Running ‘testthat.R’ [935s/598s]
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:  0.7359471    Val loss:  0.8005437 
  epoch:  20    Train loss:  0.7279664    Val loss:  0.8677916 
  epoch:  30    Train loss:  0.6160991    Val loss:  0.8721052 
  early stop at epoch:  39    Train loss:  0.6599072    Val loss:  0.8347068 
  epoch:  10    Train loss:  0.8048813    Val loss:  0.6564061 
  epoch:  20    Train loss:  0.7364646    Val loss:  0.5345602 
  epoch:  30    Train loss:  0.7827219    Val loss:  0.6971142 
  epoch:  40    Train loss:  0.818076    Val loss:  0.6821269 
  early stop at epoch:  40    Train loss:  0.818076    Val loss:  0.6821269 
  epoch:  10    Train loss:  0.715647    Val loss:  0.5961463 
  epoch:  20    Train loss:  0.7338654    Val loss:  0.6253489 
  epoch:  30    Train loss:  0.617215    Val loss:  0.2499257 
  epoch:  40    Train loss:  0.7360034    Val loss:  0.50854 
  epoch:  50    Train loss:  0.6699195    Val loss:  0.2757758 
  epoch:  60    Train loss:  0.8652055    Val loss:  0.5542819 
  early stop at epoch:  60    Train loss:  0.8652055    Val loss:  0.5542819 
  epoch:  10    Train loss:  0.7168208    Val loss:  0.6446075 
  epoch:  20    Train loss:  0.6988077    Val loss:  0.3690408 
  epoch:  30    Train loss:  0.7002189    Val loss:  0.4469593 
  early stop at epoch:  33    Train loss:  0.7012615    Val loss:  0.8720945 
  time: 131.414 sec elapsed
  epoch:  10    Train loss:  0.7952355    Val loss:  0.7773126 
  epoch:  20    Train loss:  0.7934828    Val loss:  0.7769289 
  epoch:  30    Train loss:  0.7691078    Val loss:  0.7712269 
  epoch:  40    Train loss:  0.7758812    Val loss:  0.7234622 
  epoch:  50    Train loss:  0.7617493    Val loss:  0.7523319 
  early stop at epoch:  51    Train loss:  0.7208019    Val loss:  0.7536502 
  epoch:  10    Train loss:  0.7076916    Val loss:  0.7333204 
  epoch:  20    Train loss:  0.7440391    Val loss:  0.7167297 
  epoch:  30    Train loss:  0.7502384    Val loss:  0.7478564 
  early stop at epoch:  31    Train loss:  0.7232628    Val loss:  0.7609153 
  epoch:  10    Train loss:  0.7217849    Val loss:  0.615976 
  epoch:  20    Train loss:  0.7082433    Val loss:  0.8158655 
  epoch:  30    Train loss:  0.6632234    Val loss:  0.6834738 
  epoch:  40    Train loss:  0.703834    Val loss:  0.6515464 
  epoch:  50    Train loss:  0.6984853    Val loss:  0.62675 
  epoch:  60    Train loss:  0.7279441    Val loss:  0.5711209 
  epoch:  70    Train loss:  0.733191    Val loss:  0.6625191 
  early stop at epoch:  74    Train loss:  0.6653969    Val loss:  0.8329002 
  epoch:  10    Train loss:  0.7041363    Val loss:  0.7611644 
  epoch:  20    Train loss:  0.7335375    Val loss:  0.6539726 
  epoch:  30    Train loss:  0.7327568    Val loss:  0.7083677 
  epoch:  40    Train loss:  0.7086775    Val loss:  0.7811113 
  epoch:  50    Train loss:  0.7036648    Val loss:  0.7160487 
  epoch:  60    Train loss:  0.7378365    Val loss:  0.641631 
  epoch:  70    Train loss:  0.7135801    Val loss:  0.7216411 
  epoch:  80    Train loss:  0.6838059    Val loss:  0.5612752 
  early stop at epoch:  88    Train loss:  0.6682171    Val loss:  0.7569311 
  time: 186.611 sec elapsed
  epoch:  10    Train loss:  0.3320775    Val loss:  0.3634587 
  epoch:  20    Train loss:  0.3286402    Val loss:  0.2477289 
  epoch:  30    Train loss:  0.3647017    Val loss:  0.3916861 
  early stop at epoch:  31    Train loss:  0.3105881    Val loss:  0.4460061 
  epoch:  10    Train loss:  0.3819743    Val loss:  0.4948697 
  epoch:  20    Train loss:  0.3115179    Val loss:  0.4294521 
  epoch:  30    Train loss:  0.3098654    Val loss:  0.3476937 
  early stop at epoch:  32    Train loss:  0.3510645    Val loss:  0.4821721 
  epoch:  10    Train loss:  0.2398214    Val loss:  0.465057 
  epoch:  20    Train loss:  0.2649077    Val loss:  0.1426091 
  epoch:  30    Train loss:  0.2349349    Val loss:  0.3193471 
  early stop at epoch:  34    Train loss:  0.1954198    Val loss:  0.3310946 
  epoch:  10    Train loss:  0.3241543    Val loss:  0.352525 
  epoch:  20    Train loss:  0.2922578    Val loss:  0.5942231 
  epoch:  30    Train loss:  0.2952164    Val loss:  0.170181 
  early stop at epoch:  33    Train loss:  0.274417    Val loss:  0.4186837 
