java.lang.NullPointerException

JIRA | Eric Eckstrand | 2 years ago
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  1. 0

    Here are some NPEs achieved by glm random attack test. pros = h2o.upload_file(h2o.locate("smalldata/prostate/prostate.csv.zip")) pros[1] = pros[1].asfactor() r = pros[0].runif() # ~80/20 train/validation split pros_train = pros[r > .2] pros_valid = pros[r <= .2] cars = h2o.upload_file(h2o.locate("smalldata/junit/cars.csv")) r = cars[0].runif() cars_train = cars[r > .2] cars_valid = cars[r <= .2] # Binomial and gamma use prostate (CAPSULE/DPROS respectively) # Gaussian and poisson use cars (mpg/Cylinders respectively) The common thread seems to be beta constraints w/ LBFGS x: [6, 3, 4, 5, 2, 8] y: 1 validation: True standardize: False family: binomial solver: L_BFGS prior: 0.661566011292 beta_constraints: Displaying 6 row(s): Row ID names lower_bounds upper_bounds -------- ------------ --------------------- ---------------------- 1 [u'PSA'] [0.08442861247981925] [0.12694071519057182] 2 [u'RACE'] [-0.5780290588548885] [-0.13810131302030548] 3 [u'DPROS'] [0.76852832394281] [1.3496105569956252] 4 [u'DCAPS'] [-0.9016507404584659] [-0.32401365663844667] 5 [u'AGE'] [0.5855928861219879] [1.1951827824495105] 6 [u'GLEASON'] [0.5811227135549313] [0.6066065068362181] lambda_search: True max_iterations: 29 URI: /3/ModelBuilders/glm, route: /3/ModelBuilders/glm, parms: {validation_frame=py23e6ca95-9a67-4208-94d3-0ec7b71ccb6d, response_column=CAPSULE, family=binomial, training_frame=pyedc35d3e-7aec-4024-b6de-38456db31694, prior=0.661566011292, standardize=False, lambda_search=True, beta_constraints=py93c93a64-ccd6-4b00-97c0-13ccd62272e2, max_iterations=29, solver=L_BFGS} Building H2O GLM model with these parameters: 04-29 15:24:39.309 172.16.2.49:54321 30553 FJ-0-61 INFO: {"_model_id":null,"_train":{"name":"pyedc35d3e-7aec-4024-b6de-38456db31694","type":"Key"},"_valid":{"name":"py23e6ca95-9a67-4208-94d3-0ec7b71ccb6d","type":"Key"},"_ignored_columns":null,"_drop_na20_cols":false,"_dropConsCols":true,"_score_each_iteration":false,"_response_column":"CAPSULE","_balance_classes":false,"_max_after_balance_size":5.0,"_class_sampling_factors":null,"_max_hit_ratio_k":10,"_max_confusion_matrix_size":20,"_standardize":false,"_family":"binomial","_link":"family_default","_solver":"L_BFGS","_tweedie_variance_power":"NaN","_tweedie_link_power":"NaN","_alpha":null,"_lambda":null,"_prior":0.661566011292,"_lambda_search":true,"_nlambdas":100,"_lambda_min_ratio":-1.0,"_use_all_factor_levels":false,"_beta_epsilon":1.0E-4,"_max_iterations":29,"_n_folds":0,"_beta_constraints":{"name":"py93c93a64-ccd6-4b00-97c0-13ccd62272e2","type":"Key"},"_max_active_predictors":-1} 04-29 15:24:39.383 172.16.2.49:54321 30553 FJ-0-61 INFO: GLM[dest=GLMModel__a52d485c8b76961f5edd13c26e2e483f, iteration=0, lambda = 3166.0541505486444]: lambda = 3166.0541505486444 04-29 15:24:39.384 172.16.2.49:54321 30553 FJ-0-61 INFO: GLM[dest=GLMModel__a52d485c8b76961f5edd13c26e2e483f, iteration=0, lambda = 3166.0541505486444]: strong rule at lambda_value=3166.0541505486444, all 6 coefficients are active barrier onExCompletion for hex.glm.GLM$GLMDriver@323e5ed3 java.lang.NullPointerException at hex.glm.GLM$LBFGS_ProximalSolver.solve(GLM.java:1258) at hex.optimization.ADMM$L1Solver.solve(ADMM.java:64) at hex.optimization.ADMM$L1Solver.solve(ADMM.java:37) at hex.glm.GLM$GLMSingleLambdaTsk.solve(GLM.java:734) at hex.glm.GLM$GLMSingleLambdaTsk.compute2(GLM.java:916) at water.H2O$H2OCountedCompleter.compute(H2O.java:672) at jsr166y.CountedCompleter.exec(CountedCompleter.java:429) at jsr166y.ForkJoinTask.doExec(ForkJoinTask.java:263) at jsr166y.ForkJoinPool$WorkQueue.pollAndExecAll(ForkJoinPool.java:914) at jsr166y.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:979) at jsr166y.ForkJoinPool.runWorker(ForkJoinPool.java:1477) at jsr166y.