Last updated on 2025-07-30 07:50:21 CEST.
Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
---|---|---|---|---|---|---|
r-devel-linux-x86_64-debian-clang | 1.1.0 | 15.14 | 1186.99 | 1202.13 | OK | |
r-devel-linux-x86_64-debian-gcc | 1.1.0 | 10.18 | 1411.27 | 1421.45 | OK | |
r-devel-linux-x86_64-fedora-clang | 1.1.0 | 1249.96 | OK | |||
r-devel-linux-x86_64-fedora-gcc | 1.1.0 | 1317.03 | OK | |||
r-devel-windows-x86_64 | 1.1.0 | 17.00 | 364.00 | 381.00 | OK | |
r-patched-linux-x86_64 | 1.1.0 | 13.95 | 1022.97 | 1036.92 | OK | |
r-release-linux-x86_64 | 1.1.0 | 13.72 | 1049.42 | 1063.14 | 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 | 16.00 | 323.00 | 339.00 | 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 | 22.00 | 404.00 | 426.00 | ERROR |
Version: 1.1.0
Check: tests
Result: ERROR
Running 'testthat.R' [264s]
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")
OMP: Warning #96: Cannot form a team with 28 threads, using 2 instead.
OMP: Hint Consider unsetting KMP_DEVICE_THREAD_LIMIT (KMP_ALL_THREADS), KMP_TEAMS_THREAD_LIMIT, and OMP_THREAD_LIMIT (if any are set).
epoch: 10 Train loss: 0.7880893 Val loss: 0.7255653
epoch: 20 Train loss: 0.8137968 Val loss: 0.7753562
epoch: 30 Train loss: 0.8466399 Val loss: 0.8031964
early stop at epoch: 30 Train loss: 0.8466399 Val loss: 0.8031964
epoch: 10 Train loss: 0.8181331 Val loss: 0.7062073
epoch: 20 Train loss: 0.7099457 Val loss: 0.6848931
epoch: 30 Train loss: 0.8088268 Val loss: 0.6160501
epoch: 40 Train loss: 0.7901298 Val loss: 0.7961853
early stop at epoch: 44 Train loss: 0.746365 Val loss: 0.8309304
epoch: 10 Train loss: 0.6312017 Val loss: 0.8636278
epoch: 20 Train loss: 0.6782193 Val loss: 0.4614531
epoch: 30 Train loss: 0.6822445 Val loss: 0.7606828
epoch: 40 Train loss: 0.6555291 Val loss: 0.6954718
early stop at epoch: 46 Train loss: 0.6502698 Val loss: 0.9003091
epoch: 10 Train loss: 0.6378485 Val loss: 0.5317824
epoch: 20 Train loss: 0.6150324 Val loss: 0.3747623
epoch: 30 Train loss: 0.6623861 Val loss: 0.5424011
epoch: 40 Train loss: 0.6301767 Val loss: 0.4165615
epoch: 50 Train loss: 0.6125575 Val loss: 0.4503262
epoch: 60 Train loss: 0.6257965 Val loss: 0.4263246
early stop at epoch: 65 Train loss: 0.745899 Val loss: 0.53618
time: 64.89 sec elapsed
epoch: 10 Train loss: 0.7739093 Val loss: 0.770283
epoch: 20 Train loss: 0.7055809 Val loss: 0.7759296
epoch: 30 Train loss: 0.7352791 Val loss: 0.7941313
early stop at epoch: 30 Train loss: 0.7352791 Val loss: 0.7941313
epoch: 10 Train loss: 0.7002555 Val loss: 0.694304
epoch: 20 Train loss: 0.706356 Val loss: 0.7246676
epoch: 30 Train loss: 0.7121664 Val loss: 0.7258093
early stop at epoch: 35 Train loss: 0.6510051 Val loss: 0.7416199
epoch: 10 Train loss: 0.7479615 Val loss: 0.7007744
epoch: 20 Train loss: 0.6650078 Val loss: 0.6358659
epoch: 30 Train loss: 0.6284428 Val loss: 0.6328874
early stop at epoch: 39 Train loss: 0.5988222 Val loss: 0.7966897
epoch: 10 Train loss: 0.8012241 Val loss: 0.7569225
epoch: 20 Train loss: 0.7572383 Val loss: 0.8048664
epoch: 30 Train loss: 0.7556403 Val loss: 0.7126857
early stop at epoch: 31 Train loss: 0.7280132 Val loss: 0.7868891
time: 45.17 sec elapsed
epoch: 10 Train loss: 0.3415718 Val loss: 0.2547229
epoch: 20 Train loss: 0.3281042 Val loss: 0.2208681
epoch: 30 Train loss: 0.3274095 Val loss: 0.2383749
early stop at epoch: 33 Train loss: 0.2672565 Val loss: 0.3439875
epoch: 10 Train loss: 0.3655412 Val loss: 0.2983556
epoch: 20 Train loss: 0.3302536 Val loss: 0.3878253
epoch: 30 Train loss: 0.3235301 Val loss: 0.4651515
early stop at epoch: 30 Train loss: 0.3235301 Val loss: 0.4651515
epoch: 10 Train loss: 0.2556229 Val loss: 0.3100896
