_zmean_zvar_zBitMaskConvX
SavedMeanXSavedInvstdXRunningMeanXRunningVarXConvZ
SavedMeanZSavedInvstdZRunningMeanZRunningVarZ)r   bit_maskconv_xsaved_mean_xsaved_invstd_xrunning_mean_xrunning_var_xconv_zsaved_mean_zsaved_invstd_zrunning_mean_zrunning_var_zreversermsproprmsprop_
MeanSquareMeanGrad)r   mean_square	mean_gradr"   r   r/   r#   MeanSquareOutMeanGradOut)r(   r)   mean_square_outmean_grad_outr  rnnPreState
WeightListSequenceLength)r   	pre_stateweight_listsequence_lengthDropoutStateStateReserve)r   dropout_state_outstatereserve	roi_alignroi_poolArgmax)r   r   rollshiftsShiftsTensorroundrow_convrsqrtsave_combinerr   ScaleTensorFalse)rr   rs   scatterUpdates)r   rS  updatesscatter_nd_addsearchsortedSortedSequenceValues)sorted_sequencer  segment_pool)r   r  	SummedIds)r   
summed_idsself_dp_attentionselugraph_send_recvsend_u_recv	Src_index	Dst_index)r   	src_index	dst_index	Dst_count)r   	dst_countr	  Out_sizegraph_send_ue_recvsend_ue_recv)r   r]   r`  ra  graph_send_uvsend_uvsequence_expandsequence_maskmax_lenmaxlenMaxLenTensorsequence_softmaxsgdsgd_)r   r"   r   r#   )r(   r+   shard_indexshare_bufferXOut)r   xout
share_datashare_data_shuffle_batch)r   r  
ShuffleIdxSeedOut)r   shuffle_idxseed_outshuffle_channelgroup)r   r}  sigmoidsignsilusinsinhsliceStartsTensorStartsTensorList
EndsTensorEndsTensorList)startsendsslogdeterminantslogdet	soft_relur4  softplus
softshrinksoftsignsolvesparse_batch_normsparse_reshapesparse_slice
sparse_sumsparse_sync_batch_normspectral_normV)r  r  vsplitsections)r   r   r	   rR   r{   split_with_num)rK   r   rL   sqrtsquaresqueeze2squeezeaxesstackstanhstraight_through_estimator_gradstrided_sliceStridesTensorStridesTensorList)r  r  strideselementwise_subsubtract
reduce_sum	out_dtype)r   r   dtypesvdSVH)r  svhswishsync_batch_norm)r   rr   rs   r   r   take_along_axis)r  r   tantanhtanh_shrink	tdm_childTreeInfo
child_numsr  )r   	tree_infor  r  ChildLeafMask)child	leaf_masktdm_samplerTravelLayer)r   travellayer)r   r  r  thresholded_relutilerepeat_timesRepeatTimesrepeat_times_tensortop_k_v2topkkKtop_ktopk_v1trace
transpose2	transposepermtriangular_solve	tril_triutrilinear_interp_v2trilinear_interptrunctruncated_gaussian_randomunbindunfolduniform_randomuniform)r   r	   rR   r{   uniform_random_inplaceuniform_inplaceuniqueCounts)r   r   r  countsunique_consecutive)r   rS  r  unpool)r   r   paddingunpool3d
unsqueeze2	unsqueeze
AxesTensorAxesTensorListunstackupdate_loss_scalingupdate_loss_scaling_PrevLossScalingInGoodSteps
InBadSteps)r   r=  prev_loss_scalingin_good_stepsin_bad_stepsLossScalingOutGoodStepsOutBadSteps)r   loss_scalingout_good_stepsout_bad_stepsstop_updatebool
StopUpdate
view_shapeviterbi_decode
TransitionLength)
potentialstransition_paramslengthsPath)r   r  warpctcLogitsLengthLabelLength)r1  r   logits_lengthlabels_lengthWarpCTCGrad)warpctcgradr5  where)rg  r   r]   whileyolo_boxImgSize)r   img_size)r  r   yolo_box_headyolo_box_postBoxes0Boxes1Boxes2
ImageShape
ImageScale)boxes0boxes1boxes2image_shapeimage_scale)r   rH  yolov3_loss	yolo_lossGTBoxGTLabelGTScore)r   gt_boxgt_labelgt_scoreObjectnessMaskGTMatchMask)r5  objectness_maskgt_match_maskbox_clip)rj   r  c_allreduce_sum
c_identity	c_scatterchannel_shuffle
chunk_eval	Inference	SeqLength)	inferencer   
seq_length	PrecisionRecallzF1-ScoreNumInferChunksNumLabelChunksNumCorrectChunks)	precisionrecallf1_scorenum_infer_chunksnum_label_chunksnum_correct_chunkscomm_init_allcrf_decodingEmission)emission
transitionr   lengthviterbi_pathViterbiPathcross_entropycross_entropy2MatchX)r   x_shapematch_x	ctc_alignInputLength)rj   input_lengthOutputLength)rv   output_length
cudnn_lstmInitHInitC)r   init_hinit_cr   r;  r<  StateOutLastHLastC)rB  	state_outr   last_hlast_cdecayed_adagrad)r   r   r/   r"   )r(   r)   dependDep)r   depdgc)r  r  r   r   U_outV_out
EncodeGrad
GatherBuff)u_outv_outencode_gradr  gather_buffdistribute_fpn_proposalsMultiFpnRoisRestoreIndex)multi_fpn_roisrV  restore_indexdistributed_fused_lamb_init)r   r   fp32_fused_paramFP32FusedParamfp32_fused_gradFP32FusedGradfp16_fused_paramFP16FusedParamfp16_fused_gradFP16FusedGradr9   r:   r<   r=   fused_param_offsetsFusedParamOffsetsfp32_shard_fused_param_offsetsFP32ShardFusedParamOffsetsfp16_shard_fused_param_offsetsFP16ShardFusedParamOffsets