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:104) ------------------------------------------------------------------------------------------------------------------------ x: [6, 3] y: 1 validation: True solver: L_BFGS link: identity beta_constraints: Displaying 2 row(s): Row ID names lower_bounds upper_bounds -------- ---------------------- --------------------- --------------------- 1 [u'0-60 mph (s)'] [-0.2723062059925039] [0.5907804311252647] 2 [u'displacement (cc)'] [-0.4166448368007114] [-0.1256516073053856] family: gaussian max_iterations: 3 URI: /3/ModelBuilders/glm, route: /3/ModelBuilders/glm, parms: {training_frame=pye58c73e0-3eb9-4d4b-98b1-7cf4b1541eab, family=gaussian, link=identity, validation_frame=pyb6761aad-6ac8-4de4-8cfb-d769b3f77658, beta_constraints=py43b83d31-38f5-434b-a221-1067da4cddbd, response_column=economy (mpg), max_iterations=3, solver=L_BFGS} Building H2O GLM model with these parameters: 04-29 15:27:59.588 172.16.2.49:54321 30553 FJ-0-37 INFO: { "_model_id":null, "_train":{"name":"pye58c73e0-3eb9-4d4b-98b1-7cf4b1541eab","type":"Key"}, "_valid":{"name":"pyb6761aad-6ac8-4de4-8cfb-d769b3f77658","type":"Key"}, "_ignored_columns":null,"_drop_na20_cols":false,"_dropConsCols":true, "_score_each_iteration":false,"_response_column":"economy (mpg)", "_balance_classes":false,"_max_after_balance_size":5.0, "_class_sampling_factors":null,"_max_hit_ratio_k":10, "_max_confusion_matrix_size":20,"_standardize":true, "_family":"gaussian","_link":"identity", "_solver":"L_BFGS", "_tweedie_variance_power":"NaN", "_tweedie_link_power":"NaN", "_alpha":null,"_lambda":null, "_prior":-1.0,"_lambda_search":false,"_nlambdas":-1, "_lambda_min_ratio":-1.0, "_use_all_factor_levels":false, "_beta_epsilon":1.0E-4, "_max_iterations":3, "_n_folds":0, "_beta_constraints":{"name":"py43b83d31-38f5-434b-a221-1067da4cddbd","type":"Key"}, "_max_active_predictors":-1} 04-29 15:27:59.589 172.16.2.49:54321 30553 FJ-0-37 INFO: GLM[dest=GLMModel__a6ad25f0418a87a1b947cc5e4fcd45fa, iteration=0, lambda = 6.19903015166837]: lambda = 6.19903015166837 04-29 15:27:59.589 172.16.2.49:54321 30553 FJ-0-37 INFO: GLM[dest=GLMModel__a6ad25f0418a87a1b947cc5e4fcd45fa, iteration=0, lambda = 6.19903015166837]: strong rule at lambda_value=6.19903015166837, all 2 coefficients are active barrier onExCompletion for hex.glm.GLM$GLMDriver@1f445715 java.lang.NullPointerException at hex.glm.GLM$LBFGS_ProximalSolver.solve(GLM.java:1258) at hex.optimization.ADMM$L1Solver.solve(ADMM.java:64) at hex.optimization.ADMM$L1Solver.solve(ADMM.java:37) at hex.glm.GLM$GLMSingleLambdaTsk.solve(GLM.java:734) at hex.glm.GLM$GLMSingleLambdaTsk.compute2(GLM.java:916) at water.H2O$H2OCountedCompleter.compute(H2O.java:672) at jsr166y.CountedCompleter.exec(CountedCompleter.java:429) at jsr166y.ForkJoinTask.doExec(ForkJoinTask.java:263) at jsr166y.ForkJoinPool$WorkQueue.pollAndExecAll(ForkJoinPool.java:914) at jsr166y.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:979) at jsr166y.ForkJoinPool.runWorker(ForkJoinPool.java:1477) at jsr166y.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:104) ------------------------------------------------------------------------------------------------------------------------ x: [8, 7, 5, 2, 4, 3] y: 1 validation: False beta_epsilon: 0.261800842523 beta_constraints: Displaying 6 row(s): Row ID names lower_bounds upper_bounds -------- ------------ ----------------------- --------------------- 1 [u'GLEASON'] [0.6037188079071251] [1.5672690700157834] 2 [u'VOL'] [-0.055527950646784514] [0.10034351710040412] 3 [u'DCAPS'] [0.5044730768501486] [1.4121190834113224] 4 [u'AGE'] [-0.3210641221790995] [0.24810051491640794] 5 [u'DPROS'] [-0.12327238530953367] [0.06402779204378617] 6 [u'RACE'] [-0.2277658695845901] [0.4428663282073051] standardize: False family: binomial solver: L_BFGS URI: /3/ModelBuilders/glm, route: /3/ModelBuilders/glm, parms: {standardize=False, beta_epsilon=0.261800842523, training_frame=py3e5d0afa-b854-470b-b0ba-f01cfb0fed49, family=binomial, beta_constraints=py0dd155de-c551-4e67-a3d5-a8c4ab85187b, response_column=CAPSULE, solver=L_BFGS} 04-29 15:50:04.115 172.16.2.49:54321 30553 FJ-0-1 INFO: Building H2O GLM model with these parameters: 04-29 15:50:04.115 172.16.2.49:54321 30553 FJ-0-1 INFO: {"_model_id":null,"_train":{"name":"py3e5d0afa-b854-470b-b0ba-f01cfb0fed49","type":"Key"},"_valid":null,"_ignored_columns":null,"_drop_na20_cols":false,"_dropConsCols":true,"_score_each_iteration":false,"_response_column":"CAPSULE","_balance_classes":false,"_max_after_balance_size":5.0,"_class_sampling_factors":null,"_max_hit_ratio_k":10,"_max_confusion_matrix_size":20,"_standardize":false,"_family":"binomial","_link":"family_default","_solver":"L_BFGS","_tweedie_variance_power":"NaN","_tweedie_link_power":"NaN","_alpha":null,"_lambda":null,"_prior":-1.0,"_lambda_search":false,"_nlambdas":-1,"_lambda_min_ratio":-1.0,"_use_all_factor_levels":false,"_beta_epsilon":0.261800842523,"_max_iterations":-1,"_n_folds":0,"_beta_constraints":{"name":"py0dd155de-c551-4e67-a3d5-a8c4ab85187b","type":"Key"},"_max_active_predictors":-1} 04-29 15:50:04.182 172.16.2.49:54321 30553 FJ-0-1 INFO: GLM[dest=GLMModel__9596a5d7fa5b0311c24067c844bb4ebb, iteration=0, lambda = 1.039894638541317]: lambda = 1.039894638541317 04-29 15:50:04.182 172.16.2.49:54321 30553 FJ-0-1 INFO: GLM[dest=GLMModel__9596a5d7fa5b0311c24067c844bb4ebb, iteration=0, lambda = 1.039894638541317]: strong rule at lambda_value=1.039894638541317, all 6 coefficients are active barrier onExCompletion for hex.glm.GLM$GLMDriver@271d5641 java.lang.NullPointerException at hex.glm.GLM$LBFGS_ProximalSolver.solve(GLM.java:1258) at hex.optimization.ADMM$L1Solver.solve(ADMM.java:64) at hex.optimization.ADMM$L1Solver.solve(ADMM.java:37) at hex.glm.GLM$GLMSingleLambdaTsk.solve(GLM.java:734) at hex.glm.GLM$GLMSingleLambdaTsk.compute2(GLM.java:916) at water.H2O$H2OCountedCompleter.compute(H2O.java:672) at jsr166y.CountedCompleter.exec(CountedCompleter.java:429) at jsr166y.ForkJoinTask.doExec(ForkJoinTask.java:263) at jsr166y.ForkJoinPool$WorkQueue.pollAndExecAll(ForkJoinPool.java:914) at jsr166y.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:979) at jsr166y.ForkJoinPool.runWorker(ForkJoinPool.java:1477) at jsr166y.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:104) ------------------------------------------------------------------------------------------------------------------------ x: [3] y: 1 validation: True beta_constraints: Displaying 1 row(s): Row ID names lower_bounds upper_bounds -------- ------- ---------------------- -------------------- 1 [0.0] [-0.46801259508547105] [0.3585166615222658] family: binomial solver: L_BFGS URI: /3/ModelBuilders/glm, route: /3/ModelBuilders/glm, parms: {training_frame=py82fce4d9-5d1e-4e7f-aa53-db61f3483075, family=binomial, validation_frame=pyabf61d08-51d4-4c5d-9b52-e1415377b07d, beta_constraints=pyd30cf2c3-07a4-4aba-965c-83017c2bd3e1, response_column=CAPSULE, solver=L_BFGS} 04-29 15:56:23.130 172.16.2.49:54321 30553 FJ-0-57 INFO: Building H2O GLM model with these parameters: 04-29 15:56:23.130 172.16.2.49:54321 30553 FJ-0-57 INFO: {"_model_id":null,"_train":{"name":"py82fce4d9-5d1e-4e7f-aa53-db61f3483075","type":"Key"},"_valid":{"name":"pyabf61d08-51d4-4c5d-9b52-e1415377b07d","type":"Key"},"_ignored_columns":null,"_drop_na20_cols":false,"_dropConsCols":true,"_score_each_iteration":false,"_response_column":"CAPSULE","_balance_classes":false,"_max_after_balance_size":5.0,"_class_sampling_factors":null,"_max_hit_ratio_k":10,"_max_confusion_matrix_size":20,"_standardize":true,"_family":"binomial","_link":"family_default","_solver":"L_BFGS","_tweedie_variance_power":"NaN","_tweedie_link_power":"NaN","_alpha":null,"_lambda":null,"_prior":-1.0,"_lambda_search":false,"_nlambdas":-1,"_lambda_min_ratio":-1.0,"_use_all_factor_levels":false,"_beta_epsilon":1.0E-4,"_max_iterations":-1,"_n_folds":0,"_beta_constraints":{"name":"pyd30cf2c3-07a4-4aba-965c-83017c2bd3e1","type":"Key"},"_max_active_predictors":-1} 04-29 15:56:23.188 172.16.2.49:54321 30553 FJ-0-57 INFO: GLM[dest=GLMModel__b5efc45bd5a04aff851cfd7d6b1b4640, iteration=0, lambda = 0.004285815250498477]: lambda = 0.004285815250498477 04-29 15:56:23.188 172.16.2.49:54321 30553 FJ-0-57 INFO: GLM[dest=GLMModel__b5efc45bd5a04aff851cfd7d6b1b4640, iteration=0, lambda = 0.004285815250498477]: strong rule at lambda_value=0.004285815250498477, all 1 coefficients are active barrier onExCompletion for hex.glm.GLM$GLMDriver@4ab0c9f0 java.lang.NullPointerException at hex.glm.GLM$LBFGS_ProximalSolver.solve(GLM.java:1258) at hex.optimization.ADMM$L1Solver.solve(ADMM.java:64) at hex.optimization.ADMM$L1Solver.solve(ADMM.java:37) at hex.glm.GLM$GLMSingleLambdaTsk.solve(GLM.java:734) at hex.glm.GLM$GLMSingleLambdaTsk.compute2(GLM.java:916) at water.H2O$H2OCountedCompleter.compute(H2O.java:672) at jsr166y.CountedCompleter.exec(CountedCompleter.java:429) at jsr166y.ForkJoinTask.doExec(ForkJoinTask.java:263) at jsr166y.ForkJoinPool$WorkQueue.pollAndExecAll(ForkJoinPool.java:914) at jsr166y.