Running 'testthat.R' [381s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
  > # This file is part of the standard setup for testthat.
  > # It is recommended that you do not modify it.
  > #
  > # Where should you do additional test configuration?
  > # Learn more about the roles of various files in:
  > # * https://r-pkgs.org/tests.html
  > # * https://testthat.r-lib.org/reference/test_package.html#special-files
  > 
  > library(testthat)
  > library(mlsurvlrnrs)
  > 
  > test_check("mlsurvlrnrs")
  
  CV fold: Fold1
  Parameter 'ncores' is ignored for learner 'LearnerSurvCoxPHCox'.
  
  CV fold: Fold2
  Parameter 'ncores' is ignored for learner 'LearnerSurvCoxPHCox'.
  
  CV fold: Fold3
  Parameter 'ncores' is ignored for learner 'LearnerSurvCoxPHCox'.
  
  CV fold: Fold1
  
  Registering parallel backend using 2 cores.
  
  Running initial scoring function 6 times in 2 thread(s)...  4.27 seconds
  
  Starting Epoch 1 
    1) Fitting Gaussian Process...
    2) Running local optimum search...        0.83 seconds
    3) Running FUN 2 times in 2 thread(s)...  0.54 seconds
  
  CV fold: Fold2
  
  Registering parallel backend using 2 cores.
  
  Running initial scoring function 6 times in 2 thread(s)...  4.35 seconds
  
  Starting Epoch 1 
    1) Fitting Gaussian Process...
    2) Running local optimum search...        0.93 seconds
    3) Running FUN 2 times in 2 thread(s)...  0.56 seconds
  
  CV fold: Fold3
  
  Registering parallel backend using 2 cores.
  
  Running initial scoring function 6 times in 2 thread(s)...  4.55 seconds
  
  Starting Epoch 1 
    1) Fitting Gaussian Process...
    2) Running local optimum search...        0.61 seconds
    3) Running FUN 2 times in 2 thread(s)...  0.64 seconds
  
  CV fold: Fold1
  
  Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
  ... reducing initialization grid to 10 rows.
  
  Registering parallel backend using 2 cores.
  
  Running initial scoring function 10 times in 2 thread(s)...  3.61 seconds
  
  Starting Epoch 1 
    1) Fitting Gaussian Process...
       - Could not obtain meaningful lengthscales.
    2) Running local optimum search...
       - Convergence Not Found. Trying again with tighter parameters...
       - Convergence Not Found. Trying again with tighter parameters...        5.99 seconds
    3) Running FUN 2 times in 2 thread(s)...  0.26 seconds
  
  CV fold: Fold2
  
  Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
  ... reducing initialization grid to 10 rows.
  
  Registering parallel backend using 2 cores.
  
  Running initial scoring function 10 times in 2 thread(s)...  3.5 seconds
  
  Starting Epoch 1 
    1) Fitting Gaussian Process...
    2) Running local optimum search...        12.65 seconds
    3) Running FUN 2 times in 2 thread(s)...  0.3 seconds
  
  CV fold: Fold3
  
  Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
  ... reducing initialization grid to 10 rows.
  
  Registering parallel backend using 2 cores.
  
  Running initial scoring function 10 times in 2 thread(s)...  3.39 seconds
  
  Starting Epoch 1 
    1) Fitting Gaussian Process...
       - Could not obtain meaningful lengthscales.
    2) Running local optimum search...        0.61 seconds
    3) Running FUN 2 times in 2 thread(s)...  0.25 seconds
  
  CV fold: Fold1
  
  Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
  ... reducing initialization grid to 10 rows.
  
  Registering parallel backend using 2 cores.
  
  Running initial scoring function 10 times in 2 thread(s)...  3.46 seconds
  
  Starting Epoch 1 
    1) Fitting Gaussian Process...
    2) Running local optimum search...        0.44 seconds
    3) Running FUN 2 times in 2 thread(s)...  0.27 seconds
  
  CV fold: Fold2
  
  Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
  ... reducing initialization grid to 10 rows.
  
  Registering parallel backend using 2 cores.
  
