Last updated on 2025-08-16 13:48:37 CEST.
Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
---|---|---|---|---|---|---|
r-devel-linux-x86_64-debian-clang | 1.1.0 | 14.40 | 1248.99 | 1263.39 | OK | |
r-devel-linux-x86_64-debian-gcc | 1.1.0 | 11.27 | 1203.24 | 1214.51 | ERROR | |
r-devel-linux-x86_64-fedora-clang | 1.1.0 | 1152.79 | OK | |||
r-devel-linux-x86_64-fedora-gcc | 1.1.0 | 1134.47 | OK | |||
r-devel-windows-x86_64 | 1.1.0 | 16.00 | 333.00 | 349.00 | OK | |
r-patched-linux-x86_64 | 1.1.0 | 14.62 | 1111.71 | 1126.33 | OK | |
r-release-linux-x86_64 | 1.1.0 | 13.55 | 1292.71 | 1306.26 | OK | |
r-release-macos-arm64 | 1.1.0 | 280.00 | OK | |||
r-release-macos-x86_64 | 1.1.0 | 70.00 | OK | |||
r-release-windows-x86_64 | 1.1.0 | 17.00 | 328.00 | 345.00 | OK | |
r-oldrel-macos-arm64 | 1.1.0 | 44.00 | OK | |||
r-oldrel-macos-x86_64 | 1.1.0 | 73.00 | OK | |||
r-oldrel-windows-x86_64 | 1.1.0 | 21.00 | 463.00 | 484.00 | OK |
Version: 1.1.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [19m/12m]
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: 0.7599003 Val loss: 0.7248313
epoch: 20 Train loss: 0.8645267 Val loss: 0.8023899
epoch: 30 Train loss: 0.7620199 Val loss: 0.5373248
epoch: 40 Train loss: 0.8324142 Val loss: 0.4764548
epoch: 50 Train loss: 0.8427221 Val loss: 0.5701311
epoch: 60 Train loss: 0.7945258 Val loss: 0.3817507
epoch: 70 Train loss: 0.8961152 Val loss: 0.6592442
epoch: 80 Train loss: 0.8502591 Val loss: 0.5885566
epoch: 90 Train loss: 0.7880955 Val loss: 0.2455029
epoch: 100 Train loss: 0.6798802 Val loss: 0.3645456
epoch: 10 Train loss: 0.6219627 Val loss: 0.7840626
epoch: 20 Train loss: 0.6704158 Val loss: 0.8399888
epoch: 30 Train loss: 0.6675342 Val loss: 0.8539749
early stop at epoch: 30 Train loss: 0.6675342 Val loss: 0.8539749
epoch: 10 Train loss: 0.7298967 Val loss: 0.8229401
epoch: 20 Train loss: 0.7445398 Val loss: 0.7465868
epoch: 30 Train loss: 0.629054 Val loss: 0.7237344
early stop at epoch: 31 Train loss: 0.6295169 Val loss: 0.8355131
epoch: 10 Train loss: 0.7718321 Val loss: 0.2808588
epoch: 20 Train loss: 0.6566182 Val loss: 0.3141668
epoch: 30 Train loss: 0.7045284 Val loss: 0.3500306
epoch: 40 Train loss: 0.638485 Val loss: 0.2463887
epoch: 50 Train loss: 0.6810969 Val loss: 0.8215458
epoch: 60 Train loss: 0.6973429 Val loss: 0.2378608
epoch: 70 Train loss: 0.6912739 Val loss: 0.3243187
epoch: 80 Train loss: 0.700842 Val loss: 0.2085903
epoch: 90 Train loss: 0.7693645 Val loss: 0.3736159
epoch: 100 Train loss: 0.682025 Val loss: 0.2748377
time: 199.37 sec elapsed
epoch: 10 Train loss: 0.6461609 Val loss: 0.7300589
epoch: 20 Train loss: 0.6494385 Val loss: 0.7759352
epoch: 30 Train loss: 0.8371425 Val loss: 0.7655104
epoch: 40 Train loss: 0.7388492 Val loss: 0.6114454
early stop at epoch: 47 Train loss: 0.6194892 Val loss: 0.7524267
epoch: 10 Train loss: 0.7247152 Val loss: 0.6663572
epoch: 20 Train loss: 0.7378678 Val loss: 0.6443956
