vendor/libxlearn_api.so in xlearn-0.1.3 vs vendor/libxlearn_api.so in xlearn-0.1.4

- old
+ new

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Io(HIHgH!HIGLHL|$hHD!HD$`H\$hHCH=XF!*CPS#HHPC PS HHPHHPC H4$H4IM9H$dH3%(uhH[]A\A]A^A_H$L$H$L$HT$pLL$xH$L$HHAHHF LHUH}H9tLH?uHHH9t:H8tH|$hHtH|$H|$H|$HteH]f.HbAWAVIAUIATIUSHHHoHGIH)HH9I)L!LHH9HIHI)HL)HH$LHL)IFHHLI9IuLH)H<HH?HSH9HGHHMeHt@MeIuHt2MeIuHt$MeIu HtMe Iu(HtMe(Iu0H9tFHH)HyHHL?H9t)ITfIn1flH)HH9wJ4I9tL&H[]A\A]A^A_@H)HH<H?H9HGHLeH}HLeH}HLeH}HLeH} HLe H}(HqLe(H}0HH9t"II)IpHHL 6IHL'H|I~HIM~L9MELL)H<HH?HUH9HGHJHMeHt@MeMEHt2MeMEHt$MeME HtMe ME(HtMe(ME0H9HH)HqHHH<6H9t-ITfIn1flH)HH9rMH9RM H[]A\A]A^A_JHHHHH)HH)H9H9HHCHrSH9wNMI)HL1E1eDHLH)DLHIF@LHH)HH$'IMM~IHH$I)II<$II<I?I9LGHH8HpHHxHpHHxHpHHxHp HHx Hp(H[Hx(IH0L9tIM)IrHHL6Iu{H8LHxMM)LMH9MHtHL $L $MM~InH[]A\A]A^A_M&HsIHHL6JfHnE1Lflf.I)HI9rJM9KIfDHIHsIHHHL 6HTfIn1flH)HH9rJ<M9HLfHMLLI~O@LLLLL$H $LL$H $ILHLLD$H $iLD$H $I`HH,LefDfDpfD`LeH}fDHfDAHf.AHfAHzfAHjfIH]H= H8AH?HHbasic_string::_M_construct null not valid---------------------------------------------------------------------------------------------- _ | | __ _| | ___ __ _ _ __ _ __ \ \/ / | / _ \/ _` | '__| '_ \ > <| |___| __/ (_| | | | | | | @@ -463,12 +379,12 @@ /home/runner/work/ml-builds/ml-builds/xlearn/src/c_api/c_api.ccInput for validation type Must equal to train's!/home/runner/work/ml-builds/ml-builds/xlearn/src/data/data_structure.hHECK failed == NULL Info: Model: %s Loss: %s -Total time cost: %.2f (sec)[------------] Train set must have label!testvalidatetaskbinaryregmetricloglossoptepochfoldblock_sizestop_windowlrlambdainiton_disklock_freeearly_stopbin_outfrom_fileCHECK_GT failed = row_idXlearnDataFreeAddNode?Cannot create file: . create a new directory. -Cannot create file: () Please check that wether you need to basic_string::append/home/runner/work/ml-builds/ml-builds/xlearn/src/base/split_string.cc%s: __pos (which is %zu) > this->size() (which is %zu)delim != NULLresult != NULLbasic_string::substrSplitStringToSetUsingSplitStringUsingvector::_M_default_append/home/runner/work/ml-builds/ml-builds/xlearn/src/base/levenshtein_distance.cc!source.empty()!target.empty()!str.empty()!list.empty()ldistanceFindSimilarFindzD/home/runner/work/ml-builds/ml-builds/xlearn/src/base/file_util.hbuflenError: invoke fwrite().Error: invoke fread().CHECK_EQ failed ret!score_func.empty()!loss_func.empty()num_featurescalelinearUnknow score function: CHECK_NE failed truebias: i_v_filenameCannot open file: with mode: file_ptrError: invoke fclose().[ ERROR ] /home/runner/work/ml-builds/ml-builds/xlearn/src/data/model_parameters.ccCannot allocate enough memory for current model parameters. Parameter size: Cannot Load model from the file: %sSetBestModelReadDataFromDiskReadStringFromFileDeserializeSerializeToTXTWriteDataToDiskWriteStringToFileOpenFileOrDieSerializeModelinitialInitialize/home/runner/work/ml-builds/ml-builds/xlearn/src/base/file_util.ReadDataFromDisk????/data/model_para>0?std::future_error: /home/runner/work/ml-builds/ml-builds/xlearn/src/loss/loss.ccCHECK_GE failed end_idxstart_idxpred.empty()pred.size()matrix->row_lengthsquaredcross-entropyvector::_M_fill_insertenqueue on stopped ThreadPoolvector::reservePredictpred_threadSt11_Mutex_baseILN9__gnu_cxx12_Lock_policyE2EENSt13__future_base12_Task_setterISt10unique_ptrINS_7_ResultIvEENS_12_Result_base8_DeleterEEZNS_11_Task_stateISt5_BindIFS8_IFPFvPKN6xLearn7DMatrixEPNS9_5ModelEPSt6vectorIfSaIfEEPNS9_5ScoreEbmmESC_SE_SI_SK_bmmEEvEESaIiEFvvEE6_M_runEvEUlvE_vEENSt13__future_base12_Task_setterISt10unique_ptrINS_7_ResultIvEENS_12_Result_base8_DeleterEEZNS_11_Task_stateISt5_BindIFS8_IFPFvPKN6xLearn7DMatrixEPNS9_5ModelEPSt6vectorIfSaIfEEPNS9_5ScoreEbmmESC_SE_SI_SK_bmmEEvEESaIiEFvvEE14_M_run_delayedESt8weak_ptrINS_13_State_baseV2EEEUlvE_vEESt16_Sp_counted_baseILN9__gnu_cxx12_Lock_policyE2EENSt13__future_base13_State_baseV2ENSt13__future