Running ‘testthat.R’ [13m/14m]
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:  0.7451203    Val loss:  0.7473106 
  epoch:  20    Train loss:  0.5632022    Val loss:  0.720567 
  epoch:  30    Train loss:  0.6956195    Val loss:  0.7913723 
  early stop at epoch:  31    Train loss:  0.6732105    Val loss:  0.8386507 
  epoch:  10    Train loss:  0.7786402    Val loss:  0.6119318 
  epoch:  20    Train loss:  0.769654    Val loss:  0.5747024 
  epoch:  30    Train loss:  0.72762    Val loss:  0.5379636 
  epoch:  40    Train loss:  0.7138624    Val loss:  0.6186344 
  epoch:  50    Train loss:  0.7116687    Val loss:  0.5481068 
  epoch:  60    Train loss:  0.7106085    Val loss:  0.5130883 
  early stop at epoch:  63    Train loss:  0.7666508    Val loss:  0.6119152 
  epoch:  10    Train loss:  0.5973336    Val loss:  0.4527318 
  epoch:  20    Train loss:  0.7366181    Val loss:  0.7971062 
  epoch:  30    Train loss:  0.639971    Val loss:  0.6702385 
  epoch:  40    Train loss:  0.7176137    Val loss:  0.6666783 
  early stop at epoch:  44    Train loss:  0.6911675    Val loss:  0.8519312 
  epoch:  10    Train loss:  0.5615329    Val loss:  0.8213017 
  epoch:  20    Train loss:  0.5785059    Val loss:  0.7469137 
  epoch:  30    Train loss:  0.61052    Val loss:  0.7325623 
  early stop at epoch:  35    Train loss:  0.5450587    Val loss:  0.824356 
  time: 183.033 sec elapsed
  epoch:  10    Train loss:  0.7396947    Val loss:  0.7295969 
  epoch:  20    Train loss:  0.5835667    Val loss:  0.706398 
  epoch:  30    Train loss:  0.4514529    Val loss:  0.7241919 
  early stop at epoch:  36    Train loss:  0.5111768    Val loss:  0.7475002 
  epoch:  10    Train loss:  0.7340996    Val loss:  0.6305407 
  epoch:  20    Train loss:  0.6757241    Val loss:  0.6533249 
  epoch:  30    Train loss:  0.7155366    Val loss:  0.6247407 
  epoch:  40    Train loss:  0.6956353    Val loss:  0.6137447 
  early stop at epoch:  43    Train loss:  0.7410268    Val loss:  0.6420394 
  epoch:  10    Train loss:  0.6994811    Val loss:  0.8271866 
  epoch:  20    Train loss:  0.6776162    Val loss:  0.707306 
  epoch:  30    Train loss:  0.6239297    Val loss:  0.7597255 
  early stop at epoch:  30    Train loss:  0.6239297    Val loss:  0.7597255 
  epoch:  10    Train loss:  0.6553012    Val loss:  0.6653584 
  epoch:  20    Train loss:  0.6567004    Val loss:  0.6582726 
  epoch:  30    Train loss:  0.6568758    Val loss:  0.6821289 
  early stop at epoch:  33    Train loss:  0.6775398    Val loss:  0.7217444 
  time: 142.357 sec elapsed
  epoch:  10    Train loss:  0.385441    Val loss:  0.3301069 
  epoch:  20    Train loss:  0.2983988    Val loss:  0.2988058 
  epoch:  30    Train loss:  0.3433583    Val loss:  0.2885988 
  early stop at epoch:  31    Train loss:  0.2811543    Val loss:  0.4212732 
  epoch:  10    Train loss:  0.3849025    Val loss:  0.5268335 
  epoch:  20    Train loss:  0.2849826    Val loss:  0.277081 
  epoch:  30    Train loss:  0.35402    Val loss:  0.2355604 
  epoch:  40    Train loss:  0.2922735    Val loss:  0.3436319 
  early stop at epoch:  49    Train loss:  0.3183985    Val loss:  0.4423093 
  epoch:  10    Train loss:  0.2352209    Val loss:  0.3419928 
  epoch:  20    Train loss:  0.2343432    Val loss:  0.3757044 
  epoch:  30    Train loss:  0.2642074    Val loss:  0.2987434 
  early stop at epoch:  33    Train loss:  0.2322209    Val loss:  0.3507796 
  epoch:  10    Train loss:  0.2172693    Val loss:  0.4195762 
  epoch:  20    Train loss:  0.3127921    Val loss:  0.399893 
  epoch:  30    Train loss:  0.2535014    Val loss:  0.1273002 
  epoch:  40    Train loss:  0.2421198    Val loss:  0.270889 
  early stop at epoch:  41    Train loss:  0.2685271    Val loss:  0.3435382 
  time: 152.029 sec elapsed
  epoch:  10    Train loss:  0.4284516    Val loss:  0.5563538 
  epoch:  20    Train loss:  0.4284516    Val loss:  0.5584979 
  epoch:  30    Train loss:  0.4284516    Val loss:  0.5584979 
  early stop at epoch:  32    Train loss:  0.4284516    Val loss:  0.5615466 
  epoch:  10    Train loss:  0.7546854    Val loss:  0.616855 
