Last updated on 2025-03-23 15:50:58 CET.
| Package | ERROR | NOTE | OK |
|---|---|---|---|
| microinverterdata | 7 | 8 | |
| tabnet | 5 | 10 |
Current CRAN status: NOTE: 7, OK: 8
Version: 0.2.0
Check: DESCRIPTION meta-information
Result: NOTE
Missing dependency on R >= 4.1.0 because package code uses the pipe
|> or function shorthand \(...) syntax added in R 4.1.0.
File(s) using such syntax:
‘get_alarm.R’ ‘get_device_info.R’ ‘get_output_data.R’
‘query_device.R’
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-macos-x86_64, r-devel-windows-x86_64, r-patched-linux-x86_64
Current CRAN status: ERROR: 5, OK: 10
Version: 0.6.0
Check: examples
Result: ERROR
Running examples in ‘tabnet-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: tabnet_pretrain
> ### Title: Tabnet model
> ### Aliases: tabnet_pretrain tabnet_pretrain.default
> ### tabnet_pretrain.data.frame tabnet_pretrain.formula
> ### tabnet_pretrain.recipe tabnet_pretrain.Node
>
> ### ** Examples
>
> ## Don't show:
> if (torch::torch_is_installed()) (if (getRversion() >= "3.4") withAutoprint else force)({ # examplesIf
+ ## End(Don't show)
+ data("ames", package = "modeldata")
+ pretrained <- tabnet_pretrain(Sale_Price ~ ., data = ames, epochs = 1)
+ ## Don't show:
+ }) # examplesIf
> data("ames", package = "modeldata")
> pretrained <- tabnet_pretrain(Sale_Price ~ ., data = ames, epochs = 1)
Error in `value_error()`:
! Can't convert data of class: 'NULL'
Backtrace:
▆
1. ├─(if (getRversion() >= "3.4") withAutoprint else force)(...)
2. │ └─base::source(...)
3. │ ├─base::withVisible(eval(ei, envir))
4. │ └─base::eval(ei, envir)
5. │ └─base::eval(ei, envir)
6. ├─tabnet::tabnet_pretrain(Sale_Price ~ ., data = ames, epochs = 1)
7. └─tabnet:::tabnet_pretrain.formula(...)
8. └─tabnet:::tabnet_bridge(...)
9. └─tabnet:::tabnet_train_unsupervised(...)
10. ├─coro::loop(...)
11. │ └─rlang::eval_bare(loop, env)
12. └─coro (local) `<fn>`()
13. ├─coro::is_exhausted(elt <<- iterator())
14. ├─elt <<- iterator()
15. │ └─rlang::env_poke(env, lhs, value, inherit = TRUE, create = FALSE)
16. └─torch (local) iterator()
17. └─torch::dataloader_next(iter, coro::exhausted())
18. └─iter$.next()
19. └─self$.next_data()
20. └─self$.dataset_fetcher$fetch(index)
21. └─self$collate_fn(data)
22. └─base::lapply(data, utils_data_default_convert)
23. └─torch (local) FUN(X[[i]], ...)
24. └─base::tryCatch(...)
25. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
26. └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
27. └─value[[3L]](cond)
28. └─torch:::value_error("Can't convert data of class: '{class(data)}'")
29. └─rlang::abort(glue::glue(gettext(...)[[1]], .envir = env), class = "value_error")
Execution halted
Examples with CPU (user + system) or elapsed time > 5s
user system elapsed
autoplot.tabnet_explain 34.858 0.677 39.877
tabnet_fit 27.887 0.274 34.412
autoplot.tabnet_fit 26.385 0.369 28.816
tabnet 15.346 0.235 16.577
tabnet_explain 13.603 0.111 14.888
Flavor: r-devel-linux-x86_64-debian-clang
Version: 0.6.0
Check: examples
Result: ERROR
Running examples in ‘tabnet-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: tabnet_pretrain
> ### Title: Tabnet model
> ### Aliases: tabnet_pretrain tabnet_pretrain.default
> ### tabnet_pretrain.data.frame tabnet_pretrain.formula
> ### tabnet_pretrain.recipe tabnet_pretrain.Node
>
> ### ** Examples
>
> ## Don't show:
> if (torch::torch_is_installed()) (if (getRversion() >= "3.4") withAutoprint else force)({ # examplesIf
+ ## End(Don't show)
+ data("ames", package = "modeldata")
+ pretrained <- tabnet_pretrain(Sale_Price ~ ., data = ames, epochs = 1)
+ ## Don't show:
+ }) # examplesIf
> data("ames", package = "modeldata")
> pretrained <- tabnet_pretrain(Sale_Price ~ ., data = ames, epochs = 1)
Error in `value_error()`:
! Can't convert data of class: 'NULL'
Backtrace:
▆
1. ├─(if (getRversion() >= "3.4") withAutoprint else force)(...)