epoch: 30 Train loss: 0.7739933 Val loss: 0.6381109
epoch: 40 Train loss: 0.7259576 Val loss: 0.6338281
epoch: 50 Train loss: 0.7516199 Val loss: 0.6342371
epoch: 60 Train loss: 0.7387067 Val loss: 0.6746392
epoch: 70 Train loss: 0.7130806 Val loss: 0.6450401
epoch: 80 Train loss: 0.733237 Val loss: 0.6029599
early stop at epoch: 84 Train loss: 0.7539955 Val loss: 0.6467461
epoch: 10 Train loss: 0.7151577 Val loss: 0.7790765
epoch: 20 Train loss: 0.6298177 Val loss: 0.5040781
epoch: 30 Train loss: 0.6635298 Val loss: 0.7126158
early stop at epoch: 31 Train loss: 0.6697502 Val loss: 0.7429184
epoch: 10 Train loss: 0.6227168 Val loss: 0.6059908
epoch: 20 Train loss: 0.6884208 Val loss: 0.6417423
epoch: 30 Train loss: 0.7255963 Val loss: 0.6373754
epoch: 40 Train loss: 0.7299808 Val loss: 0.6346108
epoch: 50 Train loss: 0.7203053 Val loss: 0.6703576
epoch: 60 Train loss: 0.6884636 Val loss: 0.6244875
early stop at epoch: 64 Train loss: 0.7328161 Val loss: 0.6500231
time: 155.323 sec elapsed
epoch: 10 Train loss: 0.3348995 Val loss: 0.3127333
epoch: 20 Train loss: 0.3535367 Val loss: 0.3200153
epoch: 30 Train loss: 0.361241 Val loss: 0.4158571
early stop at epoch: 33 Train loss: 0.2710129 Val loss: 0.3990917
epoch: 10 Train loss: 0.3349542 Val loss: 0.1174232
epoch: 20 Train loss: 0.3337182 Val loss: 0.3003015
epoch: 30 Train loss: 0.3130811 Val loss: 0.5018293
early stop at epoch: 30 Train loss: 0.3130811 Val loss: 0.5018293
epoch: 10 Train loss: 0.2844067 Val loss: 0.5932306
epoch: 20 Train loss: 0.2262332 Val loss: 0.184682
epoch: 30 Train loss: 0.238215 Val loss: 0.3140552
early stop at epoch: 37 Train loss: 0.2429357 Val loss: 0.3754033
epoch: 10 Train loss: 0.3616753 Val loss: 0.1708153
epoch: 20 Train loss: 0.3221505 Val loss: 0.1485768
epoch: 30 Train loss: 0.3157081 Val loss: 0.2142386
early stop at epoch: 31 Train loss: 0.3139112 Val loss: 0.4327657
time: 81.317 sec elapsed
epoch: 10 Train loss: 0.4958697 Val loss: 0.5409112
epoch: 20 Train loss: 0.4958697 Val loss: 0.5434002
epoch: 30 Train loss: 0.4958697 Val loss: 0.5434002
early stop at epoch: 32 Train loss: 0.4958697 Val loss: 0.5572606
epoch: 10 Train loss: 0.722715 Val loss: 0.5963866
epoch: 20 Train loss: 0.722715 Val loss: 0.6199292
epoch: 30 Train loss: 0.722715 Val loss: 0.6199292
epoch: 40 Train loss: 0.722715 Val loss: 0.6199292
epoch: 50 Train loss: 0.722715 Val loss: 0.6199292
epoch: 60 Train loss: 0.722715 Val loss: 0.6199292
epoch: 70 Train loss: 0.722715 Val loss: 0.6199292
epoch: 80 Train loss: 0.722715 Val loss: 0.660278
epoch: 90 Train loss: 0.722715 Val loss: 0.6199292
epoch: 100 Train loss: 0.722715 Val loss: 0.6549069
epoch: 10 Train loss: 0.3444642 Val loss: 0.3488956
epoch: 20 Train loss: 0.3444642 Val loss: 0.3445197
epoch: 30 Train loss: 0.3541723 Val loss: 0.3488956
early stop at epoch: 34 Train loss: 0.3696207 Val loss: 0.3906776
time: 54.973 sec elapsed
