`csv_contents$metadata$save_warmup` is "true" (character), not `TRUE` (logical)

[dholstius]

Summary

Update: This error does not occur with cmdstan v2.33.1.

Running cmdstan v2.34.1 (23 January 2024) and cmdstanr v0.7.1. Reprex follows.

Attempting to fit a trivial model:

library(brms)
dat <- data.frame(y = rnorm(1000))
mod <- brm(y ~ 1, data = dat, backend = "cmdstanr")

... fails with:

Error in !is.null(csv_contents$metadata$save_warmup) && csv_contents$metadata$save_warmup: invalid 'y' type in 'x && y'

Debugging with options(error = recover), it seems that csv_contents$metadata$save_warmup is "true" (character), not TRUE (logical), when we reach lines 1437-1438 of fit.R.

Reprex

library(brms)
#> Loading required package: Rcpp
#> Loading 'brms' package (version 2.21.0). Useful instructions
#> can be found by typing help('brms'). A more detailed introduction
#> to the package is available through vignette('brms_overview').
#> 
#> Attaching package: 'brms'
#> The following object is masked from 'package:stats':
#> 
#>     ar
dat <- data.frame(y = rnorm(1000))
mod <- brm(y ~ 1, data = dat, backend = "cmdstanr")
#> Start sampling
#> Running MCMC with 4 sequential chains...
#> 
#> Chain 1 Iteration:    1 / 2000 [  0%]  (Warmup) 
#> Chain 1 Iteration:  100 / 2000 [  5%]  (Warmup) 
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#> Chain 1 finished in 0.1 seconds.
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#> Chain 2 finished in 0.1 seconds.
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#> Chain 3 finished in 0.1 seconds.
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#> Chain 4 Iteration: 1001 / 2000 [ 50%]  (Sampling) 
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#> Chain 4 Iteration: 2000 / 2000 [100%]  (Sampling) 
#> Chain 4 finished in 0.1 seconds.
#> 
#> All 4 chains finished successfully.
#> Mean chain execution time: 0.1 seconds.
#> Total execution time: 1.0 seconds.
#> Error in !is.null(csv_contents$metadata$save_warmup) && csv_contents$metadata$save_warmup: invalid 'y' type in 'x && y'

^{Created on 2024-04-24 with reprex v2.0.2}

Session info

sessioninfo::session_info()
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#>  date     2024-04-24
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[thomasgstewart]

Got the same error fitting the example in the startup guide. Like the previous commenter, I was able to verify that csv_contents$metadata$save_warmup is a character string and not a logical.

[andrjohns]

Got the same error fitting the example in the startup guide. Like the previous commenter, I was able to verify that csv_contents$metadata$save_warmup is a character string and not a logical.

Do you get the same error if you install cmdstanr from github?

remotes::install_github("stan-dev/cmdstanr")

I can't replicate the error locally

[BjarkeHautop]

I get the same error @andrjohns. Have attached all the code I ran from re-downloading and re-building to fitting.

install.packages("rstan") # version 2.32.6

remotes::install_github("stan-dev/cmdstanr")
library(cmdstanr)
rebuild_cmdstan()

cmdstan_version() # 2.35.0

file <- file.path(cmdstan_path(), "examples", "bernoulli", "bernoulli.stan")
mod <- cmdstan_model(file)

data_list <- list(N = 10, y = c(0,1,0,0,0,0,0,0,0,1))

fit <- mod$sample(
  data = data_list,
  seed = 123,
  chains = 4,
  parallel_chains = 4,
  refresh = 500 
)

stanfit <- rstan::read_stan_csv(fit$output_files())
# Error in if (max(save_warmup) == 0L) { : 
#  missing value where TRUE/FALSE needed
# In addition: Warning messages:
# 1: In parse_stancsv_comments(comments) : NAs introduced by coercion
# 2: In parse_stancsv_comments(comments) : NAs introduced by coercion
# 3: In parse_stancsv_comments(comments) : NAs introduced by coercion
# 4: In parse_stancsv_comments(comments) : NAs introduced by coercion

Session info

R version 4.4.1 (2024-06-14 ucrt)
Platform: x86_64-w64-mingw32/x64
Running under: Windows 11 x64 (build 22631)

Matrix products: default

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

other attached packages:
[1] cmdstanr_0.8.1.9000 rstan_2.32.6        StanHeaders_2.32.10

loaded via a namespace (and not attached):
 [1] tensorA_0.36.2.1     utf8_1.2.4           generics_0.1.3       magrittr_2.0.3      
 [5] grid_4.4.1           jsonlite_1.8.8       processx_3.8.4       pkgbuild_1.4.4      
 [9] backports_1.5.0      ps_1.7.7             gridExtra_2.3        fansi_1.0.6         
[13] QuickJSR_1.3.0       scales_1.3.0         codetools_0.2-20     abind_1.4-5         
[17] cli_3.6.3            rlang_1.1.4          munsell_0.5.1        withr_3.0.0         
[21] tools_4.4.1          inline_0.3.19        parallel_4.4.1       checkmate_2.3.1     
[25] dplyr_1.1.4          colorspace_2.1-0     ggplot2_3.5.1        curl_5.2.1          
[29] vctrs_0.6.5          posterior_1.6.0      R6_2.5.1             matrixStats_1.3.0   
[33] stats4_4.4.1         lifecycle_1.0.4      V8_4.4.2             pkgconfig_2.0.3     
[37] RcppParallel_5.1.8   pillar_1.9.0         gtable_0.3.5         loo_2.8.0           
[41] glue_1.7.0           data.table_1.15.4    Rcpp_1.0.12          xfun_0.45           
[45] tibble_3.2.1         tidyselect_1.2.1     rstudioapi_0.16.0    knitr_1.48          
[49] compiler_4.4.1       distributional_0.4.0

[andrjohns]

That's an issue with rstan's csv parsing, not cmdstanr

[jgabry]

I'm guessing it's related to this issue stan-dev/rstan#1131. There's an open PR to fix it that I'm reviewing at the moment.

[WillemSleegers]

Looks like this is still an issue unfortunately.

[andrjohns]

@WillemSleegers we need a bit more information here. When does the error occur for you? Through cmdstanr directly or is this through brms?

[WillemSleegers]

My bad, it looks like updating everything resolved the issue.