2. │ └─base::source(...)
3. │ ├─base::withVisible(eval(ei, envir))
4. │ └─base::eval(ei, envir)
5. │ └─base::eval(ei, envir)
6. ├─tabnet::tabnet_pretrain(Sale_Price ~ ., data = ames, epochs = 1)
7. └─tabnet:::tabnet_pretrain.formula(...)
8. └─tabnet:::tabnet_bridge(...)
9. └─tabnet:::tabnet_train_unsupervised(...)
10. ├─coro::loop(...)
11. │ └─rlang::eval_bare(loop, env)
12. └─coro (local) `<fn>`()
13. ├─coro::is_exhausted(elt <<- iterator())
14. ├─elt <<- iterator()
15. │ └─rlang::env_poke(env, lhs, value, inherit = TRUE, create = FALSE)
16. └─torch (local) iterator()
17. └─torch::dataloader_next(iter, coro::exhausted())
18. └─iter$.next()
19. └─self$.next_data()
20. └─self$.dataset_fetcher$fetch(index)
21. └─self$collate_fn(data)
22. └─base::lapply(data, utils_data_default_convert)
23. └─torch (local) FUN(X[[i]], ...)
24. └─base::tryCatch(...)
25. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
26. └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
27. └─value[[3L]](cond)
28. └─torch:::value_error("Can't convert data of class: '{class(data)}'")
29. └─rlang::abort(glue::glue(gettext(...)[[1]], .envir = env), class = "value_error")
Execution halted
Examples with CPU (user + system) or elapsed time > 5s
user system elapsed
tabnet_fit 29.549 0.077 29.086
autoplot.tabnet_explain 27.541 0.579 25.403
autoplot.tabnet_fit 24.431 0.146 18.250
tabnet_explain 18.454 0.016 13.712
tabnet 13.047 0.140 10.341
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 0.6.0
Check: examples
Result: ERROR
Running examples in ‘tabnet-Ex.R’ failed
The error most likely occurred in:
> ### Name: tabnet_pretrain
> ### Title: Tabnet model
> ### Aliases: tabnet_pretrain tabnet_pretrain.default
> ### tabnet_pretrain.data.frame tabnet_pretrain.formula
> ### tabnet_pretrain.recipe tabnet_pretrain.Node
>
> ### ** Examples
>
> ## Don't show:
> if (torch::torch_is_installed()) (if (getRversion() >= "3.4") withAutoprint else force)({ # examplesIf
+ ## End(Don't show)
+ data("ames", package = "modeldata")
+ pretrained <- tabnet_pretrain(Sale_Price ~ ., data = ames, epochs = 1)
+ ## Don't show:
+ }) # examplesIf
> data("ames", package = "modeldata")
> pretrained <- tabnet_pretrain(Sale_Price ~ ., data = ames, epochs = 1)
Error in `value_error()`:
! Can't convert data of class: 'NULL'
Backtrace:
▆
1. ├─(if (getRversion() >= "3.4") withAutoprint else force)(...)
2. │ └─base::source(...)
3. │ ├─base::withVisible(eval(ei, envir))
4. │ └─base::eval(ei, envir)
5. │ └─base::eval(ei, envir)
6. ├─tabnet::tabnet_pretrain(Sale_Price ~ ., data = ames, epochs = 1)
7. └─tabnet:::tabnet_pretrain.formula(...)