param_info	ParamInfoparam_order
ParamOrderr(   r+   r  GradOutglobal_scaleGlobalScaler   dpsgd)r   r   r"   fetch_v2fetchflatten2)r   rI  ftrlSquaredAccumulatorLinearAccumulator)r   squared_accumulatorlinear_accumulatorr   r"   SquaredAccumOutLinearAccumOut)r(   squared_accum_outlinear_accum_outfill_constant_batch_size_likefull_batch_size_likefused_elemwise_activationIntermediateOut)r   intermediate_outfused_elemwise_add_activationfused_matmul)r   r]   r  fused_reshape_Xfused_transpose_Xfused_reshape_Yfused_transpose_Yfused_reshape_Outfused_transpose_Out)
ra   rb   rc   r  fused_reshape_xfused_transpose_xfused_reshape_yfused_transpose_yfused_reshape_outfused_transpose_outfused_softmax_maskfused_softplusfused_token_pruneAttnNewMask)attnr   r  new_maskSlimmedXCLSInds)	slimmed_xcls_indsfusion_groupInputsoutsOutsfusion_seqpool_cvm_concatfusion_squared_mat_subSquaredXSquaredY	SquaredXY)	squared_x	squared_y
squared_xyr   get_tensor_from_selected_rowsgru)rj   r   r  rs   	BatchGateBatchResetHiddenPrevBatchHidden)
batch_gatebatch_reset_hidden_prevbatch_hiddenr   gru_unit
HiddenPrev)rj   hidden_prevr  rs   GateResetHiddenPrev)gatereset_hidden_prevr   identity_losslars_momentumlars_momentum_legacy_cropr{  limit_by_capacitylod_array_lengthlogspaceBase)r   r  numbaselookup_table_dequantlstm)rj   r   r   r  rs   BatchCellPreAct)r   r   r  batch_cell_pre_actluInfos)r   pivotsinfospivotr  memcpy
memcpy_d2hmp_allreduce_sumnceSampleWeightCustomDistProbsCustomDistAliasCustomDistAliasProbs)rj   r   r  rs   sample_weightcustom_dist_probscustom_dist_aliascustom_dist_alias_probsCostSampleLogitsSampleLabels)costsample_logitssample_labelsnopnumber_countnumberspartial_sendprune_gate_by_capacityGateIdxExpertCount)gate_idxexpert_countout_gate_idx
NewGateIdxpyramid_hash	WhiteList	BlackList)r   r   
white_list
black_listDropPos
X_Temp_Out)r   drop_pos
x_temp_outrandom_routingProb
TopK_ValueTopK_Idx)prob
topk_valuetopk_idxrank_attention
RankOffset	RankParam)r   rank_offset
rank_param	InputHelpInsRank)
input_helpr   ins_rankMaxRankMaxSize)max_rankmax_sizeread_from_arrayI)arrayirecv_v2graph_reindexreindex_graph	NeighborsCountHashTable_ValueHashTable_Index)r   	neighborscounthashtable_valuehashtable_indexReindex_SrcReindex_Dst	Out_Nodes)reindex_srcreindex_dst	out_nodesrreluNoise)r   noisesend_v2sequence_convPaddingData)r   padding_datarf  paddingTrainable)padding_trainablerL  rM  rN  sequence_poolMaxIndex)r   	max_index	set_value)rK   rw  StepsTensorList)r  r  stepsset_value_with_tensor!sigmoid_cross_entropy_with_logitsskip_layernorm)r   r]   rr   rs   sparse_attentionColumnsKeyPaddingMaskAttnMask)r  r  r  r  columnskey_padding_mask	attn_maskSparseDotSdd)r   sparse_dot_sddr4  sparse_momentum)r   r   r  rS  r   r"   r#   squared_l2_normstftWindow)r   windowsync_calc_streamsync_comm_streamtemporal_shifttransfer_layoutuniform_random_batch_size_likewrite_to_array)r   r  )r<  r=  rF  rG  rH  c_sync_calc_streamc_sync_comm_streamrM  rN  rO  rP  zTensor xzTensor(out))argsrv   z&Tensor x, Tensor indices, Tensor labelz0Tensor(accuracy), Tensor(correct), Tensor(total)accuracy_checkzZTensor x, Tensor y, str fn_name, double rtol=1e-5, double atol=1e-8,  bool equal_nan=falsezTensor param, Tensor grad, Tensor avg_squared_grad, Tensor avg_squared_update, Tensor learning_rate, Tensor master_param, float rho = 0.95f, float epsilon = 1.0e-6f, bool multi_precision = falsezUTensor(param_out), Tensor(moment_out), Tensor(inf_norm_out), Tensor(master_param_out)zTensor param, Tensor grad, Tensor moment, Tensor learning_rate, Tensor master_param, float epsilon = 1.0e-6f, bool multi_precision = falsez?Tensor(param_out), Tensor(moment_out), Tensor(master_param_out)a  Tensor param, Tensor grad, Tensor learning_rate, Tensor moment1, Tensor moment2, Tensor moment2_max, Tensor beta1_pow, Tensor beta2_pow, Tensor master_param, Tensor skip_update, Scalar beta1 = 0.9f, Scalar beta2 = 0.999f, Scalar