epoch: 20 Train loss: 0.2315873 Val loss: 0.3082713
epoch: 30 Train loss: 0.2328274 Val loss: 0.2574663
early stop at epoch: 34 Train loss: 0.2209101 Val loss: 0.306387
epoch: 10 Train loss: 0.3312292 Val loss: 0.4367475
epoch: 20 Train loss: 0.3224618 Val loss: 0.2174875
epoch: 30 Train loss: 0.2501336 Val loss: 0.2137407
early stop at epoch: 32 Train loss: 0.2638713 Val loss: 0.4487271
time: 42.06 sec elapsed
epoch: 10 Train loss: 0.4114213 Val loss: 0.525591
epoch: 20 Train loss: 0.4114213 Val loss: 0.5224094
epoch: 30 Train loss: 0.4114213 Val loss: 0.5224094
epoch: 40 Train loss: 0.4114213 Val loss: 0.5224094
early stop at epoch: 49 Train loss: 0.4114213 Val loss: 0.54846
epoch: 10 Train loss: 0.7400234 Val loss: 0.6073773
epoch: 20 Train loss: 0.7400234 Val loss: 0.6315222
epoch: 30 Train loss: 0.7400234 Val loss: 0.6073773
epoch: 40 Train loss: 0.7400234 Val loss: 0.6073773
epoch: 50 Train loss: 0.7400234 Val loss: 0.619832
epoch: 60 Train loss: 0.7400234 Val loss: 0.6073773
epoch: 70 Train loss: 0.7400234 Val loss: 0.6351814
epoch: 80 Train loss: 0.7400234 Val loss: 0.6105238
epoch: 90 Train loss: 0.7436123 Val loss: 0.6320261
epoch: 100 Train loss: 0.7604493 Val loss: 0.6365073
epoch: 10 Train loss: 0.6387671 Val loss: 0.6326262
epoch: 20 Train loss: 0.6387671 Val loss: 0.6326262
epoch: 30 Train loss: 0.6387671 Val loss: 0.6326262
early stop at epoch: 36 Train loss: 0.6387671 Val loss: 0.6757869
time: 24.17 sec elapsed
epoch: 10 Train loss: 0.6167455 Val loss: 0.5800428
epoch: 20 Train loss: 0.5978186 Val loss: 0.6064745
epoch: 30 Train loss: 0.5978186 Val loss: 0.5752624
early stop at epoch: 33 Train loss: 0.5784105 Val loss: 0.6041983
epoch: 10 Train loss: 0.7262605 Val loss: 0.6754378
epoch: 20 Train loss: 0.7212899 Val loss: 0.6759892
epoch: 30 Train loss: 0.7568199 Val loss: 0.6754378
epoch: 40 Train loss: 0.7212899 Val loss: 0.6759892
epoch: 50 Train loss: 0.7212899 Val loss: 0.6759892
epoch: 60 Train loss: 0.7212899 Val loss: 0.6759892
epoch: 70 Train loss: 0.7212899 Val loss: 0.6759892
epoch: 80 Train loss: 0.7212899 Val loss: 0.7039152
epoch: 90 Train loss: 0.7212899 Val loss: 0.6635614
epoch: 100 Train loss: 0.7212899 Val loss: 0.6754378
epoch: 10 Train loss: 0.5362894 Val loss: 0.4748831
epoch: 20 Train loss: 0.5311361 Val loss: 0.4533411
epoch: 30 Train loss: 0.4691363 Val loss: 0.4594963
early stop at epoch: 34 Train loss: 0.4733386 Val loss: 0.6216606
time: 25.61 sec elapsed
epoch: 10 Train loss: 0.7356187 Val loss: 0.6312646
epoch: 20 Train loss: 0.7813594 Val loss: 0.6261184
epoch: 30 Train loss: 0.748969 Val loss: 0.6655114
early stop at epoch: 32 Train loss: 0.7748536 Val loss: 0.6572163
epoch: 10 Train loss: 0.5083613 Val loss: 0.5274738
epoch: 20 Train loss: 0.5270655 Val loss: 0.3788466
epoch: 30 Train loss: 0.4570093 Val loss: 0.5561817
early stop at epoch: 30 Train loss: 0.4570093 Val loss: 0.5561817
epoch: 10 Train loss: 0.6286951 Val loss: 0.6322638
epoch: 20 Train loss: 0.6143529 Val loss: 0.5438521
epoch: 30 Train loss: 0.6301204 Val loss: 0.5574672
epoch: 40 Train loss: 0.6114512 Val loss: 0.5973297
epoch: 50 Train loss: 0.6404253 Val loss: 0.5391501
epoch: 60 Train loss: 0.6294305 Val loss: 0.5511015
epoch: 70 Train loss: 0.6345275 Val loss: 0.583086
epoch: 80 Train loss: 0.6088005 Val loss: 0.5950584
epoch: 90 Train loss: 0.6323931 Val loss: 0.5589393
early stop at epoch: 96 Train loss: 0.6434103 Val loss: 0.5927544
time: 52.6 sec elapsed
random search: 102.4 sec elapsed
[ FAIL 1 | WARN 66 | 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: 1.
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
Flavor: r-oldrel-windows-x86_64