TypeError: L2.__init__() got an unexpected keyword argument 'l'

[Macy-Zhao]

Hi,
It happened error as below, what can I do ? I searched some solutions on line, maybe it's the version of package.

Could you tell me the version of survivalmodels dependency packages, that you created the R package?

I have installed python package tensorflow,keras,pseudo, version

dnnsurv(data = simsurvdata(10))
2024-05-28 12:30:00.703445: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable TF_ENABLE_ONEDNN_OPTS=0.
2024-05-28 12:30:01.385713: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable TF_ENABLE_ONEDNN_OPTS=0.
Error in py_call_impl(callable, call_args$unnamed, call_args$named) :
TypeError: L2.init() got an unexpected keyword argument 'l'
Run reticulate::py_last_error() for details.

sessionInfo()
R version 4.3.1 (2023-06-16 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19045)

Matrix products: default

locale:
[1] LC_COLLATE=Chinese (Simplified)_China.utf8 LC_CTYPE=Chinese (Simplified)_China.utf8
[3] LC_MONETARY=Chinese (Simplified)_China.utf8 LC_NUMERIC=C
[5] LC_TIME=Chinese (Simplified)_China.utf8

time zone: Asia/Shanghai
tzcode source: internal

attached base packages:
[1] stats graphics grDevices utils datasets methods base

other attached packages:
[1] survivalmodels_0.1.19

loaded via a namespace (and not attached):
[1] rappdirs_0.3.3 tidyr_1.3.0 utf8_1.2.3 generics_0.1.3 stringi_1.7.12
[6] lattice_0.21-8 digest_0.6.34 magrittr_2.0.3 grid_4.3.1 pkgload_1.3.4
[11] fastmap_1.1.1 rprojroot_2.0.4 jsonlite_1.8.8 Matrix_1.6-5 pkgbuild_1.4.3
[16] sessioninfo_1.2.2 whisker_0.4.1 backports_1.4.1 urlchecker_1.0.1 tfruns_1.5.2
[21] promises_1.2.1 tensorflow_2.16.0 fansi_1.0.4 purrr_1.0.1 cli_3.6.1
[26] shiny_1.8.0 KMsurv_0.1-5 rlang_1.1.1 ellipsis_0.3.2 withr_3.0.0
[31] keras_2.15.0 remotes_2.4.2.1 base64enc_0.1-3 geepack_1.3.10 cachem_1.0.8
[36] devtools_2.4.5 pseudo_1.4.3 tools_4.3.1 memoise_2.0.1 dplyr_1.1.2
[41] zeallot_0.1.0 httpuv_1.6.14 here_1.0.1 broom_1.0.5 reticulate_1.37.0
[46] vctrs_0.6.3 R6_2.5.1 mime_0.12 png_0.1-8 lifecycle_1.0.4
[51] stringr_1.5.1 fs_1.6.3 htmlwidgets_1.6.4 usethis_2.2.3 MASS_7.3-60.0.1
[56] miniUI_0.1.1.1 pkgconfig_2.0.3 pillar_1.9.0 later_1.3.2 glue_1.6.2
[61] profvis_0.3.8 Rcpp_1.0.12 tidyselect_1.2.0 tibble_3.2.1 rstudioapi_0.15.0
[66] xtable_1.8-4 htmltools_0.5.7 compiler_4.3.1

[RaphaelS1]

Hey the package dependencies can be seen here

So pandas v1.4.4, tabnet v0.1.4.1, and latest versions of torch and pycox.

sorry don't think I can be much more help with this one