epsilon = 1.0e-8f, bool lazy_mode = false, int64_t min_row_size_to_use_multithread = 1000, bool multi_precision = false, bool use_global_beta_pow = false, bool amsgrad = falsezTensor(param_out), Tensor(moment1_out), Tensor(moment2_out), Tensor(moment2_max_out), Tensor(beta1_pow_out), Tensor(beta2_pow_out), Tensor(master_param_out)zTensor param, Tensor grad, Tensor learning_rate, Tensor moment, Tensor inf_norm, Tensor beta1_pow, Tensor master_param, float beta1 = 0.9f, float beta2 = 0.999f, float epsilon = 1.0e-8f, bool multi_precision = falsea  Tensor param, Tensor grad, Tensor learning_rate, Tensor moment1, Tensor moment2, Tensor moment2_max, Tensor beta1_pow, Tensor beta2_pow, Tensor master_param, Tensor skip_update, Scalar beta1 = 0.9f, Scalar beta2 = 0.999f, Scalar epsilon = 1.0e-8f, float lr_ratio = 1.0f, float coeff = 0.01f, bool with_decay = false, bool lazy_mode = false, int64_t min_row_size_to_use_multithread = 1000, bool multi_precision = false, bool use_global_beta_pow = false, bool amsgrad = falsez/Tensor x, float alpha = 1.0f, float beta = 1.0fzTensor (out)zATensor input, Tensor x, Tensor y, float beta=1.0, float alpha=1.0zBTensor x, Tensor scale, Tensor bias, str data_layout = "AnyLayout"z?Tensor input, IntArray output_shape={}, bool align_corners=truezTensor(output)z/Tensor x, int64_t[] axis={}, bool keepdim=false
all_gatherz'Tensor x, int ring_id = 0, int nranks=0
all_reducez.Tensor x, int ring_id = 0, int reduce_type = 0
all_to_allzTensor x, int ring_id = 0z\Tensor x, Tensor y, Scalar(double) rtol=1e-5, Scalar(double) atol=1e-8, bool equal_nan=falseTensor	ap_facadezTensor[] xs, int64_t num_outputs, str custom_op_name, str infer_meta_func_name, str infer_symbolic_func_name, str serialized_attributeszTensor[](out){num_outputs}ap_trivial_fusion_beginzTensor[] xsap_trivial_fusion_endap_variadiczTensor[] xs, int num_outputs, str code_module_lambda, str infer_symbolic_lambda, str infer_meta_lambda, str rnel_dispatch_lambda, str kernel_dispatch_const_data_lambdaapply_per_channel_scalezTensor x, Tensor scaleszmTensor x, Scalar(int64_t) axis, bool keepdims = false, bool flatten = false, DataType dtype = DataType::INT64z?Tensor x, int axis=-1, bool descending=false, bool stable=falsezTensor(out), Tensor(indices)
as_stridedzLTensor input, int64_t[] dims = {}, int64_t[] stride = {}, int64_t offset = 0asgd_z~Tensor param, Tensor grad, Tensor learning_rate, Tensor d, Tensor y, Tensor n, Tensor master_param, bool multi_precision=falsezITensor(param_out), Tensor(d_out), Tensor(y_out), Tensor(master_param_out)assign_out_zTensor x, Tensor outputz.Tensor x, Tensor cum_count, Tensor eff_num_lenassign_value_zMTensor output, int[] shape, DataType dtype, Scalar[] values, Place place = {}zTensor x, Tensor ya  Tensor x, Tensor c0, Tensor h0, Tensor attention_weight, Tensor attention_bias, Tensor attention_scalar, Tensor attention_scalar_bias, Tensor lstm_weight, Tensor lstm_bias, str gate_activation = "sigmoid", str cell_activation = "tanh", str candidate_activation = "tanh"zuTensor (hidden), Tensor (cell), Tensor (attentioned_x), Tensor (attention_fc_out), Tensor (lstm_x), Tensor (lstm_out)zTensor x, Tensor label, Tensor stat_pos, Tensor stat_neg, Tensor ins_tag_weight, str curve = "ROC", int num_thresholds = (2 << 12) - 1, int slide_steps = 1z7Tensor(auc), Tensor(stat_pos_out), Tensor(stat_neg_out)average_accumulates_zTensor param, Tensor in_sum_1, Tensor in_sum_2, Tensor in_sum_3, Tensor in_num_accumulates, Tensor in_old_num_accumulates, Tensor in_num_updates, float average_window = 0, int64_t max_average_window = INT64_MAX, int64_t min_average_window = 10000LzTensor(out_sum_1), Tensor(out_sum_2), Tensor(out_sum_3), Tensor(out_num_accumulates), Tensor(out_old_num_accumulates), Tensor(out_num_updates)zTensor x, int ring_id=0z#Tensor input, Tensor w, Tensor biaszTensor input, Tensor labelbeam_searchz~Tensor pre_ids, Tensor pre_scores, Tensor ids, Tensor scores, int level, int beam_size, int end_id, bool is_accumulated = truezDTensor (selected_ids), Tensor (selected_scores), Tensor (parent_idx)zTensor x, Tensor