Running ‘testthat.R’ [888s/538s]
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:  0.8042752    Val loss:  0.762619 
  epoch:  20    Train loss:  0.7497472    Val loss:  0.7153819 
  epoch:  30    Train loss:  0.7016802    Val loss:  0.7248967 
  early stop at epoch:  32    Train loss:  0.5935974    Val loss:  0.7635115 
  epoch:  10    Train loss:  0.7372665    Val loss:  0.7102394 
  epoch:  20    Train loss:  0.7129967    Val loss:  0.7795119 
  epoch:  30    Train loss:  0.7660335    Val loss:  0.6977674 
  early stop at epoch:  34    Train loss:  0.7016211    Val loss:  0.8159302 
  epoch:  10    Train loss:  0.6988701    Val loss:  0.8421989 
  epoch:  20    Train loss:  0.6796751    Val loss:  0.6213654 
  epoch:  30    Train loss:  0.7436727    Val loss:  0.5848724 
  early stop at epoch:  34    Train loss:  0.765071    Val loss:  0.9200504 
  epoch:  10    Train loss:  0.6588928    Val loss:  0.5740735 
  epoch:  20    Train loss:  0.531315    Val loss:  0.5606734 
  epoch:  30    Train loss:  0.6640955    Val loss:  0.5343564 
  epoch:  40    Train loss:  0.619541    Val loss:  0.5988131 
  early stop at epoch:  43    Train loss:  0.6022825    Val loss:  0.6977724 
  time: 93.914 sec elapsed
  epoch:  10    Train loss:  0.7081513    Val loss:  0.7781819 
  epoch:  20    Train loss:  0.654664    Val loss:  0.827737 
  epoch:  30    Train loss:  0.5709594    Val loss:  0.8031073 
  early stop at epoch:  30    Train loss:  0.5709594    Val loss:  0.8031073 
  epoch:  10    Train loss:  0.7680451    Val loss:  0.7585026 
  epoch:  20    Train loss:  0.7695665    Val loss:  0.7503206 
  epoch:  30    Train loss:  0.8147178    Val loss:  0.7352452 
  epoch:  40    Train loss:  0.7652489    Val loss:  0.6908006 
  early stop at epoch:  42    Train loss:  0.8474046    Val loss:  0.7648358 
  epoch:  10    Train loss:  0.7133324    Val loss:  0.7668064 
  epoch:  20    Train loss:  0.6768425    Val loss:  0.6844565 
  epoch:  30    Train loss:  0.6395798    Val loss:  0.7512909 
  early stop at epoch:  30    Train loss:  0.6395798    Val loss:  0.7512909 
  epoch:  10    Train loss:  0.7350594    Val loss:  0.6476609 
  epoch:  20    Train loss:  0.7119259    Val loss:  0.6588126 
  epoch:  30    Train loss:  0.6146967    Val loss:  0.7144643 
  early stop at epoch:  30    Train loss:  0.6146967    Val loss:  0.7144643 
  time: 92.283 sec elapsed
  epoch:  10    Train loss:  0.3393962    Val loss:  0.3114486 
  epoch:  20    Train loss:  0.3320459    Val loss:  0.2753577 
  epoch:  30    Train loss:  0.3778413    Val loss:  0.380605 
  early stop at epoch:  31    Train loss:  0.2766331    Val loss:  0.3878916 
  epoch:  10    Train loss:  0.3747157    Val loss:  0.5435675 
  epoch:  20    Train loss:  0.289193    Val loss:  0.225682 
  epoch:  30    Train loss:  0.3258832    Val loss:  0.2549182 
  epoch:  40    Train loss:  0.2962081    Val loss:  0.3649592 
  early stop at epoch:  41    Train loss:  0.2769096    Val loss:  0.370787 
  epoch:  10    Train loss:  0.2472248    Val loss:  0.2361955 
  epoch:  20    Train loss:  0.2726143    Val loss:  0.4811167 
  epoch:  30    Train loss:  0.2406069    Val loss:  0.2214216 
  early stop at epoch:  32    Train loss:  0.2437847    Val loss:  0.4102204 
  epoch:  10    Train loss:  0.3107558    Val loss:  0.2437524 
  epoch:  20    Train loss:  0.2918636    Val loss:  0.2498634 
  epoch:  30    Train loss:  0.3250392    Val loss:  0.571016 
  early stop at epoch:  30    Train loss:  0.3250392    Val loss:  0.571016 
  time: 94.711 sec elapsed
  epoch:  10    Train loss:  0.4367557    Val loss:  0.5376367 
  epoch:  20    Train loss:  0.4367557    Val loss:  0.5402423 
  epoch:  30    Train loss:  0.4367557    Val loss:  0.5402423 
  early stop at epoch:  32    Train loss:  0.4367557    Val loss:  0.5480005 
  epoch:  10    Train loss:  0.07086423    Val loss:  0.08353268 
  epoch:  20    Train loss:  0.07086423    Val loss:  0.07086422 
  epoch:  30    Train loss:  0.07086423    Val loss:  0.07086422 
  early stop at epoch:  35    Train loss:  0.07086423    Val loss:  0.2079035 