_base7_ResultIvEEN6xLearn4LossENSt13__future_base16_Task_state_baseIFvvEEESt19_Sp_make_shared_tagSt23_Sp_counted_ptr_inplaceISt13packaged_taskIFvvEESaIS2_ELN9__gnu_cxx12_Lock_policyE2EEZN10ThreadPool7enqueueISt5_BindIFPFvPKN6xLearn7DMatrixEPNS2_5ModelEPSt6vectorIfSaIfEEPNS2_5ScoreEbmmES5_S7_SB_SD_bmmEEJEEESt6futureINSt9result_ofIFT_DpT0_EE4typeEEOSK_DpOSL_EUlvE_NSt13__future_base11_Task_stateISt5_BindIFS1_IFPFvPKN6xLearn7DMatrixEPNS2_5ModelEPSt6vectorIfSaIfEEPNS2_5ScoreEbmmES5_S7_SB_SD_bmmEEvEESaIiEFvvEEESt23_Sp_counted_ptr_inplaceINSt13__future_base11_Task_stateISt5_BindIFS2_IFPFvPKN6xLearn7DMatrixEPNS3_5ModelEPSt6vectorIfSaIfEEPNS3_5ScoreEbmmES6_S8_SC_SE_bmmEEvEESaIiEFvvEEESL_LN9__gnu_cxx12_Lock_policyE2EE_/home/runner/work/ml-builds/ml-builds/xlearn/src/loss/squared_loss.ccstartlabel.empty()CalcGradsq_gradient_threadsq_evalute_threadEvaluteNSt13__future_base12_Task_setterISt10unique_ptrINS_7_ResultIvEENS_12_Result_base8_DeleterEEZNS_11_Task_stateISt5_BindIFS8_IFPFvPKN6xLearn7DMatrixEPNS9_5ModelEPNS9_5ScoreEbPfjjESC_SE_SG_bSH_mmEEvEESaIiEFvvEE6_M_runEvEUlvE_vEENSt13__future_base12_Task_setterISt10unique_ptrINS_7_ResultIvEENS_12_Result_base8_DeleterEEZNS_11_Task_stateISt5_BindIFS8_IFPFvPKN6xLearn7DMatrixEPNS9_5ModelEPNS9_5ScoreEbPfjjESC_SE_SG_bSH_mmEEvEESaIiEFvvEE14_M_run_delayedESt8weak_ptrINS_13_State_baseV2EEEUlvE_vEENSt13__future_base12_Task_setterISt10unique_ptrINS_7_ResultIvEENS_12_Result_base8_DeleterEEZNS_11_Task_stateISt5_BindIFS8_IFPFvPKSt6vectorIfSaIfEESD_PfmmESD_SD_SE_mmEEvEESaIiEFvvEE6_M_runEvEUlvE_vEENSt13__future_base12_Task_setterISt10unique_ptrINS_7_ResultIvEENS_12_Result_base8_DeleterEEZNS_11_Task_stateISt5_BindIFS8_IFPFvPKSt6vectorIfSaIfEESD_PfmmESD_SD_SE_mmEEvEESaIiEFvvEE14_M_run_delayedESt8weak_ptrINS_13_State_baseV2EEEUlvE_vEEN6xLearn11SquaredLossEZN10ThreadPool7enqueueISt5_BindIFPFvPKSt6vectorIfSaIfEES6_PfmmES6_S6_S7_mmEEJEEESt6futureINSt9result_ofIFT_DpT0_EE4typeEEOSE_DpOSF_EUlvE_ZN10ThreadPool7enqueueISt5_BindIFPFvPKN6xLearn7DMatrixEPNS2_5ModelEPNS2_5ScoreEbPfjjES5_S7_S9_bSA_mmEEJEEESt6futureINSt9result_ofIFT_DpT0_EE4typeEEOSH_DpOSI_EUlvE_NSt13__future_base11_Task_stateISt5_BindIFS1_IFPFvPKSt6vectorIfSaIfEES6_PfmmES6_S6_S7_mmEEvEESaIiEFvvEEENSt13__future_base11_Task_stateISt5_BindIFS1_IFPFvPKN6xLearn7DMatrixEPNS2_5ModelEPNS2_5ScoreEbPfjjES5_S7_S9_bSA_mmEEvEESaIiEFvvEEESt23_Sp_counted_ptr_inplaceINSt13__future_base11_Task_stateISt5_BindIFS2_IFPFvPKSt6vectorIfSaIfEES7_PfmmES7_S7_S8_mmEEvEESaIiEFvvEEESF_LN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt13__future_base11_Task_stateISt5_BindIFS2_IFPFvPKN6xLearn7DMatrixEPNS3_5ModelEPNS3_5ScoreEbPfjjES6_S8_SA_bSB_mmEEvEESaIiEFvvEEESI_LN9__gnu_cxx12_Lock_policyE2EE?/home/runner/work/ml-builds/ml-builds/xlearn/src/loss/cross_entropy_loss.ccce_gradient_threadCalcGradce_evalute_threadEvaluteNSt13__future_base12_Task_setterISt10unique_ptrINS_7_ResultIvEENS_12_Result_base8_DeleterEEZNS_11_Task_stateISt5_BindIFS8_IFPFvPKN6xLearn7DMatrixEPNS9_5ModelEPNS9_5ScoreEbPfmmESC_SE_SG_bSH_jjEEvEESaIiEFvvEE6_M_runEvEUlvE_vEENSt13__future_base12_Task_setterISt10unique_ptrINS_7_ResultIvEENS_12_Result_base8_DeleterEEZNS_11_Task_stateISt5_BindIFS8_IFPFvPKN6xLearn7DMatrixEPNS9_5ModelEPNS9_5ScoreEbPfmmESC_SE_SG_bSH_jjEEvEESaIiEFvvEE14_M_run_delayedESt8weak_ptrINS_13_State_baseV2EEEUlvE_vEEN6xLearn16CrossEntropyLossEZN10ThreadPool7enqueueISt5_BindIFPFvPKN6xLearn7DMatrixEPNS2_5ModelEPNS2_5ScoreEbPfmmES5_S7_S9_bSA_jjEEJEEESt6futureINSt9result_ofIFT_DpT0_EE4typeEEOSH_DpOSI_EUlvE_NSt13__future_base11_Task_stateISt5_BindIFS1_IFPFvPKN6xLearn7DMatrixEPNS2_5ModelEPNS2_5ScoreEbPfmmES5_S7_S9_bSA_jjEEvEESaIiEFvvEEESt23_Sp_counted_ptr_inplaceINSt13__future_base11_Task_stateISt5_BindIFS2_IFPFvPKN6xLearn7DMatrixEPNS3_5ModelEPNS3_5ScoreEbPfmmES6_S8_SA_bSB_jjEEvEESaIiEFvvEEESI_LN9__gnu_cxx12_Lock_policyE2EE/home/runner/work/ml-builds/ml-builds/xlearn/src/loss/metric.hpositive_vec.size