epoch: 10 Train loss: 0.6071812 Val loss: 0.6415308
epoch: 20 Train loss: 0.6071812 Val loss: 0.6360424
epoch: 30 Train loss: 0.6071812 Val loss: 0.6355206
early stop at epoch: 33 Train loss: 0.6206218 Val loss: 0.6652892
epoch: 10 Train loss: 0.7500421 Val loss: 0.6997044
epoch: 20 Train loss: 0.7306059 Val loss: 0.7055011
epoch: 30 Train loss: 0.7580199 Val loss: 0.7385918
epoch: 40 Train loss: 0.7306059 Val loss: 0.7055011
epoch: 50 Train loss: 0.7306059 Val loss: 0.7055011
early stop at epoch: 59 Train loss: 0.7306059 Val loss: 0.7696314
epoch: 10 Train loss: 0.629312 Val loss: 0.5607011
epoch: 20 Train loss: 0.629312 Val loss: 0.5492671
epoch: 30 Train loss: 0.6406093 Val loss: 0.5573002
epoch: 40 Train loss: 0.629312 Val loss: 0.5281357
epoch: 50 Train loss: 0.629312 Val loss: 0.592643
epoch: 60 Train loss: 0.6529294 Val loss: 0.5171959
epoch: 70 Train loss: 0.629312 Val loss: 0.5272684
epoch: 80 Train loss: 0.6539798 Val loss: 0.5305492
early stop at epoch: 86 Train loss: 0.6509914 Val loss: 0.549684
time: 62.951 sec elapsed
epoch: 10 Train loss: 0.7478594 Val loss: 0.6029842
epoch: 20 Train loss: 0.7700991 Val loss: 0.6105425
epoch: 30 Train loss: 0.7340216 Val loss: 0.6602426
early stop at epoch: 33 Train loss: 0.82791 Val loss: 0.6469655
epoch: 10 Train loss: 0.5273364 Val loss: 0.58466
epoch: 20 Train loss: 0.4626501 Val loss: 0.5301526
epoch: 30 Train loss: 0.4510717 Val loss: 0.5539699
early stop at epoch: 30 Train loss: 0.4510717 Val loss: 0.5539699
epoch: 10 Train loss: 0.5515197 Val loss: 0.5940535
epoch: 20 Train loss: 0.5589992 Val loss: 0.5536286
epoch: 30 Train loss: 0.5773443 Val loss: 0.5408852
epoch: 40 Train loss: 0.5690995 Val loss: 0.5068976
epoch: 50 Train loss: 0.6083781 Val loss: 0.5089527
early stop at epoch: 54 Train loss: 0.6084317 Val loss: 0.5165728
time: 80.935 sec elapsed
random search: 198.867 sec elapsed
epoch: 10 Train loss: 0.07086423 Val loss: 0.1388676
epoch: 20 Train loss: 0.07086423 Val loss: 0.07086423
epoch: 30 Train loss: 0.07086423 Val loss: 0.142736
epoch: 40 Train loss: 0.07086423 Val loss: 0.1257446
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: 0.2012536 Val loss: 0.2306222
epoch: 30 Train loss: 0.1184543 Val loss: 0.1225919
early stop at epoch: 32 Train loss: 0.1184543 Val loss: 0.229417
epoch: 10 Train loss: 0.07893316 Val loss: 0.07893316
epoch: 20 Train loss: 0.07893316 Val loss: 0.07893316
epoch: 30 Train loss: 0.07893316 Val loss: 0.3078472
epoch: 40 Train loss: 0.131701 Val loss: 0.07893316
epoch: 50 Train loss: 0.07893316 Val loss: 0.07893316
epoch: 60 Train loss: 0.2089476 Val loss: 0.1126959
epoch: 70 Train loss: 0.07893316 Val loss: 0.198078
epoch: 80 Train loss: 0.07893316 Val loss: 0.07893316
epoch: 90 Train loss: 0.07893316 Val loss: 0.3511017
epoch: 100 Train loss: 0.1628903 Val loss: 0.07893316
time: 74.519 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
Flavor: r-devel-linux-x86_64-debian-gcc