out_size, Tensor[] size_tensor, Tensor scale_tensor, str data_format="NCHW", int out_d=0, int out_h=0, int out_w=0, double[] scale={}, str interp_method="bilinear", bool align_corners=true, int align_mode=1z.Tensor x, Tensor y, Tensor weight, Tensor biasz3Tensor x, Tensor weights, Scalar(int) minlength = 0binomialzTensor count, Tensor probzITensor dist_mat, str match_type = "bipartite", float dist_threshold = 0.5zATensor (col_to_row_match_indices), Tensor (col_to_row_match_dist)bitwise_left_shiftz-Tensor x, Tensor y, bool is_arithmetic = truebitwise_right_shiftzTensor input, Tensor im_infozTensor (output)zTensor prior_box, Tensor prior_box_var, Tensor target_box, str code_type = "encode_center_size", bool box_normalized = true, int axis = 0, float[] variance = {}zTensor(output_box)	broadcastz'Tensor x, int ring_id = 0, int root = 0zTensor[] inputzTensor[]{input.size()}"build_src_rank_and_local_expert_idzWTensor expert_num_global_tensor, int64_t[] expert_num_global, int64_t num_local_expertsz'Tensor(vector), Tensor(local_expert_id)zDTensor x, int ring_id, bool use_calc_stream, bool use_model_parallelzZTensor x, int rank, int nranks, int ring_id, bool use_calc_stream, bool use_model_parallelzUTensor x, int ring_id = 0, int root = 0, int nranks = 0, bool use_calc_stream = falsez`Tensor logits, Tensor label,  int64_t ignore_index=-100, int ring_id=0, int rank=0, int nranks=0zTensor(softmax), Tensor(loss)zWTensor x, int rank = 0, int nranks = 1, int ring_id = 0, bool use_model_parallel = truecal_aux_losszTensor gate_prob, Tensor dispatch_mask, Tensor tokens_mask, Tensor dispatch_tokens_mask, int64_t num_experts, bool use_group, int64_t moe_k, float clip_minz4Tensor(l_aux_loss), Tensor(seqlen_float), Tensor(ce)calc_reduced_attn_scoresz&Tensor q, Tensor k, Tensor softmax_lsezTensor(reduced_scores)zTensor x, DataType dtypezTensor x, float alpha = 1.0z,Tensor x, int groups, str data_format="NCHW"zTensor[] x, Tensor scalez/Tensor[](out){x.size()}, Tensor(found_infinite)check_numericszTensor tensor, str op_type = "", str var_name = "", int check_nan_inf_level = 0, int stack_height_limit = -1, str output_dir = ""zTensor(stats), Tensor(values)zTensor x, bool upper=falsez$Tensor x, Tensor y, bool upper=falsezTensor label, int num_classes, int num_samples, int ring_id = 0, int rank = 0, int nranks = 1, bool fix_seed = false, int seed = 0z:Tensor(remapped_label), Tensor(sampled_local_class_center)z.Tensor x, Scalar(float) min, Scalar(float) maxzTensor x, float max_norma  Tensor[] input, DataType dtype, bool copy_data = false, bool set_constant = false, bool persist_output = false, float constant = 0.0, bool use_align = true, int align_size = -1, int size_of_dtype = -1, int64_t[] concated_shapes = {}, int64_t[] concated_ranks = {}z4Tensor[](output){input.size()}, Tensor(fused_output)zhTensor[] multi_level_rois, Tensor[] multi_level_scores, Tensor[] multi_level_rois_num, int post_nms_topnz$Tensor (fpn_rois), Tensor (rois_num)zTensor real, Tensor imagzTensor[] x, Scalar axis=0zTensor input, Tensor filter, int[] strides={1, 1}, int[] paddings={0, 0}, str padding_algorithm="EXPLICIT", int[] dilations={1, 1}, int groups=1, str data_format="NCHW"zTensor x, Tensor filter, int[] strides={1, 1}, int[] paddings={0, 0}, int[] output_padding={}, IntArray output_size={}, str padding_algorithm="EXPLICIT", int groups=1, int[] dilations={1, 1}, str data_format="NCHW"zTensor x, Tensor filter, Tensor bias, int[] strides={1, 1}, int[] paddings={0, 0}, int[] output_padding={}, IntArray output_size={}, str padding_algorithm="EXPLICIT", int groups=1, int[] dilations={1, 1}, str data_format="NCHW"zTensor input, Tensor filter, int[] strides={1, 1, 1}, int[] paddings={0, 0, 0}, str padding_algorithm="EXPLICIT", int groups=1, int[] dilations={1, 1, 1}, str data_format="NCDHW"zTensor x, Tensor filter, int[] strides={1, 1, 1}, int[] paddings={0, 0, 0}, int[] output_padding={}, int[] output_size={}, str padding_algorithm="EXPLICIT", int groups=1, int[] dilations={1, 1, 1}, str data_format="NCHW"copy_toz$Tensor x, Place place, bool blockingcopysignzTensor