()negative_vec.size()Y.size()accprecrecallf1maemapermsdaucauc_accum_threadAccumulateCalcAUCrmsd_accum_threadAccumulatemae_accum_threadAccumulatemae_accum_threadAccumulatef1_accum_threadAccumulaterecall_accum_threadAccumulateprec_accum_threadAccumulateacc_accum_threadAccumulateNSt13__future_base12_Task_setterISt10unique_ptrINS_7_ResultIvEENS_12_Result_base8_DeleterEEZNS_11_Task_stateISt5_BindIFS8_IFPFvPKSt6vectorIfSaIfEESD_PN6xLearn9AUCMetric4InfoEmmESD_SD_SH_mmEEvEESaIiEFvvEE6_M_runEvEUlvE_vEENSt13__future_base12_Task_setterISt10unique_ptrINS_7_ResultIvEENS_12_Result_base8_DeleterEEZNS_11_Task_stateISt5_BindIFS8_IFPFvPKSt6vectorIfSaIfEESD_PN6xLearn9AUCMetric4InfoEmmESD_SD_SH_mmEEvEESaIiEFvvEE14_M_run_delayedESt8weak_ptrINS_13_State_baseV2EEEUlvE_vEENSt13__future_base12_Task_setterISt10unique_ptrINS_7_ResultIvEENS_12_Result_base8_DeleterEEZNS_11_Task_stateISt5_BindIFS8_IFPFvPKSt6vectorIfSaIfEESD_PjSE_mmESD_SD_SE_SE_mmEEvEESaIiEFvvEE6_M_runEvEUlvE_vEENSt13__future_base12_Task_setterISt10unique_ptrINS_7_ResultIvEENS_12_Result_base8_DeleterEEZNS_11_Task_stateISt5_BindIFS8_IFPFvPKSt6vectorIfSaIfEESD_PjSE_mmESD_SD_SE_SE_mmEEvEESaIiEFvvEE14_M_run_delayedESt8weak_ptrINS_13_State_baseV2EEEUlvE_vEENSt13__future_base12_Task_setterISt10unique_ptrINS_7_ResultIvEENS_12_Result_base8_DeleterEEZNS_11_Task_stateISt5_BindIFS8_IFPFvPKSt6vectorIfSaIfEESD_PjmmESD_SD_SE_mmEEvEESaIiEFvvEE6_M_runEvEUlvE_vEENSt13__future_base12_Task_setterISt10unique_ptrINS_7_ResultIvEENS_12_Result_base8_DeleterEEZNS_11_Task_stateISt5_BindIFS8_IFPFvPKSt6vectorIfSaIfEESD_PjmmESD_SD_SE_mmEEvEESaIiEFvvEE14_M_run_delayedESt8weak_ptrINS_13_State_baseV2EEEUlvE_vEEN6xLearn6MetricEN6xLearn9AccMetricEN6xLearn10PrecMetricEN6xLearn12RecallMetricEN6xLearn8F1MetricEN6xLearn9AUCMetricEN6xLearn9MAEMetricEN6xLearn10MAPEMetricEN6xLearn10RMSDMetricEZN10ThreadPool7enqueueISt5_BindIFPFvPKSt6vectorIfSaIfEES6_PjmmES6_S6_S7_mmEEJEEESt6futureINSt9result_ofIFT_DpT0_EE4typeEEOSE_DpOSF_EUlvE_ZN10ThreadPool7enqueueISt5_BindIFPFvPKSt6vectorIfSaIfEES6_PjS7_mmES6_S6_S7_S7_mmEEJEEESt6futureINSt9result_ofIFT_DpT0_EE4typeEEOSE_DpOSF_EUlvE_ZN10ThreadPool7enqueueISt5_BindIFPFvPKSt6vectorIfSaIfEES6_PN6xLearn9AUCMetric4InfoEmmES6_S6_SA_mmEEJEEESt6futureINSt9result_ofIFT_DpT0_EE4typeEEOSH_DpOSI_EUlvE_NSt13__future_base11_Task_stateISt5_BindIFS1_IFPFvPKSt6vectorIfSaIfEES6_PjmmES6_S6_S7_mmEEvEESaIiEFvvEEENSt13__future_base11_Task_stateISt5_BindIFS1_IFPFvPKSt6vectorIfSaIfEES6_PjS7_mmES6_S6_S7_S7_mmEEvEESaIiEFvvEEENSt13__future_base11_Task_stateISt5_BindIFS1_IFPFvPKSt6vectorIfSaIfEES6_PN6xLearn9AUCMetric4InfoEmmES6_S6_SA_mmEEvEESaIiEFvvEEESt23_Sp_counted_ptr_inplaceINSt13__future_base11_Task_stateISt5_BindIFS2_IFPFvPKSt6vectorIfSaIfEES7_PjmmES7_S7_S8_mmEEvEESaIiEFvvEEESF_LN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt13__future_base11_Task_stateISt5_BindIFS2_IFPFvPKSt6vectorIfSaIfEES7_PjS8_mmES7_S7_S8_S8_mmEEvEESaIiEFvvEEESF_LN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt13__future_base11_Task_stateISt5_BindIFS2_IFPFvPKSt6vectorIfSaIfEES7_PN6xLearn9AUCMetric4InfoEmmES7_S7_SB_mmEEvEESaIiEFvvEEESI_LN9__gnu_cxx12_Lock_policyE2EE?;?@AQB?K$tIEncountered a too-long line. Please check the data./home/runner/work/ml-builds/ml-builds/xlearn/src/reader/parser.cclibsvmlibffmcsvParseParseAddNodeParseN6xLearn6ParserEN6xLearn12LibsvmParserEN6xLearn9FFMParserEN6xLearn9CSVParserEget_line_from_bu/reader/parser.c/home/runner/work/ml-builds/ml-builds/xlearn/src/reader/file_splitor.ccnum_blocksError: invoke fseek().Error: invoke ftell().