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P?>>NSt3__117bad_function_callE---------------------------------------------------------------------------------------------- _ | | __ _| | ___ __ _ _ __ _ __ \ \/ / | / _ \/ _` | '__| '_ \ > <| |___| __/ (_| | | | | | | /_/\_\_____/\___|\__,_|_| |_| |_| xLearn -- 0.43 Version -- ---------------------------------------------------------------------------------------------- /Users/runner/runners/2.164.0/work/ml-builds/ml-builds/xlearn/src/c_api/c_api.ccXlearnDataFreeCHECK failed : out == NULL Info: Model: %s Loss: %s Input for validation type Must equal to train's!Total time cost: %.2f (sec)trainTrain set must have label!testvalidatetaskbinarycross-entropyregsquaredunknowmetricloglossoptkepochfoldblock_sizenthreadstop_windowseedlrlambdainitalphabetalambda_1lambda_2on_diskquietnormlock_freeearly_stopsignsigmoidbin_outfrom_filelinearadagrad/tmp/xlearn_logallocator::allocate(size_t n) 'n' exceeds maximum supported size/Users/runner/runners/2.164.0/work/ml-builds/ml-builds/xlearn/src/data/data_structure.hAddNodeCHECK_GT failed row_length = row_id[------------] Cannot create file: . Please check that wether you need to create a new directory. Cannot create file: () w/Users/runner/runners/2.164.0/work/ml-builds/ml-builds/xlearn/src/base/split_string.ccSplitStringUsingdelim != NULLresult != NULLSplitStringToSetUsing/Users/runner/runners/2.164.0/work/ml-builds/ml-builds/xlearn/src/base/levenshtein_distance.cc!str.empty()!list.empty()FindSimilarldistance!source.empty()!target.empty()/Users/runner/runners/2.164.0/work/ml-builds/ml-builds/xlearn/src/data/model_parameters.ccInitialize!score_func.empty()!loss_func.empty()num_feature0scalefmffmUnknow score function: initialCHECK_EQ failed retCannot allocate enough memory for current model parameters. Parameter size: ModelCHECK_NE failed filename.empty()trueCannot Load model from the file: %sSerializeSerializeToTXTbias: i_: v__DeserializerSetBestModel[ ERROR ] /Users/runner/runners/2.164.0/work/ml-builds/ml-builds/xlearn/src/base/file_util.hOpenFileOrDiefilenamemodeCannot open file: with mode: WriteStringToFilefile_ptrWriteDataToDiskfilebuflenError: invoke fwrite().CloseError: invoke fclose().ReadStringFromFileReadDataFromDiskError: invoke fread()./Users/runner/runners/2.164.0/work/ml-builds/ml-builds/xlearn/src/loss/loss.ccpred_threadCHECK_GE failed end_idxstart_idxPredictmatrixpred.empty()pred.size()matrix->row_lengthenqueue on stopped ThreadPool/Users/runner/runners/2.164.0/work/ml-builds/ml-builds/xlearn/src/loss/squared_loss.ccEvalutelabel.empty()sq_gradient_threadendstartsq_evalute_thread/Users/runner/runners/2.164.0/work/ml-builds/ml-builds/xlearn/src/loss/cross_entropy_loss.ccce_evalute_threadce_gradient_threadaccrecallmaeauc/Users/runner/runners/2.164.0/work/ml-builds/ml-builds/xlearn/src/loss/metric.hAccumulateY.size()acc_accum_threadprec_accum_threadPrecisionrecall_accum_threadRecallf1_accum_threadmae_accum_threadMAErmsd_accum_threadauc_accum_threadCalcAUCpositive_vec.size()negative_vec.size()AUClibsvmlibffmcsv/Users/runner/runners/2.164.0/work/ml-builds/ml-builds/xlearn/src/reader/parser.ccget_line_from_bufferEncountered a too-long line. Please check the data.Parsesize/Users/runner/runners/2.164.0/work/ml-builds/ml-builds/xlearn/src/reader/file_splitor.ccsplitnum_blocks2%s_%dw+map_ptr_readMAP_FAILEDmap_ptr_writeGetFileSizeError: invoke fseek().Error: invoke ftell().memorydmatrix ,/Users/runner/runners/2.164.0/work/ml-builds/ml-builds/xlearn/src/reader/reader.cccheck_file_formatFile format error!Unknow file formatFirst check if the text file has been already converted to binary format.Binary file (%s.bin) found. Skip converting text to binary..binBinary file (%s.bin) NOT found. Convert text file to binary file.ResetFail to return to the head of file.GetLinefgets(line.get(), kMaxLineSize, file)Encountered a too-long line: Cannot find the '\n' char. Please check the data.operator[]/Users/runner/runners/2.164.0/work/ml-builds/ml-builds/xlearn/src/base/scoped_ptr.hi >= 0FileExistFile: doesn't exists.static_cast(f.tellg())rb!filename.empty()ReadVectorFromFilerow.size()norm.size()WriteVectorToFile!vec.empty()in-memoryon-disk/Users/runner/runners/2.164.0/work/ml-builds/ml-builds/xlearn/src/reader/reader.hSetShuffleCannot set shuffle for