  time: 104.005 sec elapsed
  epoch:  10    Train loss:  1.130424    Val loss:  0.4100948 
  epoch:  20    Train loss:  1.130424    Val loss:  0.4207122 
  epoch:  30    Train loss:  1.130424    Val loss:  0.4207122 
  epoch:  40    Train loss:  1.130424    Val loss:  0.4207122 
  epoch:  50    Train loss:  1.130424    Val loss:  0.4207122 
  epoch:  60    Train loss:  1.130424    Val loss:  0.4207122 
  epoch:  70    Train loss:  1.130424    Val loss:  0.4207122 
  epoch:  80    Train loss:  1.130424    Val loss:  0.4207122 
  epoch:  90    Train loss:  1.130424    Val loss:  0.4207122 
  epoch:  100    Train loss:  1.130424    Val loss:  0.4207122 
  epoch:  10    Train loss:  0.5349873    Val loss:  0.6498036 
  epoch:  20    Train loss:  0.5349873    Val loss:  0.6498036 
  epoch:  30    Train loss:  0.5362017    Val loss:  0.6498036 
  early stop at epoch:  32    Train loss:  0.5349873    Val loss:  0.6725306 
  epoch:  10    Train loss:  0.3557965    Val loss:  0.3248608 
  epoch:  20    Train loss:  0.3557965    Val loss:  0.3275437 
  epoch:  30    Train loss:  0.3582969    Val loss:  0.3248608 
  early stop at epoch:  34    Train loss:  0.3539272    Val loss:  0.3960908 
  time: 46.065 sec elapsed
  epoch:  10    Train loss:  0.496438    Val loss:  0.5688681 
  epoch:  20    Train loss:  0.496438    Val loss:  0.5508469 
  epoch:  30    Train loss:  0.496438    Val loss:  0.5787589 
  early stop at epoch:  30    Train loss:  0.496438    Val loss:  0.5787589 
  epoch:  10    Train loss:  0.6628702    Val loss:  0.6986294 
  epoch:  20    Train loss:  0.6628702    Val loss:  0.7014998 
  epoch:  30    Train loss:  0.6628702    Val loss:  0.7261751 
  early stop at epoch:  30    Train loss:  0.6628702    Val loss:  0.7261751 
  epoch:  10    Train loss:  0.5242085    Val loss:  0.5927282 
  epoch:  20    Train loss:  0.5242085    Val loss:  0.650591 
  epoch:  30    Train loss:  0.5608118    Val loss:  0.6522405 
  early stop at epoch:  30    Train loss:  0.5608118    Val loss:  0.6522405 
  time: 25.115 sec elapsed
  epoch:  10    Train loss:  0.4579934    Val loss:  0.6754975 
  epoch:  20    Train loss:  0.3652965    Val loss:  0.665134 
  epoch:  30    Train loss:  0.4382766    Val loss:  0.6552865 
  early stop at epoch:  31    Train loss:  0.419241    Val loss:  0.6954612 
  epoch:  10    Train loss:  0.4989539    Val loss:  0.3964368 
  epoch:  20    Train loss:  0.4471914    Val loss:  0.5467939 
  epoch:  30    Train loss:  0.4407201    Val loss:  0.5500527 
  early stop at epoch:  30    Train loss:  0.4407201    Val loss:  0.5500527 
  epoch:  10    Train loss:  0.5594804    Val loss:  0.6063128 
  epoch:  20    Train loss:  0.5454192    Val loss:  0.5106468 
  epoch:  30    Train loss:  0.550128    Val loss:  0.3891037 
  epoch:  40    Train loss:  0.5599449    Val loss:  0.5553904 
  early stop at epoch:  43    Train loss:  0.5259001    Val loss:  0.6514629 
  time: 58.639 sec elapsed
  random search: 129.833 sec elapsed
  epoch:  10    Train loss:  0.07086423    Val loss:  0.1402023 
  epoch:  20    Train loss:  0.07086423    Val loss:  0.07086422 
  epoch:  30    Train loss:  0.07086423    Val loss:  0.1477819 
  early stop at epoch:  30    Train loss:  0.07086423    Val loss:  0.1477819 
  epoch:  10    Train loss:  0.1184543    Val loss:  0.2277571 
  epoch:  20    Train loss:  0.1184543    Val loss:  0.1184543 
  epoch:  30    Train loss:  0.1184543    Val loss:  0.1184543 
  epoch:  40    Train loss:  0.1184543    Val loss:  0.1184543 
  epoch:  50    Train loss:  0.1184543    Val loss:  0.1184543 
  epoch:  60    Train loss:  0.1184543    Val loss:  0.1184543 
  epoch:  70    Train loss:  0.1184543    Val loss:  0.1184543 
  epoch:  80    Train loss:  0.1184543    Val loss:  0.1184543 
  epoch:  90    Train loss:  0.2012537    Val loss:  0.2220811 
  epoch:  100    Train loss:  0.1184543    Val loss:  0.115797 
  epoch:  10    Train loss:  0.08133126    Val loss:  0.08133127 
  epoch:  20    Train loss:  0.1535666    Val loss:  0.06717191 
  epoch:  30    Train loss:  0.08133126    Val loss:  0.08133127 
  early stop at epoch:  32    Train loss:  0.08133126    Val loss:  0.3589479 
  time: 37.488 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