  epoch:  20    Train loss:  0.7546854    Val loss:  0.5663382 
  epoch:  30    Train loss:  0.7546854    Val loss:  0.5663382 
  epoch:  40    Train loss:  0.7546854    Val loss:  0.5663382 
  epoch:  50    Train loss:  0.7546854    Val loss:  0.5663382 
  epoch:  60    Train loss:  0.7546854    Val loss:  0.5663382 
  epoch:  70    Train loss:  0.7546854    Val loss:  0.565825 
  epoch:  80    Train loss:  0.7546854    Val loss:  0.6017393 
  epoch:  90    Train loss:  0.7546854    Val loss:  0.5663382 
  epoch:  100    Train loss:  0.7546854    Val loss:  0.567507 
  epoch:  10    Train loss:  0.3511041    Val loss:  0.3365679 
  epoch:  20    Train loss:  0.3511041    Val loss:  0.3872628 
  epoch:  30    Train loss:  0.3619529    Val loss:  0.3365679 
  early stop at epoch:  38    Train loss:  0.3511041    Val loss:  0.3874785 
  time: 69.58 sec elapsed
  epoch:  10    Train loss:  0.07086423    Val loss:  0.1418203 
  epoch:  20    Train loss:  0.07086423    Val loss:  0.07086422 
  epoch:  30    Train loss:  0.07086423    Val loss:  0.1445347 
  early stop at epoch:  35    Train loss:  0.07086423    Val loss:  0.1188352 
  epoch:  10    Train loss:  0.2014559    Val loss:  0.1184543 
  epoch:  20    Train loss:  0.1184543    Val loss:  0.1184543 
  epoch:  30    Train loss:  0.1184543    Val loss:  0.1524345 
  early stop at epoch:  36    Train loss:  0.1184543    Val loss:  0.1553825 
  epoch:  10    Train loss:  0.0845835    Val loss:  0.2376755 
  epoch:  20    Train loss:  0.2416725    Val loss:  0.05270578 
  epoch:  30    Train loss:  0.13353    Val loss:  0.05219454 
  early stop at epoch:  36    Train loss:  0.1653197    Val loss:  0.3109783 
  time: 43.042 sec elapsed
  epoch:  10    Train loss:  0.2161914    Val loss:  0.7818606 
  epoch:  20    Train loss:  0.2161914    Val loss:  0.798671 
  epoch:  30    Train loss:  0.2161914    Val loss:  0.801501 
  early stop at epoch:  30    Train loss:  0.2161914    Val loss:  0.801501 
  epoch:  10    Train loss:  0.4239533    Val loss:  0.8702489 
  epoch:  20    Train loss:  0.4289955    Val loss:  0.857953 
  epoch:  30    Train loss:  0.4239533    Val loss:  0.8684691 
  epoch:  40    Train loss:  0.4512812    Val loss:  0.8878608 
  early stop at epoch:  40    Train loss:  0.4512812    Val loss:  0.8878608 
  epoch:  10    Train loss:  0.8651618    Val loss:  0.4082122 
  epoch:  20    Train loss:  0.854362    Val loss:  0.503502 
  epoch:  30    Train loss:  0.8520928    Val loss:  0.4082032 
  epoch:  40    Train loss:  0.8692899    Val loss:  0.3985529 
  epoch:  50    Train loss:  0.8475307    Val loss:  0.4176294 
  epoch:  60    Train loss:  0.8679323    Val loss:  0.6443841 
  epoch:  70    Train loss:  0.8437038    Val loss:  0.40443 
  epoch:  80    Train loss:  0.8330722    Val loss:  0.5244628 
  epoch:  90    Train loss:  0.8330722    Val loss:  0.4449609 
  epoch:  100    Train loss:  0.847612    Val loss:  0.40443 
  time: 83.461 sec elapsed
  epoch:  10    Train loss:  0.5660917    Val loss:  0.8301636 
  epoch:  20    Train loss:  0.6195392    Val loss:  0.8578303 
  epoch:  30    Train loss:  0.709184    Val loss:  0.8583699 
  early stop at epoch:  33    Train loss:  0.5423399    Val loss:  0.8843293 
  epoch:  10    Train loss:  0.7098332    Val loss:  0.9303793 
  epoch:  20    Train loss:  0.7477745    Val loss:  0.9189134 
  epoch:  30    Train loss:  0.7284306    Val loss:  0.9126461 
  early stop at epoch:  37    Train loss:  0.733092    Val loss:  0.919122 
  epoch:  10    Train loss:  0.8833328    Val loss:  0.5879502 
  epoch:  20    Train loss:  0.8571532    Val loss:  0.5768709 
  epoch:  30    Train loss:  0.8766273    Val loss:  0.6631085 
  epoch:  40    Train loss:  0.8598965    Val loss:  0.6193245 
  early stop at epoch:  49    Train loss:  0.908049    Val loss:  0.5988597 
  time: 148.872 sec elapsed
  random search: 275.411 sec elapsed
  [ FAIL 1 | WARN 63 | SKIP 0 | PASS 46 ]
  
  ══ Failed tests ════════════════════════════════════════════════════════════════
  ── Error ('test.R:72:13'): 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 63 | SKIP 0 | PASS 46 ]
  Error: Test failures
  Execution halted