OndiskReader.from-dmatrixsgdftrl/Users/runner/runners/2.164.0/work/ml-builds/ml-builds/xlearn/src/score/linear_score.ccUnknow optimization method: /Users/runner/runners/2.164.0/work/ml-builds/ml-builds/xlearn/src/score/fm_score.cc/Users/runner/runners/2.164.0/work/ml-builds/ml-builds/xlearn/src/score/ffm_score.cc ---------------------------------------- Training task ------------------------------------- USAGE: xlearn_train [OPTIONS] e.g., xlearn_train train_data.txt -s 0 -v validate_data.txt -r 0.1 OPTIONS: -s : Type of machine learning model (default 0) 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) -x : The metric can be 'acc', 'prec', 'recall', 'f1', 'auc' (classification), and 'mae', 'mape', 'rmsd (rmse)' (regression). On defaurt, xLearn will not print any evaluation metric information. -p : Choose the optimization method, including 'sgd', adagrad', and 'ftrl'. On default, we use the adagrad optimization. -v : Path of the validation data file. This option will be empty by default, and in this way, the xLearn will not perform validation. -m : Path of the model checkpoint file. On default, the model file name will be. set to 'train_file' + '.model'. If we set this value to 'none', the xLearn will not dump the model checkpoint after training. -pre : Path of the pre-trained model. This can be used for online learning. -t : Path of the txt model checkpoint file. On default, this option is empty and xLearn will not dump the txt model. -l : Path of the log file. Using '/tmp/xlearn_log/' by default. -k : Number of the latent factor used by fm and ffm tasks. Using 4 by default. Note that, we will get the same model size when setting k to 1 and 4. This is because we use SSE instruction and the memory need to be aligned. So even you assign k = 1, we still fill some dummy zeros from k = 2 to 4. -r : Learning rate for stochastic gradient descent. Using 0.2 by default. xLearn uses adaptive gradient descent (AdaGrad) for optimization problem, and the learning rate will be changed adaptively. -b : Lambda for L2 regular. Using 0.00002 by default. We can disable the regular term by setting this value to 0.0 -alpha : Used by ftrl. -beta : Used by ftrl. -lambda_1 : Used by ftrl. -lambda_2 : Used by ftrl. -u : Hyper parameter used for initialize model parameters. Using 0.66 by default. -e : Number of epoch for training. Using 10 by default. Note that, xLearn will perform early-stopping by default, so this value is just a upper bound. -f : Number of folds for cross-validation. Using 5 by default. -nthread : Number of thread for multi-thread training. -block : Block size fot on-disk training. -sw : Size of stop window for early-stopping. Using 2 by default. -seed : Random Seed to shuffle data set. --disk : Open on-disk training for large-scale machine learning problems. --cv : Open cross-validation in training tasks. If we use this option, xLearn will ignore the validation file (-t). --dis-lock-free : Disable lock-free training. Lock-free training can accelerate training but the result is non-deterministic. Our suggestion is that you can open this flag if the training data is big and sparse. --dis-es : Disable early-stopping in training. By default, xLearn will use early-stopping in training tasks, except for training in cross-validation. --no-norm : Disable instance-wise normalization. By default, xLearn will use instance-wise normalization for both training and prediction. --no-bin : Do not generate bin file for training and test data file. --quiet : Don't print any evaluation information during the training and just train the model quietly. ---------------------------------------------------------------------------------------------- -------------------------------------- Prediction task --------------------------------------- USAGE: xlearn_predict [OPTIONS] e.g., xlearn_predict ./test_data.txt ./model_file -o ./out.txt OPTIONS: -o : Path of the output file. On default, this value will be set to 'test_file' + '.out' -nthread : Number of thread for multi-thread learning. -l : Path of the log file. Using '/tmp/xlearn_log' by default. -block : Block size fot on-disk prediction. --sign : Converting output to 0 and 1. --sigmoid : Converting output to 0~1 (problebility). --disk : On-disk prediction. --no-norm : Disable instance-wise normalization. By default, xLearn will use instance-wise normalization for both training and prediction. -----------------------------------------------------------------------------------------------s-x-v-p-m-t-l-k-r-b-u-e-f-pre-nthread-block-sw-seed--disk--cv--dis-es--no-norm--no-bin--quiet-alpha-beta-lambda_1-lambda_2-o--sign--sigmoidTraining data 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)precf1mapermsdrmsenoneUnknow metric: %s -x can only be: acc prec recall f1 auc mae 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.