8. └─tabnet:::tabnet_bridge(...)
9. └─tabnet:::tabnet_train_unsupervised(...)
10. ├─coro::loop(...)
11. │ └─rlang::eval_bare(loop, env)
12. └─coro (local) `<fn>`()
13. ├─coro::is_exhausted(elt <<- iterator())
14. ├─elt <<- iterator()
15. │ └─rlang::env_poke(env, lhs, value, inherit = TRUE, create = FALSE)
16. └─torch (local) iterator()
17. └─torch::dataloader_next(iter, coro::exhausted())
18. └─iter$.next()
19. └─self$.next_data()
20. └─self$.dataset_fetcher$fetch(index)
21. └─self$collate_fn(data)
22. └─base::lapply(data, utils_data_default_convert)
23. └─torch (local) FUN(X[[i]], ...)
24. └─base::tryCatch(...)
25. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
26. └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
27. └─value[[3L]](cond)
28. └─torch:::value_error("Can't convert data of class: '{class(data)}'")
29. └─rlang::abort(glue::glue(gettext(...)[[1]], .envir = env), class = "value_error")
Execution halted
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc
Version: 0.6.0
Check: examples
Result: ERROR
Running examples in ‘tabnet-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: tabnet_pretrain
> ### Title: Tabnet model
> ### Aliases: tabnet_pretrain tabnet_pretrain.default
> ### tabnet_pretrain.data.frame tabnet_pretrain.formula
> ### tabnet_pretrain.recipe tabnet_pretrain.Node
>
> ### ** Examples
>
> ## Don't show:
> if (torch::torch_is_installed()) (if (getRversion() >= "3.4") withAutoprint else force)({ # examplesIf
+ ## End(Don't show)
+ data("ames", package = "modeldata")
+ pretrained <- tabnet_pretrain(Sale_Price ~ ., data = ames, epochs = 1)
+ ## Don't show:
+ }) # examplesIf
> data("ames", package = "modeldata")
> pretrained <- tabnet_pretrain(Sale_Price ~ ., data = ames, epochs = 1)
Error in `value_error()`:
! Can't convert data of class: 'NULL'
Backtrace:
▆
1. ├─(if (getRversion() >= "3.4") withAutoprint else force)(...)
2. │ └─base::source(...)
3. │ ├─base::withVisible(eval(ei, envir))
4. │ └─base::eval(ei, envir)
5. │ └─base::eval(ei, envir)
6. ├─tabnet::tabnet_pretrain(Sale_Price ~ ., data = ames, epochs = 1)
7. └─tabnet:::tabnet_pretrain.formula(...)
8. └─tabnet:::tabnet_bridge(...)
9. └─tabnet:::tabnet_train_unsupervised(...)
10. ├─coro::loop(...)
11. │ └─rlang::eval_bare(loop, env)
12. └─coro (local) `<fn>`()
13. ├─coro::is_exhausted(elt <<- iterator())
14. ├─elt <<- iterator()
15. │ └─rlang::env_poke(env, lhs, value, inherit = TRUE, create = FALSE)
16. └─torch (local) iterator()
17. └─torch::dataloader_next(iter, coro::exhausted())
18. └─iter$.next()
19. └─self$.next_data()
20. └─self$.dataset_fetcher$fetch(index)
21. └─self$collate_fn(data)
22. └─base::lapply(data, utils_data_default_convert)
23. └─torch (local) FUN(X[[i]], ...)
24. └─base::tryCatch(...)
25. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
26. └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
27. └─value[[3L]](cond)
28. └─torch:::value_error("Can't convert data of class: '{class(data)}'")
29. └─rlang::abort(glue::glue(gettext(...)[[1]], .envir = env), class = "value_error")
Execution halted
Examples with CPU (user + system) or elapsed time > 5s
user system elapsed
autoplot.tabnet_explain 33.616 0.974 37.185
tabnet_fit 27.461 0.204 32.353
autoplot.tabnet_fit 20.075 0.306 20.586
tabnet 13.704 0.234 14.212
tabnet_explain 11.412 0.108 12.836
Flavor: r-patched-linux-x86_64
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.