%s_%dw+map_ptr_readMAP_FAILEDmap_ptr_writeOpenFileOrDieGetFileSizesplit/reader/file_splFail to return to the head of file.fgets(line.get(), kMaxLineSize, file)/home/runner/work/ml-builds/ml-builds/xlearn/src/base/scoped_ptr.hEncountered a too-long line: Cannot find the '\n' char. Please check the data./home/runner/work/ml-builds/ml-builds/xlearn/src/reader/reader.ccBinary file (%s.bin) found. Skip converting text to binary.Binary file (%s.bin) NOT found. Convert text file to binary file.Cannot set shuffle for OndiskReader.modestatic_cast<int>(f.tellg())i >= 0 ,File format error!.binFile: doesn't exists.!filename.empty()memorydmatrix!vec.empty()row.size()norm.size()InitializeWriteDataToDiskWriteVectorToFileWriteVectorToFileSerializeReadVectorFromFileReadVectorFromFileDeserializeHashFileReadDataFromDiskInitializeCloseC& scoped_array<C>::operator[](std::ptrdiff_t) const [with C = char; std::ptrdiff_t = long int]GetLineOpenFileOrDieN6xLearn6ReaderEN6xLearn11InmemReaderEN6xLearn12OndiskReaderEN6xLearn12FromDMReaderE/reader/reader.h/reader/reader.c ,,,,,,,,,,,,,,,,::::::::::::::::check_file_formaUnknow file formFirst check if the text file has been already converted to binarsgdadagradftrlUnknow optimization method: N6xLearn5ScoreEN6xLearn11LinearScoreE?/score/linear_scN6xLearn7FMScoreE/score/fm_score.N6xLearn8FFMScoreE@/score/ffm_score +Total time cost: %.2f (sec)[------------] Train set must have label!testvalidatetaskbinaryregmetricloglossoptepochfoldblock_sizestop_windowlrlambdainiton_disklock_freeearly_stopbin_outfrom_fileCHECK_GT failed = row_idXlearnDataFreeAddNode?Cannot create file: . create a new directory. +Cannot create file: () Please check that wether you need to basic_string::append/home/runner/work/ml-builds/ml-builds/xlearn/src/base/split_string.cc%s: __pos (which is %zu) > this->size() (which is %zu)delim != NULLresult != NULLbasic_string::substrSplitStringToSetUsingSplitStringUsing/home/runner/work/ml-builds/ml-builds/xlearn/src/base/levenshtein_distance.cc!source.empty()!target.empty()vector::_M_default_append!str.empty()!list.empty()ldistanceFindSimilarFindzD/home/runner/work/ml-builds/ml-builds/xlearn/src/base/file_util.h/home/runner/work/ml-builds/ml-builds/xlearn/src/data/model_parameters.ccCannot allocate enough memory for current model parameters. Parameter size: Cannot Load model from the file: %sbuflenError: invoke fwrite().Error: invoke fread().[ ERROR ] CHECK_EQ failed ret!score_func.empty()!loss_func.empty()num_featurescalelinearUnknow score function: CHECK_NE failed truebias: i_v_filenameCannot open file: with mode: file_ptrError: invoke fclose().SetBestModelReadDataFromDiskReadStringFromFileDeserializeWriteDataToDiskWriteStringToFileOpenFileOrDieSerializeModelinitialInitialize>0?????std::future_error: CHECK_GE failed end_idxstart_idxvector::_M_fill_insertenqueue on stopped ThreadPoolpred.empty()pred.size()matrix->row_lengthvector::reservesquaredcross-entropy/home/runner/work/ml-builds/ml-builds/xlearn/src/loss/loss.ccPredictpred_threadSt11_Mutex_baseILN9__gnu_cxx12_Lock_policyE2EENSt13__future_base12_Task_setterISt10unique_ptrINS_7_ResultIvEENS_12_Result_base8_DeleterEESt12_Bind_simpleIFSt17reference_wrapperISt5_BindIFS9_IFPFvPKN6xLearn7DMatrixEPNSA_5ModelEPSt6vectorIfSaIfEEPNSA_5ScoreEbmmESD_SF_SJ_SL_bmmEEvEEEvEEvEESt16_Sp_counted_baseILN9__gnu_cxx12_Lock_policyE2EENSt13__future_base13_State_baseV2ENSt13__future_base7_ResultIvEEN6xLearn4LossENSt13__future_base16_Task_state_baseIFvvEEESt19_Sp_make_shared_tagSt23_Sp_counted_ptr_inplaceISt13packaged_taskIFvvEESaIS2_ELN9__gnu_cxx12_Lock_policyE2EEZN10ThreadPool7enqueueISt5_BindIFPFvPKN6xLearn7DMatrixEPNS2_5ModelEPSt6vectorIfSaIfEEPNS2_5ScoreEbmmES5_S7_SB_SD_bmmEEJEEESt6futureINSt9result_ofIFT_DpT0_EE4typeEEOSK_DpOSL_EUlvE_NSt13__future_base11_Task_stateISt5_BindIFS1_IFPFvPKN6xLearn7DMatrixEPNS2_5ModelEPSt6vectorIfSaIfEEPNS2_5ScoreEbmmES5_S7_SB_SD_bmmEEvEESaIiEFvvEEESt23_Sp_counted_ptr_inplaceINSt13__future_base11_Task_stateISt5_BindIFS2_IFPFvPKN6xLearn7DMatrixEPNS3_5ModelEPSt6vectorIfSaIfEEPNS3_5ScoreEbmmES6_S8_SC_SE_bmmEEvEESaIiEFvvEEESL_LN9__gnu_cxx12_Lock_policyE2EE_/home/runner/work/ml-builds/ml-builds/xlearn/src/loss/squared_loss.ccstartlabel.empty()CalcGradsq_gradient_threadsq_evalute_threadEvaluteNSt13__future