Running ‘testthat.R’ [810s/512s]
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:  0.7121044    Val loss:  0.8738981 
  epoch:  20    Train loss:  0.6647047    Val loss:  0.7983801 
  epoch:  30    Train loss:  0.7058528    Val loss:  0.8091417 
  early stop at epoch:  33    Train loss:  0.5852336    Val loss:  0.8206522 
  epoch:  10    Train loss:  0.7405803    Val loss:  0.7180308 
  epoch:  20    Train loss:  0.7676055    Val loss:  0.5464001 
  epoch:  30    Train loss:  0.7100381    Val loss:  0.6477516 
  epoch:  40    Train loss:  0.7745836    Val loss:  0.6599262 
  epoch:  50    Train loss:  0.7100342    Val loss:  0.6902555 
  epoch:  60    Train loss:  0.7363845    Val loss:  0.6988116 
  epoch:  70    Train loss:  0.7564012    Val loss:  0.6074605 
  epoch:  80    Train loss:  0.7012565    Val loss:  0.6555059 
  epoch:  90    Train loss:  0.7759904    Val loss:  0.5840579 
  epoch:  100    Train loss:  0.8083107    Val loss:  0.6195951 
  epoch:  10    Train loss:  0.6867441    Val loss:  0.7476346 
  epoch:  20    Train loss:  0.7003227    Val loss:  0.7344114 
  epoch:  30    Train loss:  0.7748234    Val loss:  0.7582356 
  epoch:  40    Train loss:  0.8391043    Val loss:  0.5752739 
  epoch:  50    Train loss:  0.6970328    Val loss:  0.6576896 
  epoch:  60    Train loss:  0.8117089    Val loss:  0.7965838 
  epoch:  70    Train loss:  0.8208928    Val loss:  0.7142098 
  epoch:  80    Train loss:  0.8182777    Val loss:  0.6745295 
  early stop at epoch:  83    Train loss:  0.626428    Val loss:  0.8062148 
  epoch:  10    Train loss:  0.7681531    Val loss:  0.4345273 
  epoch:  20    Train loss:  0.7061042    Val loss:  0.6116007 
  epoch:  30    Train loss:  0.6449457    Val loss:  0.4929418 
  early stop at epoch:  33    Train loss:  0.7521734    Val loss:  0.5476325 
  time: 169.806 sec elapsed
  epoch:  10    Train loss:  0.7581715    Val loss:  0.7549369 
  epoch:  20    Train loss:  0.7228208    Val loss:  0.7565721 
  epoch:  30    Train loss:  0.6780602    Val loss:  0.8085259 
  early stop at epoch:  30    Train loss:  0.6780602    Val loss:  0.8085259 
  epoch:  10    Train loss:  0.7191769    Val loss:  0.6434729 
  epoch:  20    Train loss:  0.7561649    Val loss:  0.6626661 
  epoch:  30    Train loss:  0.7414711    Val loss:  0.6474438 
  epoch:  40    Train loss:  0.7497154    Val loss:  0.672399 
  early stop at epoch:  47    Train loss:  0.7603556    Val loss:  0.6660957 
  epoch:  10    Train loss:  0.5300742    Val loss:  0.7875934 
  epoch:  20    Train loss:  0.6569842    Val loss:  0.6712412 
  epoch:  30    Train loss:  0.7157695    Val loss:  0.6765073 
  early stop at epoch:  31    Train loss:  0.5791271    Val loss:  0.7295901 
  epoch:  10    Train loss:  0.6931557    Val loss:  0.760524 
  epoch:  20    Train loss:  0.6867127    Val loss:  0.7636068 
  epoch:  30    Train loss:  0.7086079    Val loss:  0.7411101 
  early stop at epoch:  32    Train loss:  0.6865351    Val loss:  0.7804703 
  time: 84.227 sec elapsed
  epoch:  10    Train loss:  0.3464127    Val loss:  0.3956781 
  epoch:  20    Train loss:  0.3055397    Val loss:  0.3121882 
  epoch:  30    Train loss:  0.3247151    Val loss:  0.3612455 
  early stop at epoch:  37    Train loss:  0.2709752    Val loss:  0.4062977 
  epoch:  10    Train loss:  0.3075053    Val loss:  0.281049 
  epoch:  20    Train loss:  0.3822283    Val loss:  0.207809 
  epoch:  30    Train loss:  0.2934596    Val loss:  0.2954834 
  early stop at epoch:  34    Train loss:  0.2994382    Val loss:  0.4460763 
  epoch:  10    Train loss:  0.2314483    Val loss:  0.2353167 
  epoch:  20    Train loss:  0.3038726    Val loss:  0.1883104 
  epoch:  30    Train loss:  0.2402883    Val loss:  0.4811618 
  early stop at epoch:  30    Train loss:  0.2402883    Val loss:  0.4811618 