input1, Tensor input2, int pad_size, int kernel_size, int max_displacement, int stride1, int stride2, int corr_type_multiply=1z?Tensor emission, Tensor transition, Tensor label, Tensor lengthzTensor (viterbi_path)z4Tensor x, IntArray shape = {}, IntArray offsets = {}z Tensor x, Tensor y, int axis = 9zTensor input, Tensor label, bool soft_label=false, bool use_softmax=true, bool numeric_stable_mode=true, int ignore_index=-100, int axis=-1)cross_entropy_with_softmax_bwd_w_downcastz.Tensor label, Tensor softmax, Tensor loss_gradzTensor(input_grad)zcTensor input, Tensor input_length, int blank = 0, bool merge_repeated = true, int padding_value = 0z'Tensor (output), Tensor (output_length)zTensor x, Tensor init_h, Tensor init_c, Tensor w, Tensor[] weight_list, Tensor sequence_length, float dropout_prob = 0.0, bool is_bidirec = false, int hidden_size = 100, int num_layers = 1, bool is_test = false, int seed = 0zTTensor (out), Tensor (last_h), Tensor (last_c), Tensor (reserve), Tensor (state_out)cummaxz7Tensor x, int axis=-1, DataType dtype = DataType::INT64cumminz<Tensor x,  int dim, bool exclusive=false, bool reverse=falsezVTensor x, Scalar axis=-1, bool flatten=false, bool exclusive=false, bool reverse=falsez)Tensor x, Tensor cvm, bool use_cvm = truer   z5str name, IntArray shape, DataType dtype, Place placezlTensor param, Tensor grad, Tensor moment, Tensor learning_rate, float decay = 0.95f, float epsilon = 1.0e-6fz%Tensor(param_out), Tensor(moment_out)zTensor x, str mode, Place placezTensor x, Tensor offset, Tensor filter, Tensor mask, int[] strides, int[] paddings, int[] dilations, int deformable_groups, int groups, int im2col_stepzTensor x, Tensor[] depzTensor input, Tensor filter, int[] strides={1, 1}, int[] paddings={0, 0}, str padding_algorithm="EXPLICIT", int groups=1, int[] dilations={1, 1}, str data_format="NCHW"z'Tensor x, Tensor scale, float max_rangezTensor x, Tensor dictzTensor u, Tensor v, Tensor grad, Tensor param, Tensor current_step, Tensor nranks, float m=0.9, bool use_nesterov=true, float[] sparsity={}, float rampup_begin_step=0.0, float rampup_step=0.0, float regular_coeff=0.0, int regular_type=0zcTensor(u_out), Tensor(v_out), Tensor(encode_grad), Tensor(grad_out), Tensor(k), Tensor(gather_buff)zMTensor x, Tensor current_step, float max_norm, float rampup_begin_step = -1.0aH  Tensor param, Tensor grad, Tensor velocity, Tensor learning_rate, Tensor master_param, Tensor current_step_tensor, Tensor nranks_tensor, float mu, bool use_nesterov = false, str regularization_method = "", float regularization_coeff = 0.0f, bool multi_precision = false, float rescale_grad = 1.0f, float rampup_begin_step = -1.0zWTensor (param_out), Tensor (velocity_out), Tensor (master_param_out), Tensor (grad_out)z3Tensor x, int offset = 0, float padding_value = 0.0z:Tensor input, int offset = 0, int dim1 = -2, int dim2 = -1z6Tensor x, int offset = 0, int axis1 = 0, int axis2 = 1zTensor alphadisable_check_model_nan_infzTensor x, int flag = 0z!Tensor x, Tensor y, float p = 2.0zTensor param, Tensor grad, Tensor learning_rate, float clip = 10.0f, float batch_size = 16.0f, float sigma = 1.0f, int seed = 0zTensor(param_out)zTensor x, Tensor seed_tensor, Scalar p = 0.5f, bool is_test = false, str mode = "downgrade_in_infer", int seed = 0, bool fix_seed = falsezTensor(out), Tensor(mask)zWTensor hyps, Tensor refs, Tensor hypslength, Tensor refslength, bool normalized = falsez Tensor(sequencenum), Tensor(out)zTensor(out_w), Tensor(out_v)zTensor x, str UPLO = "L"z.Tensor x, str uplo = "L", bool is_test = falsez)Tensor(eigenvalues), Tensor(eigenvectors)zTensor x, float alpha = 1.0fembedding_grad_add_toz8Tensor token_indices, Tensor main_grad_, Tensor out_gradzTensor(main_grad_out)embedding_with_scaled_gradientz/Tensor x, Tensor weight, int64_t padding_idx=-1zHIntArray shape, DataType dtype=DataType::FLOAT32, Place place=CPUPlace()
