Add qs2 option for saving model objects

DESCRIPTION

@@ -52,6 +52,7 @@ Suggests:
     ggplot2,
     knitr (>= 1.37),
     loo (>= 2.0.0),
+    qs2,
     rmarkdown,
     testthat (>= 2.1.0),
     Rcpp

R/fit.R

@@ -108,12 +108,19 @@ CmdStanFit <- R6::R6Class(
 #'   read into R lazily (i.e., as needed), the `$save_object()` method is the
 #'   safest way to guarantee that everything has been read in before saving.
 #'
+#'   If you have a big object to save, use `format = "qs2"` to save using the
+#'   **qs2** package.
+#'
 #'   See the "Saving fitted model objects" section of the
 #'   [_Getting started with CmdStanR_](https://mc-stan.org/cmdstanr/articles/cmdstanr.html)
 #'   vignette for some suggestions on faster model saving for large models.
 #'
 #' @param file (string) Path where the file should be saved.
-#' @param ... Other arguments to pass to [base::saveRDS()] besides `object` and `file`.
+#' @param format (string) Serialization format for the object. The default is
+#'   `"rds"`. The `"qs2"` format uses `qs2::qs_save()` and requires the **qs2**
+#'   package.
+#' @param ... Other arguments to pass to [base::saveRDS()] (for `format = "rds"`)
+#'   or `qs2::qs_save()` (for `format = "qs2"`).
 #'
 #' @seealso [`CmdStanMCMC`], [`CmdStanMLE`], [`CmdStanVB`], [`CmdStanGQ`]
 #'
@@ -129,12 +136,20 @@ CmdStanFit <- R6::R6Class(
 #' fit$summary()
 #' }
 #'
-save_object <- function(file, ...) {
+save_object <- function(file, format = c("rds", "qs2"), ...) {
   self$draws()
   try(self$sampler_diagnostics(), silent = TRUE)
   try(self$init(), silent = TRUE)
   try(self$profiles(), silent = TRUE)
-  saveRDS(self, file = file, ...)
+  format <- match.arg(format)
+  if (format == "rds") {
+    saveRDS(self, file = file, ...)
+  } else {
+    if (!requireNamespace("qs2", quietly = TRUE)) {
+      stop("The 'qs2' package is required for format = \"qs2\".", call. = FALSE)
+    }
+    qs2::qs_save(self, file = file, ...)
+  }
   invisible(self)
 }
 CmdStanFit$set("public", name = "save_object", value = save_object)

tests/testthat/test-fit-shared.R

@@ -178,6 +178,16 @@ test_that("save_object() method works", {
   expect_identical(fit$summary(), s)
 })
 
+test_that("save_object() method works with qs2 format", {
+  skip_if_not_installed("qs2")
+  fit <- fits[["sample"]]
+  temp_qs_file <- tempfile(fileext = ".qs2")
+  fit$save_object(temp_qs_file, format = "qs2")
+  fit2 <- qs2::qs_read(temp_qs_file)
+  expect_identical(fit2$summary(), fit$summary())
+  expect_identical(fit2$return_codes(), fit$return_codes())
+})
+
 test_that("save_object() method works with profiles", {
   mod <- testing_model("logistic_profiling")
   utils::capture.output(

vignettes/cmdstanr.Rmd

@@ -432,9 +432,9 @@ fit_pf$print("theta")
 
 
 Let's extract the draws, make the same plot we made after running the other
-algorithms, and compare them all. approximation, and compare them all. In this
-simple example the distributions are quite similar, but this will not always be
-the case for more challenging problems.
+algorithms, and compare them all. In this simple example the distributions are
+quite similar, but this will not always be the case for more challenging
+problems.
 
 ```{r plot-compare-pf, message = FALSE}
 mcmc_hist(fit_pf$draws("theta"), binwidth = 0.025) +
@@ -469,57 +469,29 @@ For more details on the `$optimize()`, `$laplace()`, `$variational()`, and
 ## Saving fitted model objects
 
 The [`$save_object()`](http://mc-stan.org/cmdstanr/reference/fit-method-save_object.html)
-method provided by CmdStanR is the most convenient way to save a fitted model object
-to disk and ensure that all of the contents are available when reading the object back into R.
+method provided by CmdStanR is the most convenient way to save a fitted model
+object to disk and ensure that all of the contents are available when reading
+the object back into R. By default, `fit$save_object()` will use the `RDS`
+format to save the object. The saved object can then be read back into R using
+`readRDS()`.
 
 ```{r save_object, eval=FALSE}
 fit$save_object(file = "fit.RDS")
 
-# can be read back in using readRDS
 fit2 <- readRDS("fit.RDS")
 ```
 
-But if your model object is large, then
-[`$save_object()`](http://mc-stan.org/cmdstanr/reference/fit-method-save_object.html)
-could take a long time.
-[`$save_object()`](http://mc-stan.org/cmdstanr/reference/fit-method-save_object.html)
-reads the CmdStan results files into memory, stores them in the model object,
-and saves the object with `saveRDS()`. To speed up the process, you can emulate
-[`$save_object()`](http://mc-stan.org/cmdstanr/reference/fit-method-save_object.html)
-and replace `saveRDS` with the much faster `qsave()` function from the
-[`qs`](https://github.com/traversc/qs) package.
+But if your model object is large, then `fit$save_object()` can take a long time
+if saving in the default RDS format. For large objects, we recommend using the
+much faster [`qs2`](https://github.com/traversc/qs2) format. The saved object
+can then be read back into R using `qs2::qs_read()`.
 
 ```{r save_object_qs_full, eval = FALSE}
-# Load CmdStan output files into the fitted model object.
-fit$draws() # Load posterior draws into the object.
-try(fit$sampler_diagnostics(), silent = TRUE) # Load sampler diagnostics.
-try(fit$init(), silent = TRUE) # Load user-defined initial values.
-try(fit$profiles(), silent = TRUE) # Load profiling samples.
+fit$save_object(file = "fit.qs2", format = "qs2")
 
-# Save the object to a file.
-qs::qsave(x = fit, file = "fit.qs")
-
-# Read the object.
-fit2 <- qs::qread("fit.qs")
-```
-
-Storage is even faster if you discard results you do not need to save.
-The following example saves only posterior draws and discards
-sampler diagnostics, user-specified initial values, and profiling data.
-
-```{r save_object_qs_small, eval = FALSE}
-# Load posterior draws into the fitted model object and omit other output.
-fit$draws()
-
-# Save the object to a file.
-qs::qsave(x = fit, file = "fit.qs")
-
-# Read the object.
-fit2 <- qs::qread("fit.qs")
+fit2 <- qs2::qs_read("fit.qs2")
 ```
 
-See the vignette [_How does CmdStanR work?_](http://mc-stan.org/cmdstanr/articles/cmdstanr-internals.html)
-for more information about the composition of CmdStanR objects.
 
 ## Comparison with RStan
 
@@ -537,7 +509,8 @@ To ask a question please post on the Stan forums:
 
 * https://discourse.mc-stan.org/
 
-To report a bug, suggest a feature (including additions to these vignettes), or to start contributing to CmdStanR
-development (new contributors welcome!) please open an issue on GitHub:
+To report a bug, suggest a feature (including additions to these vignettes), or
+to start contributing to CmdStanR development (new contributors welcome!) please
+open an issue on GitHub:
 
 * https://github.com/stan-dev/cmdstanr/issues