  epoch:  10    Train loss:  0.2933556    Val loss:  0.1137974 
  epoch:  20    Train loss:  0.2624763    Val loss:  0.2908985 
  epoch:  30    Train loss:  0.265702    Val loss:  0.4377804 
  early stop at epoch:  30    Train loss:  0.265702    Val loss:  0.4377804 
  time: 84.858 sec elapsed
  epoch:  10    Train loss:  0.45254    Val loss:  0.3624296 
  epoch:  20    Train loss:  0.45254    Val loss:  0.3624296 
  epoch:  30    Train loss:  0.45254    Val loss:  0.3624296 
  epoch:  40    Train loss:  0.4800861    Val loss:  0.3624296 
  epoch:  50    Train loss:  0.4859069    Val loss:  0.3624296 
  epoch:  60    Train loss:  0.4699273    Val loss:  0.3624296 
  epoch:  70    Train loss:  0.45254    Val loss:  0.3624296 
  epoch:  80    Train loss:  0.45254    Val loss:  0.3912924 
  epoch:  90    Train loss:  0.45254    Val loss:  0.3624296 
  epoch:  100    Train loss:  0.4680164    Val loss:  0.3584892 
  epoch:  10    Train loss:  0.7290625    Val loss:  0.4825133 
  epoch:  20    Train loss:  0.7290625    Val loss:  0.4825133 
  epoch:  30    Train loss:  0.7290625    Val loss:  0.4825133 
  epoch:  40    Train loss:  0.7290625    Val loss:  0.4825133 
  epoch:  50    Train loss:  0.7290625    Val loss:  0.4825133 
  epoch:  60    Train loss:  0.7290625    Val loss:  0.4825133 
  epoch:  70    Train loss:  0.7290625    Val loss:  0.5270677 
  epoch:  80    Train loss:  0.7290625    Val loss:  0.4825133 
  epoch:  90    Train loss:  0.7290625    Val loss:  0.4825133 
  epoch:  100    Train loss:  0.7377118    Val loss:  0.5083146 
  epoch:  10    Train loss:  0.6641891    Val loss:  0.7440383 
  epoch:  20    Train loss:  0.6422756    Val loss:  0.7448631 
  epoch:  30    Train loss:  0.6422756    Val loss:  0.7875497 
  early stop at epoch:  30    Train loss:  0.6422756    Val loss:  0.7875497 
  time: 63.591 sec elapsed
  epoch:  10    Train loss:  0.3059653    Val loss:  0.5984082 
  epoch:  20    Train loss:  0.3059653    Val loss:  0.5828748 
  epoch:  30    Train loss:  0.3059653    Val loss:  0.632029 
  early stop at epoch:  30    Train loss:  0.3059653    Val loss:  0.632029 
  epoch:  10    Train loss:  0.5614365    Val loss:  0.6828829 
  epoch:  20    Train loss:  0.5614365    Val loss:  0.6828829 
  epoch:  30    Train loss:  0.5614365    Val loss:  0.6743141 
  early stop at epoch:  32    Train loss:  0.5614365    Val loss:  0.7191811 
  epoch:  10    Train loss:  0.4835046    Val loss:  0.543282 
  epoch:  20    Train loss:  0.455659    Val loss:  0.543282 
  epoch:  30    Train loss:  0.4531441    Val loss:  0.5412884 
  early stop at epoch:  31    Train loss:  0.455659    Val loss:  0.6359497 
  time: 28.025 sec elapsed
  epoch:  10    Train loss:  0.5976714    Val loss:  0.5978465 
  epoch:  20    Train loss:  0.5403702    Val loss:  0.6070974 
  epoch:  30    Train loss:  0.5836074    Val loss:  0.6180539 
  early stop at epoch:  31    Train loss:  0.4748563    Val loss:  0.6246297 
  epoch:  10    Train loss:  0.2222364    Val loss:  0.5322675 
  epoch:  20    Train loss:  0.448808    Val loss:  0.4627358 
  epoch:  30    Train loss:  0.5165807    Val loss:  0.2300893 
  early stop at epoch:  31    Train loss:  0.2479967    Val loss:  0.5508928 
  epoch:  10    Train loss:  0.5367064    Val loss:  0.5506377 
  epoch:  20    Train loss:  0.5152416    Val loss:  0.6800253 
  epoch:  30    Train loss:  0.5114337    Val loss:  0.6186984 
  early stop at epoch:  31    Train loss:  0.499859    Val loss:  0.6220505 
  time: 71.783 sec elapsed
  random search: 163.426 sec elapsed
  [ FAIL 1 | WARN 67 | 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: 1.
  Caused by error in `pmap()`:
  i In index: 1.
  Caused by error in `training_function()`:
  ! not enough data for training
  
  [ FAIL 1 | WARN 67 | SKIP 0 | PASS 46 ]
  Error: Test failures
  Execution halted