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:979) at jsr166y.ForkJoinPool.runWorker(ForkJoinPool.java:1477) at jsr166y.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:104) ------------------------------------------------------------------------------------------------------------------------ x: [7, 5, 2, 3, 4, 6, 8] y: 1 validation: False beta_constraints: Displaying 7 row(s): Row ID names lower_bounds upper_bounds -------- ------------ ---------------------- ---------------------- 1 [u'VOL'] [-0.3702057999756097] [0.4252158922797742] 2 [u'DCAPS'] [0.022210683604523274] [0.2182701878254334] 3 [u'AGE'] [0.3000966425874516] [0.4369056754392293] 4 [u'RACE'] [0.0668550023247827] [0.4766475381853143] 5 [u'DPROS'] [-0.5686436268027424] [-0.22372236244786306] 6 [u'PSA'] [0.2874500425271529] [1.0229914568776048] 7 [u'GLEASON'] [-0.4221837204368124] [-0.17674641926752077] link: logit lambda_search: True family: binomial solver: L_BFGS URI: /3/ModelBuilders/glm, route: /3/ModelBuilders/glm, parms: {training_frame=py1834a92c-ea75-4679-beef-3478ea47a7c2, family=binomial, link=logit, beta_constraints=pye9ca4329-a1db-45ff-855e-5ffe5cee6980, response_column=CAPSULE, solver=L_BFGS, lambda_search=True} 04-29 16:04:06.191 172.16.2.49:54321 30553 FJ-0-51 INFO: Building H2O GLM model with these parameters: 04-29 16:04:06.191 172.16.2.49:54321 30553 FJ-0-51 INFO: {"_model_id":null,"_train":{"name":"py1834a92c-ea75-4679-beef-3478ea47a7c2","type":"Key"},"_valid":null,"_ignored_columns":null,"_drop_na20_cols":false,"_dropConsCols":true,"_score_each_iteration":false,"_response_column":"CAPSULE","_balance_classes":false,"_max_after_balance_size":5.0,"_class_sampling_factors":null,"_max_hit_ratio_k":10,"_max_confusion_matrix_size":20,"_standardize":true,"_family":"binomial","_link":"logit","_solver":"L_BFGS","_tweedie_variance_power":"NaN","_tweedie_link_power":"NaN","_alpha":null,"_lambda":null,"_prior":-1.0,"_lambda_search":true,"_nlambdas":100,"_lambda_min_ratio":-1.0,"_use_all_factor_levels":false,"_beta_epsilon":1.0E-4,"_max_iterations":-1,"_n_folds":0,"_beta_constraints":{"name":"pye9ca4329-a1db-45ff-855e-5ffe5cee6980","type":"Key"},"_max_active_predictors":-1} 04-29 16:04:06.261 172.16.2.49:54321 30553 FJ-0-51 INFO: GLM[dest=GLMModel__adb99bd2baab9b29901ec4f4d31043ff, iteration=0, lambda = 219.7372655827877]: lambda = 219.7372655827877 04-29 16:04:06.261 172.16.2.49:54321 30553 FJ-0-51 INFO: GLM[dest=GLMModel__adb99bd2baab9b29901ec4f4d31043ff, iteration=0, lambda = 219.7372655827877]: strong rule at lambda_value=219.7372655827877, all 7 coefficients are active barrier onExCompletion for hex.glm.GLM$GLMDriver@29f73dd5 java.lang.NullPointerException at hex.glm.GLM$LBFGS_ProximalSolver.solve(GLM.java:1258) at hex.optimization.ADMM$L1Solver.solve(ADMM.java:64) at hex.optimization.ADMM$L1Solver.solve(ADMM.java:37) at hex.glm.GLM$GLMSingleLambdaTsk.solve(GLM.java:734) at hex.glm.GLM$GLMSingleLambdaTsk.compute2(GLM.java:916) at water.H2O$H2OCountedCompleter.compute(H2O.java:672) at jsr166y.CountedCompleter.exec(CountedCompleter.java:429) at jsr166y.ForkJoinTask.doExec(ForkJoinTask.java:263) at jsr166y.ForkJoinPool$WorkQueue.pollAndExecAll(ForkJoinPool.java:914) at jsr166y.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:979) at jsr166y.ForkJoinPool.runWorker(ForkJoinPool.java:1477) at jsr166y.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:104)

    JIRA | 2 years ago | Eric Eckstrand
    java.lang.NullPointerException
  2. 0

