Running ‘testthat.R’ [13m/14m]
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:  0.7404362    Val loss:  0.6499038 
  epoch:  20    Train loss:  0.7873201    Val loss:  0.6926796 
  epoch:  30    Train loss:  0.6163016    Val loss:  0.6780418 
  epoch:  40    Train loss:  0.7078852    Val loss:  0.7761384 
  early stop at epoch:  46    Train loss:  0.5981395    Val loss:  0.7940681 
  epoch:  10    Train loss:  0.6466777    Val loss:  0.7789006 
  epoch:  20    Train loss:  0.6596473    Val loss:  0.6999308 
  epoch:  30    Train loss:  0.6521254    Val loss:  0.7699696 
  early stop at epoch:  30    Train loss:  0.6521254    Val loss:  0.7699696 
  epoch:  10    Train loss:  0.6449589    Val loss:  0.444153 
  epoch:  20    Train loss:  0.758602    Val loss:  0.4385753 
  epoch:  30    Train loss:  0.6880445    Val loss:  0.3426987 
  epoch:  40    Train loss:  0.7106441    Val loss:  0.4539416 
  epoch:  50    Train loss:  0.6342977    Val loss:  0.8711337 
  epoch:  60    Train loss:  0.6885779    Val loss:  0.5211724 
  early stop at epoch:  69    Train loss:  0.6220365    Val loss:  0.9316228 
  epoch:  10    Train loss:  0.6724176    Val loss:  0.8650366 
  epoch:  20    Train loss:  0.6872246    Val loss:  0.8392095 
  epoch:  30    Train loss:  0.6896456    Val loss:  0.7370776 
  epoch:  40    Train loss:  0.6235377    Val loss:  0.7963269 
  early stop at epoch:  46    Train loss:  0.6459358    Val loss:  0.915852 
  time: 205.335 sec elapsed
  epoch:  10    Train loss:  0.5671113    Val loss:  0.7877306 
  epoch:  20    Train loss:  0.7571525    Val loss:  0.7959399 
  epoch:  30    Train loss:  0.7317599    Val loss:  0.7568924 
  early stop at epoch:  32    Train loss:  0.6777967    Val loss:  0.7978185 
  epoch:  10    Train loss:  0.7806754    Val loss:  0.6500019 
  epoch:  20    Train loss:  0.7662898    Val loss:  0.6900097 
  epoch:  30    Train loss:  0.7685689    Val loss:  0.6770724 
  epoch:  40    Train loss:  0.7533752    Val loss:  0.6859307 
  epoch:  50    Train loss:  0.7617718    Val loss:  0.6647394 
  epoch:  60    Train loss:  0.7737355    Val loss:  0.6531329 
  epoch:  70    Train loss:  0.7861809    Val loss:  0.6895149 
  early stop at epoch:  74    Train loss:  0.796499    Val loss:  0.6681731 
  epoch:  10    Train loss:  0.6801817    Val loss:  0.7570291 
  epoch:  20    Train loss:  0.7307228    Val loss:  0.7342201 
  epoch:  30    Train loss:  0.7528307    Val loss:  0.5861967 
  epoch:  40    Train loss:  0.7089797    Val loss:  0.6722263 
  epoch:  50    Train loss:  0.7582901    Val loss:  0.7544945 
  early stop at epoch:  52    Train loss:  0.6089504    Val loss:  0.7689536 
  epoch:  10    Train loss:  0.7437481    Val loss:  0.6437203 
  epoch:  20    Train loss:  0.7475831    Val loss:  0.7520479 
  epoch:  30    Train loss:  0.7930458    Val loss:  0.7699777 
  epoch:  40    Train loss:  0.7663664    Val loss:  0.7683645 
  epoch:  50    Train loss:  0.7552815    Val loss:  0.7757112 
  early stop at epoch:  59    Train loss:  0.7600039    Val loss:  0.8094699 
  time: 223.325 sec elapsed
  epoch:  10    Train loss:  0.3367965    Val loss:  0.2629166 
  epoch:  20    Train loss:  0.3691852    Val loss:  0.2489735 
  epoch:  30    Train loss:  0.3250203    Val loss:  0.281245 
  early stop at epoch:  31    Train loss:  0.2968844    Val loss:  0.4561351 
  epoch:  10    Train loss:  0.3842437    Val loss:  0.4139424 
  epoch:  20    Train loss:  0.3481341    Val loss:  0.1990154 
  epoch:  30    Train loss:  0.2937351    Val loss:  0.2895616 
  early stop at epoch:  32    Train loss:  0.3820457    Val loss:  0.4971419 
  epoch:  10    Train loss:  0.2552236    Val loss:  0.4853632 