_base12_Task_setterISt10unique_ptrINS_7_ResultIvEENS_12_Result_base8_DeleterEESt12_Bind_simpleIFSt17reference_wrapperISt5_BindIFS9_IFPFvPKN6xLearn7DMatrixEPNSA_5ModelEPNSA_5ScoreEbPfjjESD_SF_SH_bSI_mmEEvEEEvEEvEENSt13__future_base12_Task_setterISt10unique_ptrINS_7_ResultIvEENS_12_Result_base8_DeleterEESt12_Bind_simpleIFSt17reference_wrapperISt5_BindIFS9_IFPFvPKSt6vectorIfSaIfEESE_PfmmESE_SE_SF_mmEEvEEEvEEvEEN6xLearn11SquaredLossEZN10ThreadPool7enqueueISt5_BindIFPFvPKSt6vectorIfSaIfEES6_PfmmES6_S6_S7_mmEEJEEESt6futureINSt9result_ofIFT_DpT0_EE4typeEEOSE_DpOSF_EUlvE_ZN10ThreadPool7enqueueISt5_BindIFPFvPKN6xLearn7DMatrixEPNS2_5ModelEPNS2_5ScoreEbPfjjES5_S7_S9_bSA_mmEEJEEESt6futureINSt9result_ofIFT_DpT0_EE4typeEEOSH_DpOSI_EUlvE_NSt13__future_base11_Task_stateISt5_BindIFS1_IFPFvPKSt6vectorIfSaIfEES6_PfmmES6_S6_S7_mmEEvEESaIiEFvvEEENSt13__future_base11_Task_stateISt5_BindIFS1_IFPFvPKN6xLearn7DMatrixEPNS2_5ModelEPNS2_5ScoreEbPfjjES5_S7_S9_bSA_mmEEvEESaIiEFvvEEESt23_Sp_counted_ptr_inplaceINSt13__future_base11_Task_stateISt5_BindIFS2_IFPFvPKSt6vectorIfSaIfEES7_PfmmES7_S7_S8_mmEEvEESaIiEFvvEEESF_LN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt13__future_base11_Task_stateISt5_BindIFS2_IFPFvPKN6xLearn7DMatrixEPNS3_5ModelEPNS3_5ScoreEbPfjjES6_S8_SA_bSB_mmEEvEESaIiEFvvEEESI_LN9__gnu_cxx12_Lock_policyE2EE?/home/runner/work/ml-builds/ml-builds/xlearn/src/loss/cross_entropy_loss.ccce_gradient_threadCalcGradce_evalute_threadEvaluteNSt13__future_base12_Task_setterISt10unique_ptrINS_7_ResultIvEENS_12_Result_base8_DeleterEESt12_Bind_simpleIFSt17reference_wrapperISt5_BindIFS9_IFPFvPKN6xLearn7DMatrixEPNSA_5ModelEPNSA_5ScoreEbPfmmESD_SF_SH_bSI_jjEEvEEEvEEvEEN6xLearn16CrossEntropyLossEZN10ThreadPool7enqueueISt5_BindIFPFvPKN6xLearn7DMatrixEPNS2_5ModelEPNS2_5ScoreEbPfmmES5_S7_S9_bSA_jjEEJEEESt6futureINSt9result_ofIFT_DpT0_EE4typeEEOSH_DpOSI_EUlvE_NSt13__future_base11_Task_stateISt5_BindIFS1_IFPFvPKN6xLearn7DMatrixEPNS2_5ModelEPNS2_5ScoreEbPfmmES5_S7_S9_bSA_jjEEvEESaIiEFvvEEESt23_Sp_counted_ptr_inplaceINSt13__future_base11_Task_stateISt5_BindIFS2_IFPFvPKN6xLearn7DMatrixEPNS3_5ModelEPNS3_5ScoreEbPfmmES6_S8_SA_bSB_jjEEvEESaIiEFvvEEESI_LN9__gnu_cxx12_Lock_policyE2EEpositive_vec.size()negative_vec.size()Y.size()accprecrecallf1maemapermsdauc/home/runner/work/ml-builds/ml-builds/xlearn/src/loss/metric.hauc_accum_threadAccumulateCalcAUCrmsd_accum_threadAccumulatemae_accum_threadAccumulatemae_accum_threadAccumulatef1_accum_threadAccumulaterecall_accum_threadAccumulateprec_accum_threadAccumulateacc_accum_threadAccumulateNSt13__future_base12_Task_setterISt10unique_ptrINS_7_ResultIvEENS_12_Result_base8_DeleterEESt12_Bind_simpleIFSt17reference_wrapperISt5_BindIFS9_IFPFvPKSt6vectorIfSaIfEESE_PN6xLearn9AUCMetric4InfoEmmESE_SE_SI_mmEEvEEEvEEvEENSt13__future_base12_Task_setterISt10unique_ptrINS_7_ResultIvEENS_12_Result_base8_DeleterEESt12_Bind_simpleIFSt17reference_wrapperISt5_BindIFS9_IFPFvPKSt6vectorIfSaIfEESE_PjSF_mmESE_SE_SF_SF_mmEEvEEEvEEvEENSt13__future_base12_Task_setterISt10unique_ptrINS_7_ResultIvEENS_12_Result_base8_DeleterEESt12_Bind_simpleIFSt17reference_wrapperISt5_BindIFS9_IFPFvPKSt6vectorIfSaIfEESE_PjmmESE_SE_SF_mmEEvEEEvEEvEEN6xLearn6MetricEN6xLearn9AccMetricEN6xLearn10PrecMetricEN6xLearn12RecallMetricEN6xLearn8F1MetricEN6xLearn9AUCMetricEN6xLearn9MAEMetricEN6xLearn10MAPEMetricEN6xLearn10RMSDMetricEZN10ThreadPool7enqueueISt5_BindIFPFvPKSt6vectorIfSaIfEES6_PjmmES6_S6_S7_mmEEJEEESt6futureINSt9result_ofIFT_DpT0_EE4typeEEOSE_DpOSF_EUlvE_ZN10ThreadPool7enqueueISt5_BindIFPFvPKSt6vectorIfSaIfEES6_PjS7_mmES6_S6_S7_S7_mmEEJEEESt6futureINSt9result_ofIFT_DpT0_EE4typeEEOSE_DpOSF_EUlvE_ZN10ThreadPool7enqueueISt5_BindIFPFvPKSt6vectorIfSaIfEES6_PN6xLearn9AUCMetric4InfoEmmES6_S6_SA_mmEEJEEESt6futureINSt9result_ofIFT_DpT0_EE4typeEEOSH_DpOSI_EUlvE_NSt13__future_base11_Task_stateISt5_BindIFS1_IFPFvPKSt6vectorIfSaIfEES6_PjmmES6_S6_S7_mmEEvEESaIiEFvvEEENSt13__future_base11_Task_stateISt5_BindIFS1_IFPFvPKSt6vectorIfSaIfEES6_PjS7_mmES6_S6_S7_S7_mmEEvEESaIiEFvvEEENSt13__future_base11_Task_stateISt5_BindIFS1_IFPFvPKSt6vectorIfSaIfEES6_PN6xLearn9AUCMetric4InfoEmmES6_S6_SA_mmEEvEESaIiEFvvEEESt23_Sp_counted_ptr_inplaceINSt13__future_base11_Task_stateISt5_BindIFS2_IFPFvPKSt6vectorIfSaIfEES7_PjmmES7_S7_S8_mmEEvEESaIiEFvvEEESF_LN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt13__future_base11_Task_stateISt5_BindIFS2_IFPFvPKSt6vectorIfSaIfEES7_PjS8_mmES7_S7_S8_S8_mmEEvEESaIiEFvvEEESF_LN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt13__future_base11_Task_stateISt5_BindIFS2_IFPFvPKSt6vectorIfSaIfEES7_PN6xLearn9AUCMetric4InfoEmmES7_S7_SB_mmEEvEESaIiEFvvEEESI_LN9__gnu_cxx12_Lock_policyE2EE;?@AQB?K$tI?Encountered a too-long line. Please check the data./home/runner/work/ml-builds/ml-builds/xlearn/src/reader/parser.cclibsvmlibffmcsvParseParseAddNodeParseN6xLearn6ParserEN6xLearn12LibsvmParserEN6xLearn9FFMParserEN6xLearn9CSVParserE/home/runner/work/ml-builds/ml-builds/xlearn/src/reader/file_splitor.ccnum_blocksError: invoke fseek().Error: invoke ftell().%s_%dw+map_ptr_readMAP_FAILEDmap_ptr_writeOpenFileOrDieGetFileSizesplitCannot set shuffle for OndiskReader.Fail to return to the head of file.fgets(line.get(), kMaxLineSize, file)/home/runner/work/ml-builds/ml-builds/xlearn/src/base/scoped_ptr.hEncountered a too-long line: Cannot find the '\n' char. Please check the data./home/runner/work/ml-builds/ml-builds/xlearn/src/reader/reader.ccBinary file (%s.bin) found. Skip converting text to binary.Binary file (%s.bin) NOT found. Convert text file to binary file.modestatic_cast<int>(f.tellg())i >= 0 ,File format error!Unknow file format.binFile: doesn't exists.!vec.empty()row.size()norm.size()!filename.empty()memorydmatrixInitializeWriteDataToDiskWriteVectorToFileWriteVectorToFileSerializeReadVectorFromFileReadVectorFromFileDeserializeHashFileReadDataFromDiskInitializeCloseC& scoped_array<C>::operator[](std::ptrdiff_t) const [with C = char; std::ptrdiff_t = long int]GetLineOpenFileOrDieN6xLearn6ReaderEN6xLearn11InmemReaderEN6xLearn12OndiskReaderEN6xLearn12FromDMReaderE::::::::::::::::sgdadagradftrlUnknow optimization method: N6xLearn5ScoreEN6xLearn11LinearScoreE?N6xLearn7FMScoreEN6xLearn8FFMScoreE@[ WARNING ] nonermseunknow.modelUnknow evaluation metric: %s..out-s-x-p-v-m-t-l-k-r-b-u-e-f-pre-nthread-block-sw-seed--disk--cv--dis-lock-free--dis-es--no-norm--no-bin--quiet-alpha-beta-lambda_1-lambda_2-o--sign--sigmoid ---------------------------------------- Training task ------------------------------------- USAGE: xlearn_train <train_file_path> [OPTIONS] e.g., xlearn_train train_data.txt -s 0 -v validate_data.txt -r 0.1 @@ -583,19 +499,19 @@ --disk : On-disk prediction. --no-norm : Disable instance-wise normalization. By default, xLearn will use instance-wise normalization for both training and prediction. -----------------------------------------------------------------------------------------------The --cv (cross-validation) has been set, and xLearn will ignore the validation file: %sValidation file not found, xLearn has already disable (-x %s) option.The -x: %s metric can only be used in classification tasks. xLearn will ignore this option.The -x: %s metric can only be used in regression tasks. xLearn will ignore this option.Training data file: %s does not exist.Validation data file: %s does not exist.Training dataset is None, please check!The thread number must be greater than zero: %d.The task can only be 'binary' or 'reg'.Unknow optimization method: %s.Invalid size of K: %d. Size of K must be greater than zero.Invalid size of folds: %d. Size of folds must be greater than zero.Invalid number of epoch: %d. Number of epoch must be greater than zero.Test set file: %s does not exist.Test dataset is None, please check!Model file: %s does not exist.