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run.R
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# CmdStanRun --------------------------------------------------------------
#' Run CmdStan using a specified configuration
#'
#' The internal `CmdStanRun` R6 class handles preparing the call to CmdStan
#' (using the `CmdStanArgs` object), setting up the external processes (using
#' the `CmdStanProcs` object), and provides methods for running CmdStan's
#' multiple methods/algorithms, running CmdStan utilities (e.g. `stansummary`),
#' and saving the output files.
#'
#' @noRd
#' @param args A `CmdStanArgs` object.
#' @param procs A `CmdStanProcs` object.
#'
CmdStanRun <- R6::R6Class(
classname = "CmdStanRun",
public = list(
args = NULL,
procs = NULL,
initialize = function(args, procs) {
checkmate::assert_r6(args, classes = "CmdStanArgs")
checkmate::assert_r6(procs, classes = "CmdStanProcs")
self$args <- args
self$procs <- procs
private$output_files_ <- self$new_output_files()
if (cmdstan_version() >= "2.26.0") {
private$profile_files_ <- self$new_profile_files()
}
if (cmdstan_version() >= "2.34.0" && !is.null(self$args$save_cmdstan_config) && as.logical(self$args$save_cmdstan_config)) {
private$config_files_ <- self$new_config_files()
}
if (cmdstan_version() >= "2.34.0" && !is.null(self$args$method_args$save_metric) && as.logical(self$args$method_args$save_metric)) {
private$metric_files_ <- self$new_metric_files()
}
if (self$args$save_latent_dynamics) {
private$latent_dynamics_files_ <- self$new_latent_dynamics_files()
}
if (os_is_wsl()) {
# While the executable built under WSL will be stored in the Windows
# filesystem alongside the model code, we place a copy in a WSL temp
# directory prior to execution to avoid IO perfomance impacts
wsl_tmpdir <- wsl_tempdir()
file.copy(from = args$exe_file,
to = file.path(wsl_dir_prefix(), wsl_tmpdir))
args$exe_file <- file.path(wsl_tmpdir, basename(args$exe_file))
processx::run("wsl", args = c("chmod", "+x", args$exe_file),
error_on_status = FALSE)
}
invisible(self)
},
num_procs = function() self$procs$num_procs(),
proc_ids = function() self$procs$proc_ids(),
exe_file = function() self$args$exe_file,
stan_code = function() self$args$stan_code,
model_methods_env = function() self$args$model_methods_env,
standalone_env = function() self$args$standalone_env,
model_name = function() self$args$model_name,
method = function() self$args$method,
data_file = function() self$args$data_file,
new_output_files = function() {
self$args$new_files(type = "output")
},
new_latent_dynamics_files = function() {
self$args$new_files(type = "diagnostic")
},
new_profile_files = function() {
self$args$new_files(type = "profile")
},
new_config_files = function() {
# because CmdStan 2.34 uses the output_file name as the base for the config file
paste0(tools::file_path_sans_ext(private$output_files_), "_config.json")
},
new_metric_files = function() {
# because CmdStan 2.34 uses the output_file name as the base for the metric file
paste0(tools::file_path_sans_ext(private$output_files_), "_metric.json")
},
config_files = function(include_failed = FALSE) {
files <- private$config_files_
files_win_path <- sapply(private$config_files_, wsl_safe_path, revert = TRUE)
if (include_failed) {
files
} else {
ok <- self$procs$is_finished() | self$procs$is_queued()
files[ok]
}
},
metric_files = function(include_failed = FALSE) {
files <- private$metric_files_
files_win_path <- sapply(private$metric_files_, wsl_safe_path, revert = TRUE)
if (include_failed) {
files
} else {
ok <- self$procs$is_finished() | self$procs$is_queued()
files[ok]
}
},
latent_dynamics_files = function(include_failed = FALSE) {
if (!length(private$latent_dynamics_files_)) {
stop(
"No latent dynamics files found. ",
"Set 'save_latent_dynamics=TRUE' when fitting the model.",
call. = FALSE
)
}
if (include_failed) {
private$latent_dynamics_files_
} else {
ok <- self$procs$is_finished() | self$procs$is_queued()
private$latent_dynamics_files_[ok]
}
},
output_files = function(include_failed = FALSE) {
if (include_failed) {
private$output_files_
} else {
ok <- self$procs$is_finished() | self$procs$is_queued()
private$output_files_[ok]
}
},
profile_files = function(include_failed = FALSE) {
files <- private$profile_files_
if (!length(files) || !any(file.exists(files))) {
stop(
"No profile files found. ",
"The model that produced the fit did not use any profiling.",
call. = FALSE
)
}
if (include_failed) {
files
} else {
ok <- self$procs$is_finished() | self$procs$is_queued()
files[ok]
}
},
save_output_files = function(dir = ".",
basename = NULL,
timestamp = TRUE,