empty_likez@Tensor x, DataType dtype = DataType::UNDEFINED, Place place = {}enable_check_model_nan_infzTensor x, int flag = 1zTensor x, IntArray shape = {}z/Tensor x, Tensor y, int64_t[] target_shape = {}expand_modality_expert_idztTensor expert_id, int64_t num_expert_per_modality, int64_t group_size, int64_t modality_offset, bool is_group_expertzTensor(expert_id_out)zTensor x, float lamzUScalar num_rows, Scalar num_columns, DataType dtype=DataType::FLOAT32, Place place={}z]Tensor x, Tensor[] scales, int[] quant_bits = {8}, int quant_axis = 0, int x_num_col_dims = 1zZTensor x, int bit_length = 8, int round_type = 1, int quant_axis = 0, bool is_test = falsezTensor(out), Tensor(out_scale)zDTensor x, int bit_length = 8, int round_type = 1, int quant_axis = 0z0Tensor x, int bit_length = 8, int round_type = 1zTensor x, Tensor in_scale, Tensor in_accum, Tensor in_state, float moving_rate = 0.9, int bit_length = 8, bool is_test = false, int round_type = 1zDTensor(out), Tensor(out_scale), Tensor(out_state), Tensor(out_accum)z~Tensor x, Tensor in_scale, Tensor iter, int window_size = 10000,  int bit_length = 8, bool is_test = false, int round_type = 1z2Tensor(out), Tensor(out_scale), Tensor(out_scales)z9Tensor x, int64_t[] axes, str normalization, bool forwardzSTensor x, int64_t[] axes, str normalization, bool forward, int64_t last_dim_size=0LzHTensor x, int64_t[] axes, str normalization, bool forward, bool onesidedz Tensor x, Scalar(double) value=0z6Tensor x, float value=0, int offset=0, bool wrap=falsezBTensor x, Tensor y, int64_t offset = 0, int dim1 = 0, int dim2 = 1
flash_attnzTensor q, Tensor k, Tensor v, Tensor fixed_seed_offset, Tensor attn_mask, float dropout = 0.0, bool causal = false, bool return_softmax = false, bool is_test = false, str rng_name = ""zFTensor(out), Tensor(softmax), Tensor(softmax_lse), Tensor(seed_offset)flash_attn_qkvpackedzTensor qkv, Tensor fixed_seed_offset, Tensor attn_mask, float dropout = 0.0, bool causal = false, bool return_softmax = false, bool is_test = false, str rng_name = ""a  Tensor q, Tensor k, Tensor v, Tensor cu_seqlens_q,  Tensor cu_seqlens_k, Tensor fixed_seed_offset, Tensor attn_mask, Scalar max_seqlen_q, Scalar max_seqlen_k, float scale, float dropout = 0.0, bool causal = false, bool return_softmax = false, bool is_test = false, str rng_name = ""flash_attn_v3a  Tensor q, Tensor k, Tensor v, Tensor q_v_, Tensor q_descale_, Tensor k_descale_, Tensor v_descale_, float softmax_scale, bool is_causal, int window_size_left, int window_size_right, float softcap, int num_splits, bool manual_set_pack_gqa, bool pack_gqa_, int sm_marginz Tensor(out), Tensor(softmax_lse)a{  Tensor q, Tensor k, Tensor v, Tensor cu_seqlens_q, Tensor cu_seqlens_k, Tensor seqused_q, Tensor seqused_k, Tensor qv, Tensor q_descale, Tensor k_descale, Tensor v_descale, Scalar max_seqlen_q, Scalar max_seqlen_k, float softmax_scale, bool causal, int window_size_left, int window_size_right, float softcap, int num_splits, bool manual_set_pack_gqa, bool pack_gqa, int sm_margina#  Tensor qkv, Tensor cu_seqlens_q,  Tensor cu_seqlens_k, Tensor fixed_seed_offset, Tensor attn_mask, Scalar max_seqlen_q, Scalar max_seqlen_k, float scale, float dropout = 0.0, bool causal = false, bool return_softmax = false, bool is_test = false, str rng_name = "", bool varlen_padded = trueflashmask_attentionzTensor q, Tensor k, Tensor v, Tensor startend_row_indices,  Tensor fixed_seed_offset, float dropout = 0.0, bool causal = false, bool return_softmax = false, bool is_test = false, str rng_name = ""flashmask_attention_v2zqTensor q, Tensor k, Tensor v, Tensor startend_row_indices, Tensor block_mask, float softmax_scale, bool is_causalz/Tensor x, int start_axis = 1, int stop_axis = 1zTensor x, int[] axiszaTensor x, int[] output_sizes, int[] kernel_sizes,  int[] strides, int[] paddings, int[] dilationsfractional_max_pool2dzfTensor x, int[] output_size, int[] kernel_size = {0, 0}, float random_u = 0.0, bool return_mask = truefractional_max_pool3dziTensor x, int[] output_size, int[] kernel_size = {0, 0, 0}, float random_u = 0.0, bool return_mask = truez7Tensor x, int frame_length, int hop_length, int axis=-1z9Tensor x, IntArray axis,  bool keep_dim,  bool reduce_allzTensor param, Tensor squared_accumulator, Tensor linear_accumulator, Tensor