Running ‘testthat.R’ [938s/591s]
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:  0.5788068    Val loss:  0.7615665 
  epoch:  20    Train loss:  0.6267315    Val loss:  0.7854717 
  epoch:  30    Train loss:  0.5835145    Val loss:  0.7468793 
  early stop at epoch:  34    Train loss:  0.5731231    Val loss:  0.8231868 
  epoch:  10    Train loss:  0.7302467    Val loss:  0.5057912 
  epoch:  20    Train loss:  0.8149955    Val loss:  0.4485699 
  epoch:  30    Train loss:  0.778167    Val loss:  0.4580292 
  epoch:  40    Train loss:  0.7194757    Val loss:  0.4532183 
  epoch:  50    Train loss:  0.7286757    Val loss:  0.435063 
  epoch:  60    Train loss:  0.795844    Val loss:  0.473906 
  early stop at epoch:  61    Train loss:  0.8195978    Val loss:  0.4746233 
  epoch:  10    Train loss:  0.6930163    Val loss:  0.6611052 
  epoch:  20    Train loss:  0.6442805    Val loss:  0.5165489 
  epoch:  30    Train loss:  0.7245831    Val loss:  0.4601876 
  epoch:  40    Train loss:  0.7408463    Val loss:  0.4788599 
  early stop at epoch:  42    Train loss:  0.5984856    Val loss:  0.7926724 
  epoch:  10    Train loss:  0.6859234    Val loss:  0.8328362 
  epoch:  20    Train loss:  0.5250563    Val loss:  0.6944969 
  epoch:  30    Train loss:  0.6916525    Val loss:  0.757234 
  early stop at epoch:  34    Train loss:  0.6131497    Val loss:  0.8418196 
  time: 123.111 sec elapsed
  epoch:  10    Train loss:  0.8061588    Val loss:  0.7053779 
  epoch:  20    Train loss:  0.6718895    Val loss:  0.690855 
  epoch:  30    Train loss:  0.8859985    Val loss:  0.7873367 
  early stop at epoch:  30    Train loss:  0.8859985    Val loss:  0.7873367 
  epoch:  10    Train loss:  0.7219209    Val loss:  0.7078794 
  epoch:  20    Train loss:  0.7418959    Val loss:  0.7131626 
  epoch:  30    Train loss:  0.701626    Val loss:  0.7664087 
  early stop at epoch:  30    Train loss:  0.701626    Val loss:  0.7664087 
  epoch:  10    Train loss:  0.5904789    Val loss:  0.8210188 
  epoch:  20    Train loss:  0.6268718    Val loss:  0.7892195 
  epoch:  30    Train loss:  0.5953217    Val loss:  0.835769 
  early stop at epoch:  30    Train loss:  0.5953217    Val loss:  0.835769 
  epoch:  10    Train loss:  0.6746593    Val loss:  0.5582851 
  epoch:  20    Train loss:  0.6238996    Val loss:  0.5770239 
  epoch:  30    Train loss:  0.662691    Val loss:  0.6016925 
  epoch:  40    Train loss:  0.653276    Val loss:  0.5812768 
  early stop at epoch:  48    Train loss:  0.6674852    Val loss:  0.5919284 
  time: 108.229 sec elapsed
  epoch:  10    Train loss:  0.2763225    Val loss:  0.4649228 
  epoch:  20    Train loss:  0.3271827    Val loss:  0.3470422 
  epoch:  30    Train loss:  0.3131918    Val loss:  0.2327961 
  early stop at epoch:  31    Train loss:  0.3316959    Val loss:  0.4206645 
  epoch:  10    Train loss:  0.2998268    Val loss:  0.4556637 
  epoch:  20    Train loss:  0.3013942    Val loss:  0.4247108 
  epoch:  30    Train loss:  0.3275842    Val loss:  0.4407933 
  early stop at epoch:  30    Train loss:  0.3275842    Val loss:  0.4407933 
  epoch:  10    Train loss:  0.3116498    Val loss:  0.1173257 
  epoch:  20    Train loss:  0.2091731    Val loss:  0.518469 
  epoch:  30    Train loss:  0.2771624    Val loss:  0.2422333 
  early stop at epoch:  33    Train loss:  0.2465063    Val loss:  0.3643527 
  epoch:  10    Train loss:  0.2850414    Val loss:  0.1912855 
  epoch:  20    Train loss:  0.2880409    Val loss:  0.4640248 
  epoch:  30    Train loss:  0.2949161    Val loss:  0.3170047 
  early stop at epoch:  35    Train loss:  0.2287316    Val loss:  0.4208836 
  time: 107.251 sec elapsed
  epoch:  10    Train loss:  0.07086423    Val loss:  0.1512602 
  epoch:  20    Train loss:  0.07086423    Val loss:  0.07086422 
  epoch:  30    Train loss:  0.07086423    Val loss:  0.07086422 