random = TRUE) {
current_files <- self$output_files(include_failed = TRUE)
new_paths <- copy_temp_files(
current_paths = current_files,
new_dir = dir,
new_basename = basename %||% self$model_name(),
ids = self$procs$proc_ids(),
ext = ".csv",
timestamp = timestamp,
random = random
)
file.remove(current_files[!current_files %in% new_paths])
private$output_files_ <- new_paths
message(
"Moved ",
length(current_files),
" files and set internal paths to new locations:\n",
paste("-", new_paths, collapse = "\n")
)
private$output_files_saved_ <- TRUE
invisible(new_paths)
},
save_latent_dynamics_files = function(dir = ".",
basename = NULL,
timestamp = TRUE,
random = TRUE) {
current_files <- self$latent_dynamics_files(include_failed = TRUE) # used so we get error if 0 files
new_paths <- copy_temp_files(
current_paths = current_files,
new_dir = dir,
new_basename = paste0(basename %||% self$model_name(), "-diagnostic"),
ids = self$proc_ids(),
ext = ".csv",
timestamp = timestamp,
random = random
)
file.remove(current_files[!current_files %in% new_paths])
private$latent_dynamics_files_ <- new_paths
message(
"Moved ",
length(current_files),
" files and set internal paths to new locations:\n",
paste("-", new_paths, collapse = "\n")
)
private$latent_dynamics_files_saved_ <- TRUE
invisible(new_paths)
},
save_profile_files = function(dir = ".",
basename = NULL,
timestamp = TRUE,
random = TRUE) {
current_files <- self$profile_files(include_failed = TRUE) # used so we get error if 0 files
new_paths <- copy_temp_files(
current_paths = current_files,
new_dir = dir,
new_basename = paste0(basename %||% self$model_name(), "-profile"),
ids = self$proc_ids(),
ext = ".csv",
timestamp = timestamp,
random = random
)
file.remove(current_files[!current_files %in% new_paths])
private$profile_files_ <- new_paths
message(
"Moved ",
length(current_files),
" files and set internal paths to new locations:\n",
paste("-", new_paths, collapse = "\n")
)
private$profile_files_saved_ <- TRUE
invisible(new_paths)
},
save_data_file = function(dir = ".",
basename = NULL,
timestamp = TRUE,
random = TRUE) {
new_path <- copy_temp_files(
current_paths = self$data_file(),
new_dir = dir,
new_basename = basename %||% self$model_name(),
ids = NULL,
ext = tools::file_ext(self$data_file()),
timestamp = timestamp,
random = random
)
if (new_path != self$data_file()) {
file.remove(self$data_file())
}
self$args$data_file <- new_path
message("Moved data file and set internal path to new location:\n",
"- ", new_path)
invisible(new_path)
},
save_config_files = function(dir = ".",
basename = NULL,
timestamp = TRUE,
random = TRUE) {
current_files <- self$config_files(include_failed = TRUE) # used so we get error if 0 files
new_paths <- copy_temp_files(
current_paths = current_files,
new_dir = dir,
new_basename = paste0(basename %||% self$model_name(), "-config"),
ids = self$proc_ids(),
ext = ".json",
timestamp = timestamp,
random = random
)
file.remove(current_files[!current_files %in% new_paths])
private$config_files_ <- new_paths
message(
"Moved ",
length(current_files),
" files and set internal paths to new locations:\n",
paste("-", new_paths, collapse = "\n")
)
invisible(new_paths)
},
save_metric_files = function(dir = ".",
basename = NULL,
timestamp = TRUE,
random = TRUE) {
current_files <- self$metric_files(include_failed = TRUE) # used so we get error if 0 files
new_paths <- copy_temp_files(
current_paths = current_files,
new_dir = dir,
new_basename = paste0(basename %||% self$model_name(), "-metric"),
ids = self$proc_ids(),
ext = ".json",
timestamp = timestamp,
random = random
)
file.remove(current_files[!current_files %in% new_paths])
private$metric_files_ <- new_paths
message(
"Moved ",
length(current_files),
" files and set internal paths to new locations:\n",
paste("-", new_paths, collapse = "\n")
)
invisible(new_paths)
},
command = function() self$args$command(),
command_args = function() {
if (!length(private$command_args_)) {
# create a list of character vectors (one per run/chain) of cmdstan arguments
private$command_args_ <- lapply(self$procs$proc_ids(), function(j) {
self$args$compose_all_args(
idx = j,
output_file = private$output_files_[j],
profile_file = private$profile_files_[j],
latent_dynamics_file = private$latent_dynamics_files_[j] # maybe NULL
)
})
}
private$command_args_
},
run_cmdstan = function() {
run_method <- paste0("run_", self$method(), "_")
private[[run_method]]()
},
run_cmdstan_mpi = function(mpi_cmd, mpi_args) {
private$run_sample_(mpi_cmd, mpi_args)
},
#' Run `bin/stansummary` or `bin/diagnose`
#' @param tool The name of the tool in `bin/` to run.