    Here are some NPEs achieved by glm random attack test. pros = h2o.upload_file(h2o.locate("smalldata/prostate/prostate.csv.zip")) pros[1] = pros[1].asfactor() r = pros[0].runif() # ~80/20 train/validation split pros_train = pros[r > .2] pros_valid = pros[r <= .2] cars = h2o.upload_file(h2o.locate("smalldata/junit/cars.csv")) r = cars[0].runif() cars_train = cars[r > .2] cars_valid = cars[r <= .2] # Binomial and gamma use prostate (CAPSULE/DPROS respectively) # Gaussian and poisson use cars (mpg/Cylinders respectively) The common thread seems to be beta constraints w/ LBFGS x: [6, 3, 4, 5, 2, 8] y: 1 validation: True standardize: False family: binomial solver: L_BFGS prior: 0.661566011292 beta_constraints: Displaying 6 row(s): Row ID names lower_bounds upper_bounds -------- ------------ --------------------- ---------------------- 1 [u'PSA'] [0.08442861247981925] [0.12694071519057182] 2 [u'RACE'] [-0.5780290588548885] [-0.13810131302030548] 3 [u'DPROS'] [0.76852832394281] [1.3496105569956252] 4 [u'DCAPS'] [-0.9016507404584659] [-0.32401365663844667] 5 [u'AGE'] [0.5855928861219879] [1.1951827824495105] 6 [u'GLEASON'] [0.5811227135549313] [0.6066065068362181] lambda_search: True max_iterations: 29 URI: /3/ModelBuilders/glm, route: /3/ModelBuilders/glm, parms: {validation_frame=py23e6ca95-9a67-4208-94d3-0ec7b71ccb6d, response_column=CAPSULE, family=binomial, training_frame=pyedc35d3e-7aec-4024-b6de-38456db31694, prior=0.661566011292, standardize=False, lambda_search=True, beta_constraints=py93c93a64-ccd6-4b00-97c0-13ccd62272e2, max_iterations=29, solver=L_BFGS} Building H2O GLM model with these parameters: 04-29 15:24:39.309 172.16.2.49:54321 30553 FJ-0-61 INFO: {"_model_id":null,"_train":{"name":"pyedc35d3e-7aec-4024-b6de-38456db31694","type":"Key"},"_valid":{"name":"py23e6ca95-9a67-4208-94d3-0ec7b71ccb6d","type":"Key"},"_ignored_columns":null,"_drop_na20_cols":false,"_dropConsCols":true,"_score_each_iteration":false,"_response_column":"CAPSULE","_balance_classes":false,"_max_after_balance_size":5.0,"_class_sampling_factors":null,"_max_hit_ratio_k":10,"_max_confusion_matrix_size":20,"_standardize":false,"_family":"binomial","_link":"family_default","_solver":"L_BFGS","_tweedie_variance_power":"NaN","_tweedie_link_power":"NaN","_alpha":null,"_lambda":null,"_prior":0.661566011292,"_lambda_search":true,"_nlambdas":100,"_lambda_min_ratio":-1.0,"_use_all_factor_levels":false,"_beta_epsilon":1.0E-4,"_max_iterations":29,"_n_folds":0,"_beta_constraints":{"name":"py93c93a64-ccd6-4b00-97c0-13ccd62272e2","type":"Key"},"_max_active_predictors":-1} 04-29 15:24:39.383 172.16.2.49:54321 30553 FJ-0-61 INFO: GLM[dest=GLMModel__a52d485c8b76961f5edd13c26e2e483f, iteration=0, lambda = 3166.0541505486444]: lambda = 3166.0541505486444 04-29 15:24:39.384 172.16.2.49:54321 30553 FJ-0-61 INFO: GLM[dest=GLMModel__a52d485c8b76961f5edd13c26e2e483f, iteration=0, lambda = 3166.0541505486444]: strong rule at lambda_value=3166.0541505486444, all 6 coefficients are active barrier onExCompletion for hex.glm.GLM$GLMDriver@323e5ed3 java.lang.NullPointerException at hex.glm.GLM$LBFGS_ProximalSolver.solve(GLM.java:1258) at hex.optimization.ADMM$L1Solver.solve(ADMM.java:64) at hex.optimization.ADMM$L1Solver.solve(ADMM.java:37) at hex.glm.GLM$GLMSingleLambdaTsk.solve(GLM.java:734) at hex.glm.GLM$GLMSingleLambdaTsk.compute2(GLM.java:916) at water.H2O$H2OCountedCompleter.compute(H2O.java:672) at jsr166y.CountedCompleter.exec(CountedCompleter.java:429) at jsr166y.ForkJoinTask.doExec(ForkJoinTask.java:263) at jsr166y.ForkJoinPool$WorkQueue.pollAndExecAll(ForkJoinPool.java:914) at jsr166y.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:979) at jsr166y.ForkJoinPool.runWorker(ForkJoinPool.java:1477) at jsr166y.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:104) ------------------------------------------------------------------------------------------------------------------------ x: [6, 3] y: 1 validation: True solver: L_BFGS link: identity beta_constraints: Displaying 2 row(s): Row ID names lower_bounds upper_bounds -------- ---------------------- --------------------- --------------------- 1 [u'0-60 mph (s)'] [-0.2723062059925039] [0.5907804311252647] 2 [u'displacement (cc)'] [-0.4166448368007114] [-0.1256516073053856] family: gaussian max_iterations: 3 URI: /3/ModelBuilders/glm, route: /3/ModelBuilders/glm, parms: {training_frame=pye58c73e0-3eb9-4d4b-98b1-7cf4b1541eab, family=gaussian, link=identity, validation_frame=pyb6761aad-6ac8-4de4-8cfb-d769b3f77658, beta_constraints=py43b83d31-38f5-434b-a221-1067da4cddbd, response_column=economy (mpg), max_iterations=3, solver=L_BFGS} Building H2O GLM model with these parameters: 04-29 15:27:59.588 172.16.2.49:54321 30553 FJ-0-37 INFO: { "_model_id":null, "_train":{"name":"pye58c73e0-3eb9-4d4b-98b1-7cf4b1541eab","type":"Key"}, "_valid":{"name":"pyb6761aad-6ac8-4de4-8cfb-d769b3f77658","type":"Key"}, "_ignored_columns":null,"_drop_na20_cols":false,"_dropConsCols":true, "_score_each_iteration":false,"_response_column":"economy (mpg)", "_balance_classes":false,"_max_after_balance_size":5.0, "_class_sampling_factors":null,"_max_hit_ratio_k":10, "_max_confusion_matrix_size":20,"_standardize":true, "_family":"gaussian","_link":"identity", "_solver":"L_BFGS", "_tweedie_variance_power":"NaN", "_tweedie_link_power":"NaN", "_alpha":null,"_lambda":null, "_prior":-1.0,"_lambda_search":false,"_nlambdas":-1, "_lambda_min_ratio":-1.0, "_use_all_factor_levels":false, "_beta_epsilon":1.0E-4, "_max_iterations":3, "_n_folds":0, "_beta_constraints":{"name":"py43b83d31-38f5-434b-a221-1067da4cddbd","type":"Key"}, "_max_active_predictors":-1} 04-29 15:27:59.589 172.16.2.49:54321 30553 FJ-0-37 INFO: GLM[dest=GLMModel__a6ad25f0418a87a1b947cc5e4fcd45fa, iteration=0, lambda = 6.19903015166837]: lambda = 6.19903015166837 04-29 15:27:59.589 172.16.2.49:54321 30553 FJ-0-37 INFO: GLM[dest=GLMModel__a6ad25f0418a87a1b947cc5e4fcd45fa, iteration=0, lambda = 6.19903015166837]: strong rule at lambda_value=6.19903015166837, all 2 coefficients are active barrier onExCompletion for hex.glm.GLM$GLMDriver@1f445715 java.lang.NullPointerException at hex.glm.GLM$LBFGS_ProximalSolver.solve(GLM.java:1258) at hex.optimization.ADMM$L1Solver.solve(ADMM.java:64) at hex.optimization.ADMM$L1Solver.solve(ADMM.java:37) at hex.glm.GLM$GLMSingleLambdaTsk.solve(GLM.java:734) at hex.glm.GLM$GLMSingleLambdaTsk.compute2(GLM.java:916) at water.H2O$H2OCountedCompleter.compute(H2O.java:672) at jsr166y.CountedCompleter.exec(CountedCompleter.java:429) at jsr166y.ForkJoinTask.doExec(ForkJoinTask.java:263) at jsr166y.ForkJoinPool$WorkQueue.pollAndExecAll(ForkJoinPool.java:914) at jsr166y.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:979) at jsr166y.ForkJoinPool.runWorker(ForkJoinPool.java:1477) at jsr166y.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:104) ------------------------------------------------------------------------------------------------------------------------ x: [8, 7, 5, 2, 4, 3] y: 1 validation: False beta_epsilon: 0.261800842523 beta_constraints: Displaying 6 row(s): Row ID names lower_bounds upper_bounds -------- ------------ ----------------------- --------------------- 1 [u'GLEASON'] [0.6037188079071251] [1.5672690700157834] 2 [u'VOL'] [-0.055527950646784514] [0.10034351710040412] 3 [u'DCAPS'] [0.5044730768501486] [1.4121190834113224] 4 [u'AGE'] [-0.3210641221790995] [0.24810051491640794] 5 [u'DPROS'] [-0.12327238530953367] [0.06402779204378617] 6 [u'RACE'] [-0.2277658695845901] [0.4428663282073051] standardize: False family: binomial solver: L_BFGS URI: /3/ModelBuilders/glm, route: /3/ModelBuilders/glm, parms: {standardize=False, beta_epsilon=0.261800842523, training_frame=py3e5d0afa-b854-470b-b0ba-f01cfb0fed49, family=binomial, beta_constraints=py0dd155de-c551-4e67-a3d5-a8c4ab85187b, response_column=CAPSULE, solver=L_BFGS} 04-29 15:50:04.115 172.16.2.49:54321 30553 FJ-0-1 INFO: Building H2O GLM model with these parameters: 04-29 15:50:04.115 172.16.2.49:54321 30553 FJ-0-1 INFO: {"_model_id":null,"_train":{"name":"py3e5d0afa-b854-470b-b0ba-f01cfb0fed49","type":"Key"},"_valid":null,"_ignored_columns":null,"_drop_na20_cols":false,"_dropConsCols":true,"_score_each_iteration":false,"_response_column":"CAPSULE","_balance_classes":false,"_max_after_balance_size":5.0,"_class_sampling_factors":null,"_max_hit_ratio_k":10,"_max_confusion_matrix_size":20,"_standardize":false,"_family":"binomial","_link":"family_default","_solver":"L_BFGS","_tweedie_variance_power":"NaN","_tweedie_link_power":"NaN","_alpha":null,"_lambda":null,"_prior":-1.0,"_lambda_search":false,"_nlambdas":-1,"_lambda_min_ratio":-1.0,"_use_all_factor_levels":false,"_beta_epsilon":0.261800842523,"_max_iterations":-1,"_n_folds":0,"_beta_constraints":{"name":"py0dd155de-c551-4e67-a3d5-a8c4ab85187b","type":"Key"},"_max_active_predictors":-1} 04-29 15:50:04.182 172.16.2.49:54321 30553 FJ-0-1 INFO: GLM[dest=GLMModel__9596a5d7fa5b0311c24067c844bb4ebb, iteration=0, lambda = 1.039894638541317]: lambda = 1.039894638541317 04-29 15:50:04.182 