  early stop at epoch:  33    Train loss:  0.07086423    Val loss:  0.2083862 
  epoch:  10    Train loss:  0.1184543    Val loss:  0.1184543 
  epoch:  20    Train loss:  0.2014567    Val loss:  0.1184543 
  epoch:  30    Train loss:  0.1184543    Val loss:  0.1184543 
  epoch:  40    Train loss:  0.1184543    Val loss:  0.1869216 
  epoch:  50    Train loss:  0.1184543    Val loss:  0.2522153 
  epoch:  60    Train loss:  0.1184543    Val loss:  0.1184543 
  epoch:  70    Train loss:  0.1184543    Val loss:  0.1228884 
  epoch:  80    Train loss:  0.1440095    Val loss:  0.1184543 
  epoch:  90    Train loss:  0.1184543    Val loss:  0.2408815 
  epoch:  100    Train loss:  0.1184543    Val loss:  0.1184543 
  epoch:  10    Train loss:  0.0317572    Val loss:  0.03167522 
  epoch:  20    Train loss:  0.0317572    Val loss:  0.1856589 
  epoch:  30    Train loss:  0.0317572    Val loss:  0.1227927 
  early stop at epoch:  30    Train loss:  0.0317572    Val loss:  0.1227927 
  time: 55.624 sec elapsed
  epoch:  10    Train loss:  0.8640934    Val loss:  0.7564418 
  epoch:  20    Train loss:  0.8640934    Val loss:  0.7408723 
  epoch:  30    Train loss:  0.8640934    Val loss:  0.7733344 
  epoch:  40    Train loss:  0.8535393    Val loss:  0.7690729 
  epoch:  50    Train loss:  0.8640934    Val loss:  0.771186 
  early stop at epoch:  55    Train loss:  0.8792196    Val loss:  0.7786958 
  epoch:  10    Train loss:  0.442159    Val loss:  0.9089877 
  epoch:  20    Train loss:  0.3478584    Val loss:  0.9104664 
  epoch:  30    Train loss:  0.3751385    Val loss:  0.915233 
  early stop at epoch:  32    Train loss:  0.3523662    Val loss:  0.9165674 
  epoch:  10    Train loss:  0.8750541    Val loss:  0.08552663 
  epoch:  20    Train loss:  0.8341721    Val loss:  0.08667952 
  epoch:  30    Train loss:  0.8456057    Val loss:  0.1035002 
  epoch:  40    Train loss:  0.8336698    Val loss:  0.0677993 
  epoch:  50    Train loss:  0.8203856    Val loss:  0.106751 
  epoch:  60    Train loss:  0.8375466    Val loss:  0.08220709 
  epoch:  70    Train loss:  0.8381673    Val loss:  0.231533 
  epoch:  80    Train loss:  0.8286211    Val loss:  0.116746 
  epoch:  90    Train loss:  0.8312194    Val loss:  0.3051896 
  epoch:  100    Train loss:  0.8203856    Val loss:  0.08623349 
  time: 68.059 sec elapsed
  epoch:  10    Train loss:  0.8444542    Val loss:  0.8862541 
  epoch:  20    Train loss:  0.8646039    Val loss:  0.8927444 
  epoch:  30    Train loss:  0.7724872    Val loss:  0.8545548 
  epoch:  40    Train loss:  0.9187369    Val loss:  0.8809724 
  early stop at epoch:  44    Train loss:  0.8255855    Val loss:  0.8824968 
  epoch:  10    Train loss:  0.7441384    Val loss:  0.9199622 
  epoch:  20    Train loss:  0.7584287    Val loss:  0.9378126 
  epoch:  30    Train loss:  0.7124266    Val loss:  0.9216418 
  early stop at epoch:  30    Train loss:  0.7124266    Val loss:  0.9216418 
  epoch:  10    Train loss:  0.8181283    Val loss:  0.5359964 
  epoch:  20    Train loss:  0.8175043    Val loss:  0.3761493 
  epoch:  30    Train loss:  0.8141212    Val loss:  0.3963043 
  epoch:  40    Train loss:  0.8182454    Val loss:  0.5568075 
  epoch:  50    Train loss:  0.8294666    Val loss:  0.4039587 
  epoch:  60    Train loss:  0.8017391    Val loss:  0.1532943 
  epoch:  70    Train loss:  0.8177714    Val loss:  0.3064767 
  epoch:  80    Train loss:  0.84637    Val loss:  0.4375013 
  epoch:  90    Train loss:  0.8124074    Val loss:  0.3039845 
  epoch:  100    Train loss:  0.8019361    Val loss:  0.3691657 
  time: 120.673 sec elapsed
  random search: 244.366 sec elapsed
  [ FAIL 1 | WARN 61 | 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: 1.
  Caused by error in `training_function()`:
  ! not enough data for training
  
  [ FAIL 1 | WARN 61 | SKIP 0 | PASS 46 ]
  Error: Test failures
  Execution halted