Running ‘testthat.R’ [16m/10m]
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:  0.7262089    Val loss:  0.7782243 
  epoch:  20    Train loss:  0.7570113    Val loss:  0.7823648 
  epoch:  30    Train loss:  0.7509822    Val loss:  0.6603521 
  epoch:  40    Train loss:  0.724188    Val loss:  0.7497709 
  early stop at epoch:  41    Train loss:  0.8285783    Val loss:  0.7633737 
  epoch:  10    Train loss:  0.7444847    Val loss:  0.8057399 
  epoch:  20    Train loss:  0.6900331    Val loss:  0.7852004 
  epoch:  30    Train loss:  0.7001898    Val loss:  0.876106 
  early stop at epoch:  30    Train loss:  0.7001898    Val loss:  0.876106 
  epoch:  10    Train loss:  0.6077271    Val loss:  0.6449838 
  epoch:  20    Train loss:  0.5971876    Val loss:  0.5847306 
  epoch:  30    Train loss:  0.743968    Val loss:  0.4599368 
  early stop at epoch:  39    Train loss:  0.7900096    Val loss:  0.4845917 
  epoch:  10    Train loss:  0.7917127    Val loss:  0.6476637 
  epoch:  20    Train loss:  0.7727556    Val loss:  0.716337 
  epoch:  30    Train loss:  0.7778031    Val loss:  0.4595953 
  early stop at epoch:  34    Train loss:  0.7382386    Val loss:  0.8638936 
  time: 100.363 sec elapsed
  epoch:  10    Train loss:  0.7916674    Val loss:  0.681209 
  epoch:  20    Train loss:  0.7698188    Val loss:  0.6162977 
  epoch:  30    Train loss:  0.8052637    Val loss:  0.7099208 
  early stop at epoch:  30    Train loss:  0.8052637    Val loss:  0.7099208 
  epoch:  10    Train loss:  0.6463624    Val loss:  0.667847 
  epoch:  20    Train loss:  0.6935502    Val loss:  0.6887021 
  epoch:  30    Train loss:  0.6871161    Val loss:  0.6819496 
  early stop at epoch:  36    Train loss:  0.6557673    Val loss:  0.7053472 
  epoch:  10    Train loss:  0.7353466    Val loss:  0.7775524 
  epoch:  20    Train loss:  0.7006274    Val loss:  0.5854363 
  epoch:  30    Train loss:  0.7391927    Val loss:  0.7581239 
  epoch:  40    Train loss:  0.7583737    Val loss:  0.6713415 
  early stop at epoch:  43    Train loss:  0.6709933    Val loss:  0.7733536 
  epoch:  10    Train loss:  0.6511138    Val loss:  0.6207005 
  epoch:  20    Train loss:  0.6642611    Val loss:  0.6981703 
  epoch:  30    Train loss:  0.6815276    Val loss:  0.7399237 
  early stop at epoch:  38    Train loss:  0.6483322    Val loss:  0.7120036 
  time: 103.71 sec elapsed
  epoch:  10    Train loss:  0.2816075    Val loss:  0.3656197 
  epoch:  20    Train loss:  0.3419951    Val loss:  0.189373 
  epoch:  30    Train loss:  0.281172    Val loss:  0.3167396 
  epoch:  40    Train loss:  0.2954774    Val loss:  0.2538841 
  early stop at epoch:  41    Train loss:  0.2381007    Val loss:  0.3622168 
  epoch:  10    Train loss:  0.3310393    Val loss:  0.4096441 
  epoch:  20    Train loss:  0.3031943    Val loss:  0.2557983 
  epoch:  30    Train loss:  0.2772352    Val loss:  0.364721 
  epoch:  40    Train loss:  0.3484    Val loss:  0.1708302 
  early stop at epoch:  44    Train loss:  0.2964724    Val loss:  0.5048294 
  epoch:  10    Train loss:  0.2490857    Val loss:  0.2136127 
  epoch:  20    Train loss:  0.2618084    Val loss:  0.4474599 
