Running GAM twice in a row gives Null Pointer Exception

[exalate-issue-sync]

This should just overwrite the previous model & R object, rather than give an NPE.

{code:java}library(h2o)
#> Warning: package 'h2o' was built under R version 4.0.5
#>
#> ----------------------------------------------------------------------
#>
#> Your next step is to start H2O:
#> > h2o.init()
#>
#> For H2O package documentation, ask for help:
#> > ??h2o
#>
#> After starting H2O, you can use the Web UI at http://localhost:54321
#> For more information visit https://docs.h2o.ai
#>
#> ----------------------------------------------------------------------
#>
#> Attaching package: 'h2o'
#> The following objects are masked from 'package:stats':
#>
#> cor, sd, var
#> The following objects are masked from 'package:base':
#>
#> %*%, %in%, &&, ||, apply, as.factor, as.numeric, colnames,
#> colnames<-, ifelse, is.character, is.factor, is.numeric, log,
#> log10, log1p, log2, round, signif, trunc
h2o.init()
#> Connection successful!
#>
#> R is connected to the H2O cluster:
#> H2O cluster uptime: 19 minutes 25 seconds
#> H2O cluster timezone: America/Chicago
#> H2O data parsing timezone: UTC
#> H2O cluster version: 3.32.1.3
#> H2O cluster version age: 2 months and 21 days
#> H2O cluster name: H2O_started_from_R_E014307_zqv421
#> H2O cluster total nodes: 1
#> H2O cluster total memory: 26.08 GB
#> H2O cluster total cores: 20
#> H2O cluster allowed cores: 20
#> H2O cluster healthy: TRUE
#> H2O Connection ip: localhost
#> H2O Connection port: 54321
#> H2O Connection proxy: NA
#> H2O Internal Security: FALSE
#> H2O API Extensions: Amazon S3, Algos, AutoML, Core V3, TargetEncoder, Core V4
#> R Version: R version 4.0.2 (2020-06-22)

create frame knots

knots1 <- c(-1.99905699, -0.98143075, 0.02599159, 1.00770987, 1.99942290)
frame_Knots1 <- as.h2o(knots1)
#> | | | 0% | |======================================================================| 100%

import the dataset

h2o_data <- h2o.importFile("https://s3.amazonaws.com/h2o-public-test-data/smalldata/glm_test/multinomial_10_classes_10_cols_10000_Rows_train.csv")
#> | | | 0% | |==================== | 29% | |================================================================== | 94% | |======================================================================| 100%
h2o_data[["C1"]] <- as.factor(h2o_data[["C1"]])

build the GAM model

gam_model <- h2o.gam(x = "C6",
y = "C1",
training_frame = h2o_data,
family = 'multinomial',
gam_columns = "C6",
scale = 1,
num_knots = 5,
knot_ids = h2o.keyof(frame_Knots1))
#> | | | 0% | |======================================================================| 100%

error

gam_model <- h2o.gam(x = "C6",
y = "C1",
training_frame = h2o_data,
family = 'multinomial',
gam_columns = "C6",
scale = 1,
num_knots = 5,
knot_ids = h2o.keyof(frame_Knots1))
#> | | | 0%
#>
#> java.lang.NullPointerException
#>
#> java.lang.NullPointerException
#> at water.Scope.track(Scope.java:94)
#> at hex.gam.GAM.generateKnotsFromKeys(GAM.java:153)
#> at hex.gam.GAM.validateGamParameters(GAM.java:268)
#> at hex.gam.GAM.init(GAM.java:216)
#> at hex.gam.GAM$GAMDriver.computeImpl(GAM.java:664)
#> at hex.ModelBuilder$Driver.compute2(ModelBuilder.java:246)
#> at water.H2O$H2OCountedCompleter.compute(H2O.java:1637)
#> at jsr166y.CountedCompleter.exec(CountedCompleter.java:468)
#> at jsr166y.ForkJoinTask.doExec(ForkJoinTask.java:263)
#> at jsr166y.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:974)
#> at jsr166y.ForkJoinPool.runWorker(ForkJoinPool.java:1477)
#> at jsr166y.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:104)
#> Error: java.lang.NullPointerException{code}

[exalate-issue-sync]

Wendy commented: Thank you Erin. Should be a simple fix.

[h2o-ops]

JIRA Issue Details

Jira Issue: PUBDEV-8267
Assignee: Wendy
Reporter: Erin LeDell
State: Resolved
Fix Version: 3.34.0.1
Attachments: N/A
Development PRs: Available

[h2o-ops]

Linked PRs from JIRA

#5636