  epoch:  20    Train loss:  0.2440273    Val loss:  0.2029163 
  epoch:  30    Train loss:  0.2477501    Val loss:  0.2569994 
  epoch:  40    Train loss:  0.2262447    Val loss:  0.1975362 
  early stop at epoch:  42    Train loss:  0.2444609    Val loss:  0.3899662 
  epoch:  10    Train loss:  0.2969968    Val loss:  0.278839 
  epoch:  20    Train loss:  0.2843761    Val loss:  0.2205169 
  epoch:  30    Train loss:  0.297507    Val loss:  0.4162907 
  early stop at epoch:  35    Train loss:  0.2779097    Val loss:  0.4804926 
  time: 146.267 sec elapsed
  epoch:  10    Train loss:  0.07086423    Val loss:  0.1342499 
  epoch:  20    Train loss:  0.07086423    Val loss:  0.07086422 
  epoch:  30    Train loss:  0.07086423    Val loss:  0.1414617 
  early stop at epoch:  35    Train loss:  0.07086423    Val loss:  0.1934745 
  epoch:  10    Train loss:  0.2014556    Val loss:  0.1184543 
  epoch:  20    Train loss:  0.1184542    Val loss:  0.1184543 
  epoch:  30    Train loss:  0.1184542    Val loss:  0.1572601 
  early stop at epoch:  36    Train loss:  0.1184542    Val loss:  0.1543265 
  epoch:  10    Train loss:  0.08458353    Val loss:  0.06167005 
  epoch:  20    Train loss:  0.232845    Val loss:  0.0491862 
  epoch:  30    Train loss:  0.2402083    Val loss:  0.1324876 
  early stop at epoch:  33    Train loss:  0.05270579    Val loss:  0.1365599 
  time: 44.345 sec elapsed
  epoch:  10    Train loss:  0.1069393    Val loss:  0.2469431 
  epoch:  20    Train loss:  0.1069393    Val loss:  0.3089375 
  epoch:  30    Train loss:  0.1069393    Val loss:  0.324126 
  early stop at epoch:  30    Train loss:  0.1069393    Val loss:  0.324126 
  epoch:  10    Train loss:  0.6792193    Val loss:  0.1115732 
  epoch:  20    Train loss:  0.7309577    Val loss:  0.1633555 
  epoch:  30    Train loss:  0.6792193    Val loss:  0.2798297 
  epoch:  40    Train loss:  0.6940066    Val loss:  0.2237568 
  epoch:  50    Train loss:  0.693056    Val loss:  0.1645221 
  epoch:  60    Train loss:  0.6792193    Val loss:  0.120089 
  epoch:  70    Train loss:  0.6792193    Val loss:  0.1807808 
  epoch:  80    Train loss:  0.6792193    Val loss:  0.2511505 
  epoch:  90    Train loss:  0.6821669    Val loss:  0.2415981 
  epoch:  100    Train loss:  0.6877335    Val loss:  0.1448254 
  epoch:  10    Train loss:  0.4121527    Val loss:  0.9659778 
  epoch:  20    Train loss:  0.3497554    Val loss:  0.9637098 
  epoch:  30    Train loss:  0.3497554    Val loss:  0.96589 
  early stop at epoch:  35    Train loss:  0.3824081    Val loss:  0.9772152 
  time: 76.698 sec elapsed
  epoch:  10    Train loss:  0.2441066    Val loss:  0.5909442 
  epoch:  20    Train loss:  0.3808201    Val loss:  0.6069433 
  epoch:  30    Train loss:  0.4020416    Val loss:  0.5675647 
  early stop at epoch:  31    Train loss:  0.3043025    Val loss:  0.6239682 
  epoch:  10    Train loss:  0.7730089    Val loss:  0.4593685 
  epoch:  20    Train loss:  0.860289    Val loss:  0.444143 
  epoch:  30    Train loss:  0.7404982    Val loss:  0.4949161 
  early stop at epoch:  32    Train loss:  0.8780193    Val loss:  0.4698609 
  epoch:  10    Train loss:  0.6297266    Val loss:  0.9583788 
  epoch:  20    Train loss:  0.5626031    Val loss:  0.9397631 
  epoch:  30    Train loss:  0.5265221    Val loss:  0.9673436 
  early stop at epoch:  30    Train loss:  0.5265221    Val loss:  0.9673436 
  time: 113.638 sec elapsed
  random search: 234.736 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: 1.
  Caused by error in `training_function()`:
  ! not enough data for training
  
  [ FAIL 1 | WARN 60 | SKIP 0 | PASS 46 ]
  Error: Test failures
  Execution halted