  epoch:  30    Train loss:  0.2437014    Val loss:  0.3408162 
  epoch:  40    Train loss:  0.2568401    Val loss:  0.1962195 
  epoch:  50    Train loss:  0.2260446    Val loss:  0.2648942 
  early stop at epoch:  53    Train loss:  0.2749288    Val loss:  0.430352 
  epoch:  10    Train loss:  0.2955167    Val loss:  0.3052865 
  epoch:  20    Train loss:  0.2838775    Val loss:  0.2777529 
  epoch:  30    Train loss:  0.2850738    Val loss:  0.1880422 
  early stop at epoch:  32    Train loss:  0.2528674    Val loss:  0.4071683 
  time: 111.915 sec elapsed
  epoch:  10    Train loss:  0.5535022    Val loss:  0.5689651 
  epoch:  20    Train loss:  0.5535022    Val loss:  0.5673431 
  epoch:  30    Train loss:  0.5535022    Val loss:  0.5673431 
  early stop at epoch:  38    Train loss:  0.5535022    Val loss:  0.5702459 
  epoch:  10    Train loss:  0.8834864    Val loss:  0.6978939 
  epoch:  20    Train loss:  0.8834864    Val loss:  0.6714969 
  epoch:  30    Train loss:  0.8834864    Val loss:  0.6714969 
  epoch:  40    Train loss:  0.8834864    Val loss:  0.6714969 
  epoch:  50    Train loss:  0.8834864    Val loss:  0.6714969 
  epoch:  60    Train loss:  0.8834864    Val loss:  0.6714969 
  epoch:  70    Train loss:  0.8834864    Val loss:  0.6714969 
  epoch:  80    Train loss:  0.8886582    Val loss:  0.6711968 
  epoch:  90    Train loss:  0.8886582    Val loss:  0.6714969 
  epoch:  100    Train loss:  0.8834864    Val loss:  0.6714969 
  epoch:  10    Train loss:  0.4426976    Val loss:  0.3050964 
  epoch:  20    Train loss:  0.444401    Val loss:  0.3074296 
  epoch:  30    Train loss:  0.4426976    Val loss:  0.6305744 
  early stop at epoch:  30    Train loss:  0.4426976    Val loss:  0.6305744 
  time: 41.708 sec elapsed
  epoch:  10    Train loss:  0.07086423    Val loss:  0.1401838 
  epoch:  20    Train loss:  0.07086423    Val loss:  0.07086423 
  epoch:  30    Train loss:  0.07086423    Val loss:  0.143551 
  epoch:  40    Train loss:  0.07086423    Val loss:  0.1266328 
  epoch:  50    Train loss:  0.07086423    Val loss:  0.07086423 
  epoch:  60    Train loss:  0.07086423    Val loss:  0.07086423 
  epoch:  70    Train loss:  0.07086423    Val loss:  0.07086423 
  epoch:  80    Train loss:  0.07086423    Val loss:  0.07086423 
  epoch:  90    Train loss:  0.07086423    Val loss:  0.07086423 
  epoch:  100    Train loss:  0.07086423    Val loss:  0.07086423 
  epoch:  10    Train loss:  0.1184543    Val loss:  0.1184543 
  epoch:  20    Train loss:  0.2012537    Val loss:  0.2263433 
  epoch:  30    Train loss:  0.1184543    Val loss:  0.1555534 
  early stop at epoch:  30    Train loss:  0.1184543    Val loss:  0.1555534 
  epoch:  10    Train loss:  0.08133126    Val loss:  0.08133126 
  epoch:  20    Train loss:  0.1535666    Val loss:  0.08133126 
  epoch:  30    Train loss:  0.08133126    Val loss:  0.08133126 
  epoch:  40    Train loss:  0.08133126    Val loss:  0.08133126 
  epoch:  50    Train loss:  0.1481376    Val loss:  0.06018644 
  epoch:  60    Train loss:  0.08133126    Val loss:  0.1794721 
  epoch:  70    Train loss:  0.08133126    Val loss:  0.08052959 