  epoch:  10    Train loss:  0.2014559    Val loss:  0.1184543 
  epoch:  20    Train loss:  0.1184542    Val loss:  0.1184543 
  epoch:  30    Train loss:  0.1184542    Val loss:  0.1531882 
  early stop at epoch:  36    Train loss:  0.1184542    Val loss:  0.1565416 
  epoch:  10    Train loss:  0.08458351    Val loss:  0.04578351 
  epoch:  20    Train loss:  0.1653197    Val loss:  0.05270579 
  epoch:  30    Train loss:  0.13353    Val loss:  0.05219597 
  early stop at epoch:  36    Train loss:  0.1653198    Val loss:  0.3318663 
  time: 24.737 sec elapsed
  epoch:  10    Train loss:  0.135906    Val loss:  0.8111857 
  epoch:  20    Train loss:  0.135906    Val loss:  0.8185331 
  epoch:  30    Train loss:  0.1921211    Val loss:  0.8335539 
  early stop at epoch:  32    Train loss:  0.135906    Val loss:  0.8496706 
  epoch:  10    Train loss:  0.957583    Val loss:  0.3403419 
  epoch:  20    Train loss:  0.957583    Val loss:  0.3926123 
  epoch:  30    Train loss:  0.957583    Val loss:  0.3665439 
  epoch:  40    Train loss:  0.9579064    Val loss:  0.3958067 
  epoch:  50    Train loss:  0.957583    Val loss:  0.3403419 
  epoch:  60    Train loss:  0.9605089    Val loss:  0.3758774 
  epoch:  70    Train loss:  0.957583    Val loss:  0.3448422 
  epoch:  80    Train loss:  0.957583    Val loss:  0.4027291 
  epoch:  90    Train loss:  0.9518603    Val loss:  0.3403419 
  epoch:  100    Train loss:  0.957583    Val loss:  0.3571404 
  epoch:  10    Train loss:  0.7823091    Val loss:  0.4782484 
  epoch:  20    Train loss:  0.8316918    Val loss:  0.4746718 
  epoch:  30    Train loss:  0.8295838    Val loss:  0.4761661 
  epoch:  40    Train loss:  0.7988396    Val loss:  0.6226767 
  epoch:  50    Train loss:  0.78803    Val loss:  0.5520392 
  epoch:  60    Train loss:  0.7921165    Val loss:  0.5193998 
  epoch:  70    Train loss:  0.7916048    Val loss:  0.4746718 
  epoch:  80    Train loss:  0.8356276    Val loss:  0.6702973 
  epoch:  90    Train loss:  0.7965561    Val loss:  0.6271805 
  epoch:  100    Train loss:  0.7886027    Val loss:  0.4151983 
  time: 75.695 sec elapsed
  epoch:  10    Train loss:  0.1640261    Val loss:  0.8173639 
  epoch:  20    Train loss:  0.1908239    Val loss:  0.8540781 
  epoch:  30    Train loss:  0.2171751    Val loss:  0.8329006 
  early stop at epoch:  31    Train loss:  0.2224745    Val loss:  0.8428413 
  epoch:  10    Train loss:  0.9544982    Val loss:  0.5370396 
  epoch:  20    Train loss:  0.9450549    Val loss:  0.5678437 
  epoch:  30    Train loss:  0.9565475    Val loss:  0.5246407 
  epoch:  40    Train loss:  0.952684    Val loss:  0.5688892 
  epoch:  50    Train loss:  0.9508348    Val loss:  0.5698899 
  epoch:  60    Train loss:  0.9348406    Val loss:  0.5904227 
  epoch:  70    Train loss:  0.9345868    Val loss:  0.6015227 
  epoch:  80    Train loss:  0.9162596    Val loss:  0.5582333 
  epoch:  90    Train loss:  0.9743548    Val loss:  0.5615342 
  epoch:  100    Train loss:  0.940361    Val loss:  0.5575107 
  epoch:  10    Train loss:  0.8623738    Val loss:  0.6755317 
  epoch:  20    Train loss:  0.830516    Val loss:  0.7151622 
  epoch:  30    Train loss:  0.8443766    Val loss:  0.6674847 
  epoch:  40    Train loss:  0.8159938    Val loss:  0.7034666 
  epoch:  50    Train loss:  0.8317666    Val loss:  0.701517 
  epoch:  60    Train loss:  0.8668987    Val loss:  0.765408 
  epoch:  70    Train loss:  0.8553956    Val loss:  0.7419701 
  epoch:  80    Train loss:  0.8404363    Val loss:  0.7189943 
  epoch:  90    Train loss:  0.8641479    Val loss:  0.7037748 
  epoch:  100    Train loss:  0.8318632    Val loss:  0.6146955 
  time: 141.608 sec elapsed
  random search: 242.049 sec elapsed
  [ FAIL 1 | WARN 60 | 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: 1.
  Caused by error in `pmap()`:
  i In index: 2.
  Caused by error in `training_function()`:
  ! not enough data for training
  
  [ FAIL 1 | WARN 60 | SKIP 0 | PASS 46 ]
  Error: Test failures
  Execution halted