-s can only be [0 - 5] : +----------------------------------------------------------------------------------------------The --cv (cross-validation) has been set, and xLearn will ignore the validation file: %sValidation file not found, xLearn has already disable (-x %s) option.The -x: %s metric can only be used in classification tasks. xLearn will ignore this option.The -x: %s metric can only be used in regression tasks. xLearn will ignore this option.Training data file: %s does not exist.Validation data file: %s does not exist.Training dataset is None, please check!The thread number must be greater than zero: %d.The task can only be 'binary' or 'reg'.Invalid size of K: %d. Size of K must be greater than zero.Invalid size of folds: %d. Size of folds must be greater than zero.Invalid number of epoch: %d. Number of epoch must be greater than zero.Unknow optimization method: %s.Test set file: %s does not exist.Test dataset is None, please check!Model file: %s does not exist.-s can only be [0 - 5] : for classification task: 0 -- linear model (GLM) 1 -- factorization machines (FM) 2 -- field-aware factorization machines (FFM) for regression task: 3 -- linear model (GLM) 4 -- factorization machines (FM) - 5 -- field-aware factorization machines (FFM)Unknow metric: %s + 5 -- field-aware factorization machines (FFM)Validation set file: %s dose not exists.Illegal -k '%i'. -k must be geater than zero.Illegal -r : '%f'. -r must be greater than zero.Illegal -b : '%f' -b must be greater than or equal to zero.Illegal -u : '%f'. -u must be greater than zero.Illegal -e : '%i'. -e must be greater than zero.Illegal -f : '%i'. -f must be greater than zero.Illegal -nthread : '%i'. -nthread must be greater than zero.Illegal -block : '%i'. -block must be greater than zero.Illegal -sw : '%i'. -sw must be greater than or equal to 1.Illegal -seed : '%i'. -seed must be greater than or equal to 1.Illegal -alpha : '%f'. -alpha must be greater than zero.Illegal -beta : '%f'. -beta cannot be less than zero.Illegal -lambda_1 : '%f'. -lambda_1 cannot be less than zero.Illegal -lambda_2 : '%f'. -lambda_2 cannot be less than zero.Unknow argument '%s'. Do you mean '%s' ?Unknow metric: %s -x can only be: acc prec recall f1 @@ -604,527 +520,530 @@ mape rmsd rmse noneUnknow optimization method: %s -o can only be: adagrad and ftrl. -Validation set file: %s dose not exists.Illegal -k '%i'. -k must be geater than zero.Illegal -r : '%f'. -r must be greater than zero.Illegal -b : '%f' -b must be greater than or equal to zero.Illegal -u : '%f'. -u must be greater than zero.Illegal -e : '%i'. -e must be greater than zero.Illegal -f : '%i'. -f must be greater than zero.Illegal -nthread : '%i'. -nthread must be greater than zero.Illegal -block : '%i'. -block must be greater than zero.Illegal -sw : '%i'. -sw must be greater than or equal to 1.Illegal -seed : '%i'. -seed must be greater than or equal to 1.Illegal -alpha : '%f'. -alpha must be greater than zero.Illegal -beta : '%f'. -beta cannot be less than zero.Illegal -lambda_1 : '%f'. -lambda_1 cannot be less than zero.Illegal -lambda_2 : '%f'. -lambda_2 cannot be less than zero.Unknow argument '%s'. Do you mean '%s' ?[ WARNING ] nonermseunknowUnknow evaluation metric: %s..model.out-s-x-p-v-m-t-l-k-r-b-u-e-f-pre-nthread-block-sw-seed--disk--cv--dis-lock-free--dis-es--no-norm--no-bin--quiet-alpha-beta-lambda_1-lambda_2-o--sign--sigmoidvvHvvuvTransform DMatrix not from file doesn't support cross-validation. xLearn has already disable theOn-disk training doesn't support cross-validation. xLearn has already disable thCross-validation early-stopping. xLearn has already close early-The --cv (cross-validation) has been set, and xLearn will ignore the --quiet optearn will not dump model checkpoValidation file(dataset) not found, xLearn has already disable eBoth of --sign and --sigmoid have been set. xLearn has already disable --sign anThe test file and