grad, Tensor learning_rate, float l1=0.0f, float l2=0.0f, float lr_power=-0.5fzFTensor(param_out), Tensor(squared_accum_out), Tensor(linear_accum_out)z^IntArray shape, Scalar(double) value, DataType dtype=DataType::FLOAT32, Place place=CPUPlace()full_zmTensor output, IntArray shape, Scalar(double) value, DataType dtype=DataType::FLOAT32, Place place=CPUPlace()z~Tensor input, int[] shape, DataType dtype, Scalar(double) value, int input_dim_idx, int output_dim_idx, Place place=CPUPlace()full_int_arrayzIint64_t[] value, DataType dtype=DataType::FLOAT32, Place place=CPUPlace()zNTensor x, Scalar value, DataType dtype = DataType::UNDEFINED, Place place = {}z>Tensor value, IntArray shape, DataType dtype=DataType::FLOAT32znTensor x, Tensor scale, Tensor bias, Tensor mean, Tensor variance, float momentum, float epsilon, str act_typezvTensor(out), Tensor(mean_out), Tensor(variance_out), Tensor(saved_mean), Tensor(saved_variance), Tensor(reserve_space)zxTensor x, Tensor z, Tensor scale, Tensor bias, Tensor mean, Tensor variance, float momentum, float epsilon, str act_typefused_rms_norm_quantzTensor x, Tensor bias, Tensor residual, Tensor norm_weight, Tensor norm_bias, float epsilon, int begin_norm_axis, float quant_scale, int quant_round_type, float quant_max_bound, float quant_min_boundz2Tensor(out), Tensor(residual_out), Tensor(inv_var)zTensor x, Tensor mask!fused_softmax_mask_upper_trianglezTensor XzTensor(Out)	gammainccgammalnz%Tensor x, Tensor index, Scalar axis=0zTensor x, Tensor indexzTensor ids, Tensor parentszOIntArray shape, float mean, float std, int seed, DataType dtype, Place place={}gaussian_inplacez1Tensor x, float mean=0, float std=1.0, int seed=0z#Tensor x,  bool approximate = falsezTensor scores, Tensor bbox_deltas, Tensor im_shape, Tensor anchors, Tensor variances, int pre_nms_top_n, int post_nms_top_n, float nms_thresh, float min_size, float eta, bool pixel_offset=truez=Tensor(rpn_rois), Tensor(rpn_roi_probs), Tensor(rpn_rois_num)zBTensor x, Tensor local_count, Tensor global_count, int ring_id = 0zVTensor row, Tensor colptr, Tensor x, Tensor eids, int[] sample_sizes, bool return_eidsz[Tensor(out_src), Tensor(out_dst), Tensor(sample_index), Tensor(reindex_x), Tensor(out_eids)z~Tensor row, Tensor colptr, Tensor x, Tensor 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 5
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DLa"	a"
 8Da" la" a"" #a"*  Ui+a"2  ]S3a":  g q;a"B  jiCa"J  l qKa"R A Sa"Z S[a"b V ca"j Q"ka"r 
Asa"z 9{a"B @Ca"J +Ka"R nSa"Z A[a"b Aca"j ka"r 
Asa"z  Z.{a"B  Ca"J Ka"R  z.Sa"Z ) [a"b ca"j ka"r Q0sa"z {a"B Ca"J ^Ka"R  Q]Sa"Z [a"b ca"j )ka"r @sa"z _{a"B Ca"J $Ka"R Sa"Z  f J[a"b 
 pKca"j  J cka"r Ssa"z ){a"B 5Ca"J ,Ka"R  QXSa"Z [a"b  v"ca"j @ka"r  v"sa"z E{a"B +Ca"J ]UKa"R $Sa"Z ?[a"b ca"j $ka"r ?sa"z ${a"B 
$Ca"J .#Ka"R  u&Sa"Z 9[a"b  *ca"j )i;+ka"r Vsa"z l{a"B	 VC	a"J	 gK	a"R	 #r1%S	a"Z	 i[	a"b	  nHc	a"j	 8*!k	a"r	 *s	a"z	 {	a"B
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sa"z {a"B Q)Ca"J FKa"R 2Sa"Z ! ^1#[a"b 0@&2ca"j u;ka"r  shsa"z I0{a"B I0Ca"J NKa"R hSa"Z 
; [a"b Gca"j ~9ka"r 1sa"z  j{a"B ( Ca"J  Ka"R ! m#Sa"Z 9[a"b 'ca"j 
ka"r 
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$Ca"J  R%Ka"R  ^-Sa"Z i4[a"b 
0ca"j ,0ka"r sa"z B={a"B 
.Ca"J J)Ka"R %A'Sa"Z Z[a"b Rca"j !(#ka"r $sa"z 
{a"B Ca"J 
Ka"R /Sa"Z A[a"b   G)"ca"j ka"r %sa"z 
g{a"B +o-Ca"J )l2+Ka"R 4V26Sa"Z 9 [a"b B2ca"j 'B2)ka"r 6 eX8sa"z + eX-{a"B " QF$Ca"J KKa"R eSa"Z Z[a"b 2ca"j Hka"r Tsa"z  MZ{a"B  {ZCa"J  oZKa"R  _4Sa"Z  N4[a"b " xZ$ca"j  YZka"r  D4sa"z A{a"B & Ca"J Ka"R $Sa"Z $[a"b sca"j x-ka"r {-sa"z I{a"B KCa"J  mZKa"R pSa"Z [a"b  Qca"j [ka"r `sa"z P{a"B  A KCa"J  K K Ka"R  ZFSa"Z '[a"b (*ca"j $ka"r sa"z 7{a"B (Ca"J ,Ka"R aSa"Z C[a"b 5ca"j  SQka"r Tsa"z T{a"B hoCa"J  QDKa"R ySa"Z x=[a"b 
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Ca"J 	Ka"R 
Sa"Z -[a"b  F ca"j  ka"r -sa"z I{a"B  T Ca"J  m Ka"R ( m *Sa"Z Q[a"b (ca"j 6ka"r 7sa"z II{a"B  v"Ca"J Ka"R Sa"Z o[a"b ca"j ka"r sa"z [{a"B  $C a"J  N0K a"R  S a"Z  G [ a"b   s Yc a"j  d?k a"r  8s a"z  3{ a"B! C!a"J! DK!a"R!  v"S!a"Z! W[!a"b! `c!a"j! 