172.16.2.49:54321 30553 FJ-0-1 INFO: GLM[dest=GLMModel__9596a5d7fa5b0311c24067c844bb4ebb, iteration=0, lambda = 1.039894638541317]: strong rule at lambda_value=1.039894638541317, all 6 coefficients are active barrier onExCompletion for hex.glm.GLM$GLMDriver@271d5641 java.lang.NullPointerException at hex.glm.GLM$LBFGS_ProximalSolver.solve(GLM.java:1258) at hex.optimization.ADMM$L1Solver.solve(ADMM.java:64) at hex.optimization.ADMM$L1Solver.solve(ADMM.java:37) at hex.glm.GLM$GLMSingleLambdaTsk.solve(GLM.java:734) at hex.glm.GLM$GLMSingleLambdaTsk.compute2(GLM.java:916) at water.H2O$H2OCountedCompleter.compute(H2O.java:672) at jsr166y.CountedCompleter.exec(CountedCompleter.java:429) at jsr166y.ForkJoinTask.doExec(ForkJoinTask.java:263) at jsr166y.ForkJoinPool$WorkQueue.pollAndExecAll(ForkJoinPool.java:914) at jsr166y.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:979) at jsr166y.ForkJoinPool.runWorker(ForkJoinPool.java:1477) at jsr166y.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:104) ------------------------------------------------------------------------------------------------------------------------ x: [3] y: 1 validation: True beta_constraints: Displaying 1 row(s): Row ID names lower_bounds upper_bounds -------- ------- ---------------------- -------------------- 1 [0.0] [-0.46801259508547105] [0.3585166615222658] family: binomial solver: L_BFGS URI: /3/ModelBuilders/glm, route: /3/ModelBuilders/glm, parms: {training_frame=py82fce4d9-5d1e-4e7f-aa53-db61f3483075, family=binomial, validation_frame=pyabf61d08-51d4-4c5d-9b52-e1415377b07d, beta_constraints=pyd30cf2c3-07a4-4aba-965c-83017c2bd3e1, response_column=CAPSULE, solver=L_BFGS} 04-29 15:56:23.130 172.16.2.49:54321 30553 FJ-0-57 INFO: Building H2O GLM model with these parameters: 04-29 15:56:23.130 172.16.2.49:54321 30553 FJ-0-57 INFO: {"_model_id":null,"_train":{"name":"py82fce4d9-5d1e-4e7f-aa53-db61f3483075","type":"Key"},"_valid":{"name":"pyabf61d08-51d4-4c5d-9b52-e1415377b07d","type":"Key"},"_ignored_columns":null,"_drop_na20_cols":false,"_dropConsCols":true,"_score_each_iteration":false,"_response_column":"CAPSULE","_balance_classes":false,"_max_after_balance_size":5.0,"_class_sampling_factors":null,"_max_hit_ratio_k":10,"_max_confusion_matrix_size":20,"_standardize":true,"_family":"binomial","_link":"family_default","_solver":"L_BFGS","_tweedie_variance_power":"NaN","_tweedie_link_power":"NaN","_alpha":null,"_lambda":null,"_prior":-1.0,"_lambda_search":false,"_nlambdas":-1,"_lambda_min_ratio":-1.0,"_use_all_factor_levels":false,"_beta_epsilon":1.0E-4,"_max_iterations":-1,"_n_folds":0,"_beta_constraints":{"name":"pyd30cf2c3-07a4-4aba-965c-83017c2bd3e1","type":"Key"},"_max_active_predictors":-1} 04-29 15:56:23.188 172.16.2.49:54321 30553 FJ-0-57 INFO: GLM[dest=GLMModel__b5efc45bd5a04aff851cfd7d6b1b4640, iteration=0, lambda = 0.004285815250498477]: lambda = 0.004285815250498477 04-29 15:56:23.188 172.16.2.49:54321 30553 FJ-0-57 INFO: GLM[dest=GLMModel__b5efc45bd5a04aff851cfd7d6b1b4640, iteration=0, lambda = 0.004285815250498477]: strong rule at lambda_value=0.004285815250498477, all 1 coefficients are active barrier onExCompletion for hex.glm.GLM$GLMDriver@4ab0c9f0 java.lang.NullPointerException at hex.glm.GLM$LBFGS_ProximalSolver.solve(GLM.java:1258) at hex.optimization.ADMM$L1Solver.solve(ADMM.java:64) at hex.optimization.ADMM$L1Solver.solve(ADMM.java:37) at hex.glm.GLM$GLMSingleLambdaTsk.solve(GLM.java:734) at hex.glm.GLM$GLMSingleLambdaTsk.compute2(GLM.java:916) at water.H2O$H2OCountedCompleter.compute(H2O.java:672) at jsr166y.CountedCompleter.exec(CountedCompleter.java:429) at jsr166y.ForkJoinTask.doExec(ForkJoinTask.java:263) at jsr166y.ForkJoinPool$WorkQueue.pollAndExecAll(ForkJoinPool.java:914) at jsr166y.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:979) at jsr166y.ForkJoinPool.runWorker(ForkJoinPool.java:1477) at jsr166y.