Running ‘testthat.R’ [842s/517s]
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(spinner)
  > 
  > test_check("spinner")
  epoch:  10    Train loss:  0.7204121    Val loss:  0.7203274 
  epoch:  20    Train loss:  0.6296779    Val loss:  0.7302311 
  epoch:  30    Train loss:  0.8075095    Val loss:  0.7627564 
  epoch:  40    Train loss:  0.6625845    Val loss:  0.7967191 
  early stop at epoch:  40    Train loss:  0.6625845    Val loss:  0.7967191 
  epoch:  10    Train loss:  0.7151833    Val loss:  0.5440799 
  epoch:  20    Train loss:  0.6911519    Val loss:  0.5959554 
  epoch:  30    Train loss:  0.6927945    Val loss:  0.6695415 
  epoch:  40    Train loss:  0.751623    Val loss:  0.5734559 
  epoch:  50    Train loss:  0.7976046    Val loss:  0.5956052 
  epoch:  60    Train loss:  0.7538683    Val loss:  0.6761467 
  epoch:  70    Train loss:  0.8191086    Val loss:  0.5360289 
  early stop at epoch:  74    Train loss:  0.8203162    Val loss:  0.6210989 
  epoch:  10    Train loss:  0.6845793    Val loss:  0.6112297 
  epoch:  20    Train loss:  0.7940713    Val loss:  0.9094752 
  epoch:  30    Train loss:  0.7393802    Val loss:  0.9037513 
  early stop at epoch:  30    Train loss:  0.7393802    Val loss:  0.9037513 
  epoch:  10    Train loss:  0.6684072    Val loss:  0.769263 
  epoch:  20    Train loss:  0.68843    Val loss:  0.4726485 
  epoch:  30    Train loss:  0.7632083    Val loss:  0.4042826 
  epoch:  40    Train loss:  0.7304531    Val loss:  0.5822257 
  epoch:  50    Train loss:  0.7158087    Val loss:  0.5855912 
  epoch:  60    Train loss:  0.7468383    Val loss:  0.7975863 
  epoch:  70    Train loss:  0.7592491    Val loss:  0.3772056 
  epoch:  80    Train loss:  0.6885586    Val loss:  0.7985604 
  early stop at epoch:  87    Train loss:  0.6689662    Val loss:  0.8231781 
  time: 169.149 sec elapsed
  epoch:  10    Train loss:  0.6176803    Val loss:  0.63171 
  epoch:  20    Train loss:  0.7412597    Val loss:  0.7585567 
  epoch:  30    Train loss:  0.743888    Val loss:  0.7438254 
  early stop at epoch:  34    Train loss:  0.667655    Val loss:  0.7830914 
  epoch:  10    Train loss:  0.7845878    Val loss:  0.5987629 
  epoch:  20    Train loss:  0.7093925    Val loss:  0.5980781 
  epoch:  30    Train loss:  0.7922461    Val loss:  0.5836344 
  epoch:  40    Train loss:  0.7660909    Val loss:  0.5829992 
  epoch:  50    Train loss:  0.7537355    Val loss:  0.5705996 
  epoch:  60    Train loss:  0.7458642    Val loss:  0.6022186 
  early stop at epoch:  63    Train loss:  0.7740546    Val loss:  0.6061423 
  epoch:  10    Train loss:  0.6709067    Val loss:  0.5779042 
  epoch:  20    Train loss:  0.6432183    Val loss:  0.6304967 
  epoch:  30    Train loss:  0.6958638    Val loss:  0.6456637 
  early stop at epoch:  37    Train loss:  0.4278853    Val loss:  0.7298496 
  epoch:  10    Train loss:  0.6490998    Val loss:  0.8072621 
  epoch:  20    Train loss:  0.6196672    Val loss:  0.6969966 
  epoch:  30    Train loss:  0.6187429    Val loss:  0.79194 
  early stop at epoch:  30    Train loss:  0.6187429    Val loss:  0.79194 
  time: 92.432 sec elapsed
  epoch:  10    Train loss:  0.3301883    Val loss:  0.2502386 