  epoch:  80    Train loss:  0.08133126    Val loss:  0.06903934 
  epoch:  90    Train loss:  0.08133126    Val loss:  0.08133126 
  epoch:  100    Train loss:  0.1535666    Val loss:  0.2058443 
  time: 65.996 sec elapsed
  epoch:  10    Train loss:  0.1299174    Val loss:  0.8306619 
  epoch:  20    Train loss:  0.1299174    Val loss:  0.8490623 
  epoch:  30    Train loss:  0.2199278    Val loss:  0.8482561 
  early stop at epoch:  32    Train loss:  0.1299174    Val loss:  0.8618797 
  epoch:  10    Train loss:  0.9557327    Val loss:  0.6459207 
  epoch:  20    Train loss:  0.9557327    Val loss:  0.7082584 
  epoch:  30    Train loss:  0.9557327    Val loss:  0.6490547 
  epoch:  40    Train loss:  0.9555648    Val loss:  0.6652384 
  epoch:  50    Train loss:  0.9557327    Val loss:  0.6459207 
  epoch:  60    Train loss:  0.9557327    Val loss:  0.6458974 
  epoch:  70    Train loss:  0.9557327    Val loss:  0.6439793 
  epoch:  80    Train loss:  0.9557327    Val loss:  0.6670248 
  epoch:  90    Train loss:  0.9752132    Val loss:  0.6459207 
  epoch:  100    Train loss:  0.9557327    Val loss:  0.6873803 
  epoch:  10    Train loss:  0.8030542    Val loss:  0.5248823 
  epoch:  20    Train loss:  0.8007991    Val loss:  0.5249152 
  epoch:  30    Train loss:  0.8050852    Val loss:  0.5616086 
  epoch:  40    Train loss:  0.8042043    Val loss:  0.5267338 
  epoch:  50    Train loss:  0.7902642    Val loss:  0.5252429 
  epoch:  60    Train loss:  0.792356    Val loss:  0.5964966 
  epoch:  70    Train loss:  0.801122    Val loss:  0.5249152 
  epoch:  80    Train loss:  0.8102846    Val loss:  0.6280752 
  epoch:  90    Train loss:  0.8166845    Val loss:  0.6312142 
  epoch:  100    Train loss:  0.7934675    Val loss:  0.5612985 
  time: 86.144 sec elapsed
  epoch:  10    Train loss:  0.3330007    Val loss:  0.9072204 
  epoch:  20    Train loss:  0.601362    Val loss:  0.9240627 
  epoch:  30    Train loss:  0.4566821    Val loss:  0.9242129 
  early stop at epoch:  31    Train loss:  0.3189774    Val loss:  0.9242551 
  epoch:  10    Train loss:  0.9484078    Val loss:  0.8590236 
  epoch:  20    Train loss:  0.9358888    Val loss:  0.8908734 
  epoch:  30    Train loss:  0.9615254    Val loss:  0.8615615 
  epoch:  40    Train loss:  0.9512906    Val loss:  0.8711975 
  epoch:  50    Train loss:  0.9280653    Val loss:  0.8885146 
  early stop at epoch:  52    Train loss:  0.9724578    Val loss:  0.8795025 
  epoch:  10    Train loss:  0.8491904    Val loss:  0.6239446 
  epoch:  20    Train loss:  0.8387845    Val loss:  0.6694392 
  epoch:  30    Train loss:  0.8267169    Val loss:  0.6090332 
  epoch:  40    Train loss:  0.8598953    Val loss:  0.6028724 
  epoch:  50    Train loss:  0.8171022    Val loss:  0.683565 
  epoch:  60    Train loss:  0.8444331    Val loss:  0.6603197 
  early stop at epoch:  65    Train loss:  0.8764925    Val loss:  0.6362083 
  time: 89.96 sec elapsed
  random search: 242.109 sec elapsed
  [ FAIL 1 | WARN 66 | 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 66 | SKIP 0 | PASS 46 ]
  Error: Test failures
  Execution halted