--dis-lock-freeIllegal -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' ?.modelValidation 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 evaluation metric: %s.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.Transform DMatrix not from file doesn't support cross-validation. xLearn has already disable the -cv option.On-disk training doesn't support cross-validation. xLearn has already disable the -cv option.Cross-validation doesn't support early-stopping. xLearn has already close early-stopping.The --cv (cross-validation) has been set, and xLearn will ignore the validation file: %sThe --cv (cross-validation) has been set, and xLearn will ignore the --quiet option.The --cv (cross-validation) has been set, and xLearn will not dump model checkpoint to disk.Validation file(dataset) not found, xLearn has already disable early-stopping.Validation 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.The test file and model file must be set.Test set file: %s does not exist.Model file: %s does not exist..outTest dataset is None, please check!Both of --sign and --sigmoid have been set. xLearn has already disable --sign and --sigmoid.[ WARNING ] EpochTrain Test Time cost (sec)[------------]%d%.6f%.2f[ % ]Cross-validation: %d/%lu:Average %s: %.6fAccuarcyF1MAPERMSDEarly-stopping at epoch %d, best %s: %f/Users/runner/runners/2.164.0/work/ml-builds/ml-builds/xlearn/src/solver/trainer.cccalc_gradientreader.empty()calc_metricreader_list.empty()[ ACTION ] /Users/runner/runners/2.164.0/work/ml-builds/ml-builds/xlearn/src/base/format_print.hprint_rowcolumn.size()width.size()The test loss is: %.6f/Users/runner/runners/2.164.0/work/ml-builds/ml-builds/xlearn/src/solver/inference.ccin.size()out.size()ar+a+wbabr+bw+ba+bUSERUSERNAME/Users/runner/runners/2.164.0/work/ml-builds/ml-builds/xlearn/src/base/system.hprint_current_timelocaltime_r(¤t_time, &broken_down_time) == &broken_down_time%04d%02d%02d-%02d%02d%02dget_log_file!file_base.empty()%s.%s.%s.%s.%udisk/Users/runner/runners/2.164.0/work/ml-builds/ml-builds/xlearn/src/solver/solver.cccreate_readerCannot create reader: create_scoreCannot create score: create_lossCannot create loss: Arguments error_train_predict%s.INFO%s.WARN%s.ERRORxLearn uses %i threads for training task.Read Problem ...init_trainStart to init Readerhyper_param_.num_foldsSplit file into parts.hyper_param_.train_set_file.empty()Number of Reader: Cannot open the file %sInit Reader: hyper_param_.train_datasetCannot open initialze dataset %dFeature index is too large (overflow).Number of feature: Number of Feature: %dNumber of field: Number of Field: %dTime cost for reading problem: %.2f (sec)Initialize model ...Number parameters: Model size: %sTime cost for model initial: %.2f (sec)Initialize score function.Initialize loss function.Initialize evaluation metric.xLearn uses %i threads for prediction task.Load model ...init_predicthyper_param_.model_file.empty()Load model from %sLoss function: %sScore function: %sNumber of K: %dNumber of field: %dTime cost for loading model: %.2f (sec)Initialize model.hyper_param_.test_set_file.empty()hyper_param_.test_datasetInitialize Reader: StartWorkStart training work.Start inference work.Start to train ...Finish Cross-ValidationStart to save model ...Model file: %sTime cost for saving model: %.2f (sec)Start to save txt model ...TXT Model file: %sTime cost for saving txt model: %.2f (sec)Finish trainingStart to predict ...ClearClear the xLearn environment ...thread constructor failedSetBlockSize%.2f GB%.2f MB%.2f KB/Users/runner/runners/2.164.0/work/ml-builds/ml-builds/xlearn/src/loss/loss.hscorepool/Users/runner/runners/2.164.0/work/ml-builds/ml-builds/xlearn/src/solver/trainer.hmodelSaveModelfilename.compare("none")SaveTxtModel/Users/runner/runners/2.164.0/work/ml-builds/ml-builds/xlearn/src/solver/inference.hreaderout.empty() HLXQ!Q!aQX QQa R"\d2\" 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