  epoch:  20    Train loss:  0.3329349    Val loss:  0.3107572 
  epoch:  30    Train loss:  0.3524886    Val loss:  0.197439 
  early stop at epoch:  33    Train loss:  0.3217809    Val loss:  0.3757134 
  epoch:  10    Train loss:  0.3472048    Val loss:  0.2388925 
  epoch:  20    Train loss:  0.2989524    Val loss:  0.2965727 
  epoch:  30    Train loss:  0.3447234    Val loss:  0.4693904 
  early stop at epoch:  30    Train loss:  0.3447234    Val loss:  0.4693904 
  epoch:  10    Train loss:  0.2841241    Val loss:  0.3900169 
  epoch:  20    Train loss:  0.2636533    Val loss:  0.3575157 
  epoch:  30    Train loss:  0.2474763    Val loss:  0.2139024 
  early stop at epoch:  34    Train loss:  0.228196    Val loss:  0.3763213 
  epoch:  10    Train loss:  0.3501405    Val loss:  0.2388428 
  epoch:  20    Train loss:  0.3189723    Val loss:  0.3690073 
  epoch:  30    Train loss:  0.2649272    Val loss:  0.2128325 
  early stop at epoch:  33    Train loss:  0.2953162    Val loss:  0.4754127 
  time: 70.52 sec elapsed
  epoch:  10    Train loss:  0.3482861    Val loss:  0.439102 
  epoch:  20    Train loss:  0.3482861    Val loss:  0.442521 
  epoch:  30    Train loss:  0.3482861    Val loss:  0.442521 
  epoch:  40    Train loss:  0.3482861    Val loss:  0.442521 
  early stop at epoch:  42    Train loss:  0.3482861    Val loss:  0.4489033 
  epoch:  10    Train loss:  0.6628533    Val loss:  0.4969321 
  epoch:  20    Train loss:  0.6628533    Val loss:  0.4969321 
  epoch:  30    Train loss:  0.6628533    Val loss:  0.4969321 
  epoch:  40    Train loss:  0.6628533    Val loss:  0.4969321 
  epoch:  50    Train loss:  0.6628533    Val loss:  0.4969321 
  epoch:  60    Train loss:  0.6628533    Val loss:  0.4969321 
  epoch:  70    Train loss:  0.6628533    Val loss:  0.4837587 
  epoch:  80    Train loss:  0.6628533    Val loss:  0.4969321 
  epoch:  90    Train loss:  0.6628533    Val loss:  0.5252546 
  epoch:  100    Train loss:  0.6628533    Val loss:  0.4969321 
  epoch:  10    Train loss:  0.4699441    Val loss:  0.47624 
  epoch:  20    Train loss:  0.5934506    Val loss:  0.477994 
  epoch:  30    Train loss:  0.4686506    Val loss:  0.477994 
  early stop at epoch:  33    Train loss:  0.4699441    Val loss:  0.5299301 
  time: 41.394 sec elapsed
  epoch:  10    Train loss:  0.6049055    Val loss:  0.6137345 
  epoch:  20    Train loss:  0.6049055    Val loss:  0.6395074 
  epoch:  30    Train loss:  0.6049055    Val loss:  0.6102574 
  early stop at epoch:  33    Train loss:  0.6016685    Val loss:  0.6388255 
  epoch:  10    Train loss:  0.7894533    Val loss:  0.7001863 
  epoch:  20    Train loss:  0.75912    Val loss:  0.6708778 
  epoch:  30    Train loss:  0.75912    Val loss:  0.665655 
  epoch:  40    Train loss:  0.75912    Val loss:  0.6708778 
  epoch:  50    Train loss:  0.75912    Val loss:  0.6708778 
  epoch:  60    Train loss:  0.75912    Val loss:  0.6708778 
  epoch:  70    Train loss:  0.75912    Val loss:  0.6708778 
  epoch:  80    Train loss:  0.75912    Val loss:  0.6844155 
  epoch:  90    Train loss:  0.75912    Val loss:  0.6747321 
  early stop at epoch:  92    Train loss:  0.7888336    Val loss:  0.6859844 