k!a"r! s!a"z! {!a"B" C"a"J" ;K"a"R" )S"a"Z" e["a"b" $c"a"j" k"a"r" $s"a"z" ${"a"B# -C#a"J# K#a"R# dS#a"Z# V[#a"b# @ c#a"j#  ~k#a"r#  Cds#a"z# L^{#a"B$ 	->C$a"J$ ?K$a"R$ Z6S$a"Z$  Q1[$a"b$ 5 c$a"j$ " nT$k$a"r$ ' s$a"z$ =.{$a"B%  f?C%a"J% !K%a"R% VS%a"Z% J[%a"b% _c%a"j% 
@k%a"r%  j-s%a"z%  q-{%a"B& [3C&a"J& 4K&a"R& @S&a"Z& [&a"b& U0c&a"j& .k&a"r& .s&a"z& ! }N#{&a"B' C'a"J'  ] aK'a"R'  U FS'a"Z' !0['a"b' [3c'a"j' (k'a"r' A0s'a"z' H{'a"B( HC(a"J( `K(a"R( kwS(a"Z( " A M$[(a"b( kwc(a"j( . T _0k(a"r(  qw"s(a"z(  | J{(a"B)  PCC)a"J)  KUK)a"R) +S)a"Z) [)a"b)  PDc)a"j) Qk)a"r) /s)a"z) 	&{)a"B*  w yC*a"J* U0K*a"R*  v"S*a"Z* $[*a"b* r5c*a"j* 
2k*a"r* "s*a"z* A-{*a"B+ +C+a"J+  K+a"R+ 3S+a"Z+ Z[+a"b+ Nc+a"j+ 7k+a"r+ }s+a"z+ 
<{+a"B, {C,a"J, AK,a"R, BS,a"Z, B[,a"b, Jc,a"j, Lk,a"r, s,a"z, !{,a"B-  VC-a"J-  WK-a"R- 
)S-a"Z- T[-a"b-  J,c-a"j- Hk-a"r- ^(s-a"z-  T{-a"B. xC.a"J.  RHK.a"R. 	2(S.a"Z.  H i[.a"b. cc.a"j. 4k.a"r. As.a"z. 7{.a"B/ eEC/a"J/ ]K/a"R/  S/a"Z/ [/a"b/ Qc/a"j/ )k/a"r/ ;s/a"z/ jO{/a"B0 C0a"J0 K0a"R0 =S0a"Z0 K[0a"b0 *N,c0a"j0 *k0a"r0 : s0a"z0 ){0a"B1 C1a"J1  F EK1a"R1 
 VnS1a"Z1  h[1a"b1 |0c1a"j1 Ak1a"r1 -s1a"z1  il{1a"B2 V.C2a"J2 K2a"R2 YS2a"Z2 M[2a"b2 8c2a"j2 ck2a"r2 D3s2a"z2 x{2a"B3 p2C3a"J3  O2K3a"R3 bS3a"Z3  b [3a"b3 Cc3a"j3 a4k3a"r3 
i s3a"z3  X{3a"B4 r?C4a"J4 K4a"R4 S4a"Z4 ][4a"b4  c4a"j4 ;Fk4a"r4 )s4a"z4 {4a"B5 (h*C5a"J5 K5a"R5 S5a"Z5 
[5a"b5 c5a"j5 ~k5a"r5 s5a"z5 0{5a"B6 FC6a"J6 1K6a"R6 S6a"Z6 $[6a"b6 xKc6a"j6 ik6a"r6 ?-s6a"z6 5!{6a"B7 C7a"J7 K7a"R7 S7a"Z7 ,[7a"b7 * c7a"j7 k7a"r7 Fs7a"z7 d {7a"B8 XC8a"J8 
dK8a"R8 
64S8a"Z8 [8a"b8 $c8a"j8 k8a"r8  D Ks8a"z8 {8a"B9 6C9a"J9 
K9a"R9 S9a"Z9 [9a"b9 ^6c9a"j9  d=k9a"r9 ^s9a"z9 D{9a"B: zTC:a"J: e0K:a"R: HS:a"Z: &[:a"b: &c:a"j: ek:a"r: *s:a"z: P{:a"B;  v"C;a"J; *K;a"R; NS;a"Z; [;a"b; $c;a"j;   C"k;a"r; ,as;a"z; ^{;a"B< fC<a"J<  GK<a"R< % ` 'S<a"Z<  I>[<a"b< |c<a"j<  ]k<a"r< .s<a"z< 1&{<a"B=  lpC=a"J= AK=a"R= .S=a"Z= 3[=a"b= Bc=a"j= n0k=a"r=  E5s=a"z=  E6{=a"B> ^C>a"J>  BK>a"R> _.S>a"Z>   DN"[>a"b> 6c>a"j>  d1k>a"r> 8s>a"z>  s5{>a"B?  jPC?a"J? ZK?a"R? PS?a"Z? _"[?a"b?  V ^c?a"j? D;k?a"r? 7-s?a"z?  YR{?a"B@  }`C@a"J@ 7-K@a"R@ DS@a"Z@ 1[@a"b@ 
$c@a"j@ !k@a"r@ Ws@a"z@ {@a"BA  D KCAa"JA WKAa"RA  F Z!SAa"ZA $[Aa"bA *\cAa"jA $kAa"rA TsAa"zA e'{Aa"BB $CBa"JB $KBa"RB  A oSBa"ZB ]6[Ba"bB $cBa"jB $kBa"rB sBa"zB ${Ba"BC $CCa"JC XKCa"RC $SCa"ZC 
@[Ca"bC $cCa"jC $kCa"rC $sCa"zC W{Ca"DD % 
 k
 %
 %
 .+
 I
 7
 CQ{Da"r  