model file musAverage %s: %.6freader.empty()Train Test [------------]%.2f[ % ]reader_list.empty()AccuarcyPrecisionRecallF1AUCMAEMAPERMSD[ ACTION ] Cross-validation: %d/%lu:/home/runner/work/ml-builds/ml-builds/xlearn/src/solver/trainer.ccEarly-stopping at epoch %d, best %s: %f/home/runner/work/ml-builds/ml-builds/xlearn/src/base/format_print.hcolumn.size()width.size()calc_metriccalc_gradientprint_rowY@/home/runner/work/ml-builds/ml-builds/xlearn/src/solver/inference.ccin.size()out.size()vector::_M_range_insertThe test loss is: %.6fsignsigmoid/home/runner/work/ml-builds/ml-builds/xlearn/src/base/system.hlocaltime_r(&current_time, &broken_down_time) == &broken_down_timeTime cost for saving model: %.2f (sec)Time cost for saving txt model: %.2f (sec)/home/runner/work/ml-builds/ml-builds/xlearn/src/solver/inference.hClear the xLearn environment ...xLearn uses %i threads for training task./home/runner/work/ml-builds/ml-builds/xlearn/src/solver/solver.cchyper_param_.train_set_file.empty()Cannot open initialze dataset %dFeature index is too large (overflow).Time cost for reading problem: %.2f (sec)Time cost for model initial: %.2f (sec)/home/runner/work/ml-builds/ml-builds/xlearn/src/loss/loss.hxLearn uses %i threads for prediction task.hyper_param_.model_file.empty()Time cost for loading model: %.2f (sec)hyper_param_.test_set_file.empty()USERUSERNAME%04d%02d%02d-%02d%02d%02d!file_base.empty()%s.%s.%s.%s.%uCannot create reader: Cannot create score: Cannot create loss: _train%s.ERROR_predict%s.WARN%s.INFOfilename.compare("none")TXT Model file: %sreaderout.empty()Start training work.Start inference work.Start to init Readerhyper_param_.num_foldsSplit file into parts.Number of Reader: Cannot open the file %sInit Reader: hyper_param_.train_datasetNumber of feature: Number of Feature: %dNumber of field: Number of Field: %dNumber parameters: %.2f GB%.2f MB%.2f KBModel size: %sInitialize score function.scorepoolInitialize loss function.Initialize evaluation metric.Load model from %sLoss function: %sScore function: %sNumber of K: %dNumber of field: %dInitialize model.hyper_param_.test_datasetInitialize Reader: /home/runner/work/ml-builds/ml-builds/xlearn/src/reader/reader.h/home/runner/work/ml-builds/ml-builds/xlearn/src/solver/trainer.hInitializeSaveTxtModelSaveModelInitializeinit_predictInitializeInitializeSetBlockSizeinit_trainget_log_fileprint_current_timeNSt6thread11_State_implINS_8_InvokerISt5tupleIJZN10ThreadPoolC4EmEUlvE_EEEEEE/solver/solver.cStart to train .Finish Cross-ValStart to save moStart to save txStart to predictClear the xLearn environment ...Read Problem ...Feature index is too large (overInitialize model>>P?;W jHjk6lplXmL2@n9n(YoHrIpxrdphvqdHqqXrXrr$r@sD#Hs/ht@8t0=tSwX8yYhyhfzf{`i|j(}lX}n}0r}Pv}w~((ȉdh4\HH<Hp8xP((<hPdX`txLHt lx8`8hhX @8Xd ( (&!&$!.x!2!3!3"(Ed"Q"Hc"xglpT$ql$Hq'q't\(u .X|/8`#Ht#X#h#####$$(,$h@$$$ȃ$؃$$($h%(%D%x%%X%%&hL&&&8 '8'8\'((H(((H)xT))T***+HX+X++,,-h-x-8`.h..H</x|22H67X 0h40xH0\0p00H000000101XP1X1X1H1882h3H3H\3x33h4$4P4|44445\555846xP6H6hH7879 -:X;<hX8xl88888(888x9x89xl9T::!:!:H";"4;H#X;h$;&8<h)<0@@0X@1p@81@h1@1@1@1XF4Gx58L6H=6\=6p=6=6=6=7=87=H7=X7=h7>7$>78>7L>7`>7t>8>8>(8>88>X8>h8>x8?8?8(?8<?8P?8d?8x?8?9?9?(9?h9?9?9@(:@h:,@:@:@:A:$A:8A:LA;`A;tAX;Ah;Ax;A;A;A;A; B;,B8<LBx<lBh=BX>BH?,C8@lC(ACBCHBDBDHDLDDhDD|DDDFDHGEHPE8JEKELEHLEhLELFLFL0FMDF8MFOLG8RGTGV$HHYlH[H]H(`DIcIXgIgJXh<JhhJXiJiJXjJjKXk4KkXKlKnK8oLhoLqLs0Mu|Mh|MXHNtN8N(pOȈO8PdPPء Qȩ`QQ(RX\RR(SXSS8Tx,TThUxpUVVHWSDTXTHtTxTTTUH(V8tVWX XXY&TZ&hZ8(ZX)l[H*]+t],]H.^/_1`GT`N`O`OaS cptctpddXYhYxYZZ,Z@ZȌZX[(,[ȎL[[8[ؐ[[8 \h \Ȓl\(\]X ^d^x^_L_X\a(aa0b|bHbch8dXeefhfffX8ghfxghghHh8 iiXij($jjiii4kkkXHl -lx j j m8mm$nH)tn+\m+pm(,n, oxAhoVoYodPpdppDqhqndpXtq8rrs0t8u8puxuxu0sXxsttvv,wxxHXxX<y8xy8yh zDzHtzz{HP{{h{h|L|||}#~RTqHrtwtwuwhxxhzx{xh\}}h,~x~~zRx $FFJ w?;*3$"DhY\PpL,8YBAA D0 AABzPLRx  4$HmKnBCA D` - 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