  epoch:  10    Train loss:  0.6611488    Val loss:  0.6663996 
  epoch:  20    Train loss:  0.6538801    Val loss:  0.635769 
  epoch:  30    Train loss:  0.6611488    Val loss:  0.6898336 
  epoch:  40    Train loss:  0.6611488    Val loss:  0.622568 
  epoch:  50    Train loss:  0.6575313    Val loss:  0.635769 
  early stop at epoch:  53    Train loss:  0.6837438    Val loss:  0.7485217 
  time: 45.076 sec elapsed
  epoch:  10    Train loss:  0.6537183    Val loss:  0.6717774 
  epoch:  20    Train loss:  0.7236333    Val loss:  0.6631523 
  epoch:  30    Train loss:  0.6727129    Val loss:  0.6678619 
  early stop at epoch:  33    Train loss:  0.7521129    Val loss:  0.65158 
  epoch:  10    Train loss:  0.4618223    Val loss:  0.4949274 
  epoch:  20    Train loss:  0.4688416    Val loss:  0.5466486 
  epoch:  30    Train loss:  0.4598603    Val loss:  0.5273082 
  early stop at epoch:  31    Train loss:  0.3738953    Val loss:  0.5442909 
  epoch:  10    Train loss:  0.6622298    Val loss:  0.5430651 
  epoch:  20    Train loss:  0.6763593    Val loss:  0.5865301 
  epoch:  30    Train loss:  0.6352437    Val loss:  0.5887785 
  early stop at epoch:  39    Train loss:  0.6946709    Val loss:  0.5821269 
  time: 65.37 sec elapsed
  random search: 151.853 sec elapsed
  epoch:  10    Train loss:  0.07086422    Val loss:  0.1314432 
  epoch:  20    Train loss:  0.07086422    Val loss:  0.07086423 
  epoch:  30    Train loss:  0.07086422    Val loss:  0.07086423 
  early stop at epoch:  35    Train loss:  0.07086422    Val loss:  0.1892674 
  epoch:  10    Train loss:  0.201456    Val loss:  0.1184543 
  epoch:  20    Train loss:  0.1184542    Val loss:  0.1184543 
  epoch:  30    Train loss:  0.1184542    Val loss:  0.1155253 
  early stop at epoch:  36    Train loss:  0.1184542    Val loss:  0.1541383 
  epoch:  10    Train loss:  0.08458349    Val loss:  0.06303233 
  epoch:  20    Train loss:  0.1653197    Val loss:  0.05270578 
  epoch:  30    Train loss:  0.13353    Val loss:  0.115967 
  early stop at epoch:  36    Train loss:  0.1653198    Val loss:  0.3284115 
  time: 26.266 sec elapsed
  [ FAIL 1 | WARN 69 | SKIP 0 | PASS 46 ]
  
  ══ Failed tests ════════════════════════════════════════════════════════════════
  ── Error ('test.R:89:13'): Correct outcome format and size for base outcome3 ───
  <purrr_error_indexed/rlang_error/error/condition>
  Error in `purrr::pmap(hyper_params, ~spinner(graph, target, node_labels, 
      edge_labels, context_labels, direction = ..1, sampling = NA, 
      threshold = 0.01, method = ..2, node_embedding_size = ..13, 
      edge_embedding_size = ..14, context_embedding_size = ..15, 
      update_order = ..3, n_layers = ..4, skip_shortcut = ..5, 
      forward_layer = ..6, forward_activation = ..7, forward_drop = ..8, 
      mode = ..9, optimization = ..10, epochs, lr = ..11, patience, 
      weight_decay = ..12, reps, folds, holdout, verbose, seed))`: i In index: 2.
  Caused by error in `pmap()`:
  i In index: 1.
  Caused by error in `training_function()`:
  ! not enough data for training
  
  [ FAIL 1 | WARN 69 | SKIP 0 | PASS 46 ]
  Error: Test failures
  Execution halted