  Running initial scoring function 10 times in 2 thread(s)...  3.69 seconds
  
  Starting Epoch 1 
    1) Fitting Gaussian Process...
    2) Running local optimum search...        0.38 seconds
    3) Running FUN 2 times in 2 thread(s)...  0.28 seconds
  
  CV fold: Fold3
  
  Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
  ... reducing initialization grid to 10 rows.
  
  Registering parallel backend using 2 cores.
  
  Running initial scoring function 10 times in 2 thread(s)...  3.28 seconds
  
  Starting Epoch 1 
    1) Fitting Gaussian Process...
    2) Running local optimum search...        0.45 seconds
    3) Running FUN 2 times in 2 thread(s)...  0.25 seconds
  
  CV fold: Fold1
  
  Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
  ... reducing initialization grid to 10 rows.
  
  Registering parallel backend using 2 cores.
  
  Running initial scoring function 10 times in 2 thread(s)...  4.32 seconds
  
  Starting Epoch 1 
    1) Fitting Gaussian Process...
    2) Running local optimum search...        9.79 seconds
    3) Running FUN 2 times in 2 thread(s)...  0.5 seconds
  
  CV fold: Fold2
  
  Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
  ... reducing initialization grid to 10 rows.
  
  Registering parallel backend using 2 cores.
  
  Running initial scoring function 10 times in 2 thread(s)...  4.3 seconds
  
  Starting Epoch 1 
    1) Fitting Gaussian Process...
    2) Running local optimum search...        7.5 seconds
    3) Running FUN 2 times in 2 thread(s)...  0.44 seconds
  
  CV fold: Fold3
  
  Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
  ... reducing initialization grid to 10 rows.
  
  Registering parallel backend using 2 cores.
  
  Running initial scoring function 10 times in 2 thread(s)...  4.37 seconds
  
  Starting Epoch 1 
    1) Fitting Gaussian Process...
    2) Running local optimum search...        10.76 seconds
    3) Running FUN 2 times in 2 thread(s)...  0.52 seconds
  
  CV fold: Fold1
  
  Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
  ... reducing initialization grid to 10 rows.
  
  Registering parallel backend using 2 cores.
  
  Running initial scoring function 10 times in 2 thread(s)...  3.45 seconds
  
  Starting Epoch 1 
    1) Fitting Gaussian Process...
    2) Running local optimum search...        3.41 seconds
    3) Running FUN 2 times in 2 thread(s)...  0.32 seconds
  
  CV fold: Fold2
  
  Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
  ... reducing initialization grid to 10 rows.
  
  Registering parallel backend using 2 cores.
  
  Running initial scoring function 10 times in 2 thread(s)...  3.14 seconds
  
  Starting Epoch 1 
    1) Fitting Gaussian Process...
       - Could not obtain meaningful lengthscales.
    2) Running local optimum search...
       - Convergence Not Found. Trying again with tighter parameters...
       - Convergence Not Found. Trying again with tighter parameters...
       - Convergence Not Found. Trying again with tighter parameters...
       - Maximum convergence attempts exceeded - process is probably sampling random points.        67.88 seconds
    3) Running FUN 2 times in 2 thread(s)...  0.31 seconds
  
  CV fold: Fold3
  
  Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
  ... reducing initialization grid to 10 rows.
  
  Registering parallel backend using 2 cores.
  
  Running initial scoring function 10 times in 2 thread(s)...  3.26 seconds
  
  Starting Epoch 1 
    1) Fitting Gaussian Process...
    2) Running local optimum search...        2.16 seconds
    3) Running FUN 2 times in 2 thread(s)...  0.27 seconds
  [ FAIL 0 | WARN 0 | SKIP 1 | PASS 17 ]
  
  ══ Skipped tests (1) ═══════════════════════════════════════════════════════════
  • On CRAN (1): 'test-lints.R:10:5'
  
  [ FAIL 0 | WARN 0 | SKIP 1 | PASS 17 ]
  > 
  > proc.time()
     user  system elapsed 
    73.93    1.40  213.39