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:104) ------------------------------------------------------------------------------------------------------------------------ x: [7, 5, 2, 3, 4, 6, 8] y: 1 validation: False beta_constraints: Displaying 7 row(s): Row ID names lower_bounds upper_bounds -------- ------------ ---------------------- ---------------------- 1 [u'VOL'] [-0.3702057999756097] [0.4252158922797742] 2 [u'DCAPS'] [0.022210683604523274] [0.2182701878254334] 3 [u'AGE'] [0.3000966425874516] [0.4369056754392293] 4 [u'RACE'] [0.0668550023247827] [0.4766475381853143] 5 [u'DPROS'] [-0.5686436268027424] [-0.22372236244786306] 6 [u'PSA'] [0.2874500425271529] [1.0229914568776048] 7 [u'GLEASON'] [-0.4221837204368124] [-0.17674641926752077] link: logit lambda_search: True family: binomial solver: L_BFGS URI: /3/ModelBuilders/glm, route: /3/ModelBuilders/glm, parms: {training_frame=py1834a92c-ea75-4679-beef-3478ea47a7c2, family=binomial, link=logit, beta_constraints=pye9ca4329-a1db-45ff-855e-5ffe5cee6980, response_column=CAPSULE, solver=L_BFGS, lambda_search=True} 04-29 16:04:06.191 172.16.2.49:54321 30553 FJ-0-51 INFO: Building H2O GLM model with these parameters: 04-29 16:04:06.191 172.16.2.49:54321 30553 FJ-0-51 INFO: {"_model_id":null,"_train":{"name":"py1834a92c-ea75-4679-beef-3478ea47a7c2","type":"Key"},"_valid":null,"_ignored_columns":null,"_drop_na20_cols":false,"_dropConsCols":true,"_score_each_iteration":false,"_response_column":"CAPSULE","_balance_classes":false,"_max_after_balance_size":5.0,"_class_sampling_factors":null,"_max_hit_ratio_k":10,"_max_confusion_matrix_size":20,"_standardize":true,"_family":"binomial","_link":"logit","_solver":"L_BFGS","_tweedie_variance_power":"NaN","_tweedie_link_power":"NaN","_alpha":null,"_lambda":null,"_prior":-1.0,"_lambda_search":true,"_nlambdas":100,"_lambda_min_ratio":-1.0,"_use_all_factor_levels":false,"_beta_epsilon":1.0E-4,"_max_iterations":-1,"_n_folds":0,"_beta_constraints":{"name":"pye9ca4329-a1db-45ff-855e-5ffe5cee6980","type":"Key"},"_max_active_predictors":-1} 04-29 16:04:06.261 172.16.2.49:54321 30553 FJ-0-51 INFO: GLM[dest=GLMModel__adb99bd2baab9b29901ec4f4d31043ff, iteration=0, lambda = 219.7372655827877]: lambda = 219.7372655827877 04-29 16:04:06.261 172.16.2.49:54321 30553 FJ-0-51 INFO: GLM[dest=GLMModel__adb99bd2baab9b29901ec4f4d31043ff, iteration=0, lambda = 219.7372655827877]: strong rule at lambda_value=219.7372655827877, all 7 coefficients are active barrier onExCompletion for hex.glm.GLM$GLMDriver@29f73dd5 java.lang.NullPointerException at hex.glm.GLM$LBFGS_ProximalSolver.solve(GLM.java:1258) at hex.optimization.ADMM$L1Solver.solve(ADMM.java:64) at hex.optimization.ADMM$L1Solver.solve(ADMM.java:37) at hex.glm.GLM$GLMSingleLambdaTsk.solve(GLM.java:734) at hex.glm.GLM$GLMSingleLambdaTsk.compute2(GLM.java:916) at water.H2O$H2OCountedCompleter.compute(H2O.java:672) at jsr166y.CountedCompleter.exec(CountedCompleter.java:429) at jsr166y.ForkJoinTask.doExec(ForkJoinTask.java:263) at jsr166y.ForkJoinPool$WorkQueue.pollAndExecAll(ForkJoinPool.java:914) at jsr166y.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:979) at jsr166y.ForkJoinPool.runWorker(ForkJoinPool.java:1477) at jsr166y.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:104)

    JIRA | 2 years ago | Eric Eckstrand
    java.lang.NullPointerException

    Root Cause Analysis

    1. java.lang.NullPointerException

      No message provided

      at hex.glm.GLM$LBFGS_ProximalSolver.solve()
    2. hex.glm
      GLM$LBFGS_ProximalSolver.solve
      1. hex.glm.GLM$LBFGS_ProximalSolver.solve(GLM.java:1258)
      1 frame
    3. hex.optimization
      ADMM$L1Solver.solve
      1. hex.optimization.ADMM$L1Solver.solve(ADMM.java:64)
      2. hex.optimization.ADMM$L1Solver.solve(ADMM.java:37)
      2 frames
    4. hex.glm
      GLM$GLMSingleLambdaTsk.compute2
      1. hex.glm.GLM$GLMSingleLambdaTsk.solve(GLM.java:734)
      2. hex.glm.GLM$GLMSingleLambdaTsk.compute2(GLM.java:916)
      2 frames
    5. water
      H2O$H2OCountedCompleter.compute
      1. water.H2O$H2OCountedCompleter.compute(H2O.java:672)
      1 frame
    6. jsr166y
      ForkJoinWorkerThread.run
      1. jsr166y.CountedCompleter.exec(CountedCompleter.java:429)
      2. jsr166y.ForkJoinTask.doExec(ForkJoinTask.java:263)
      3. jsr166y.ForkJoinPool$WorkQueue.pollAndExecAll(ForkJoinPool.java:914)
      4. jsr166y.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:979)
      5. jsr166y.ForkJoinPool.runWorker(ForkJoinPool.java:1477)
      6. jsr166y.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:104)
      6 frames