#' @param flags An optional character vector of flags (e.g. `c("--sig_figs=1")`).
#' @noRd
run_cmdstan_tool = function(tool = c("stansummary", "diagnose"), flags = NULL) {
if (self$method() == "optimize") {
stop("Not available for optimize method.", call. = FALSE)
}
if (self$method() == "laplace") {
stop("Not available for laplace method.", call. = FALSE)
}
if (self$method() == "generate_quantities") {
stop("Not available for generate_quantities method.", call. = FALSE)
}
tool <- match.arg(tool)
if (!length(self$output_files(include_failed = FALSE))) {
stop("No CmdStan runs finished successfully. ",
"Unable to run bin/", tool, ".", call. = FALSE)
}
target_exe <- file.path("bin", cmdstan_ext(tool))
check_target_exe(target_exe)
withr::with_path(
c(
toolchain_PATH_env_var(),
tbb_path()
),
run_log <- wsl_compatible_run(
command = target_exe,
args = c(
sapply(self$output_files(include_failed = FALSE),
wsl_safe_path),
flags),
wd = cmdstan_path(),
echo = TRUE,
echo_cmd = is_verbose_mode(),
error_on_status = TRUE
)
)
},
time = function() {
if (self$method() %in% c("laplace", "optimize", "variational", "pathfinder")) {
time <- list(total = self$procs$total_time())
} else if (self$method() == "generate_quantities") {
chain_time <- data.frame(
chain_id = self$procs$proc_ids()[self$procs$is_finished()],
total = self$procs$proc_total_time()[self$procs$is_finished()]
)
time <- list(total = self$procs$total_time(), chains = chain_time)
} else {
chain_ids <- names(self$procs$is_finished())
chain_time <- data.frame(
chain_id = as.vector(self$procs$proc_ids()),
warmup = as.vector(self$procs$proc_section_time("warmup")),
sampling = as.vector(self$procs$proc_section_time("sampling")),
total = as.vector(self$procs$proc_total_time()[chain_ids])
)
time <- list(total = self$procs$total_time(), chains = chain_time)
}
time
}
),
private = list(
output_files_ = character(),
profile_files_ = NULL,
output_files_saved_ = FALSE,
latent_dynamics_files_ = NULL,
latent_dynamics_files_saved_ = FALSE,
profile_files_saved_ = FALSE,
config_files_ = NULL,
metric_files_ = NULL,
config_files_saved_ = FALSE,
metric_files_saved_ = FALSE,
command_args_ = list(),
finalize = function() {
if (self$args$using_tempdir) {
temp_files <- c(
if (!private$output_files_saved_)
self$output_files(include_failed = TRUE),
if (self$args$save_latent_dynamics && !private$latent_dynamics_files_saved_)
self$latent_dynamics_files(include_failed = TRUE),
if (cmdstan_version() > "2.25.0" && !private$profile_files_saved_)
private$profile_files_,
if (cmdstan_version() > "2.34.0" &&
!is.null(self$args$save_cmdstan_config) &&
as.logical(self$args$save_cmdstan_config) &&
!private$config_files_saved_)
self$config_files(include_failed = TRUE),
if (cmdstan_version() > "2.34.0" &&
!(is.null(self$args$method_args$save_metric)) &&
as.logical(self$args$method_args$save_metric) &&
!private$metric_files_saved_)
self$metric_files(include_failed = TRUE)
)
unlink(temp_files)
}
}
)
)
# run helpers -------------------------------------------------
check_target_exe <- function(exe) {
exe_path <- file.path(cmdstan_path(), exe)
if (!file.exists(exe_path)) {
withr::with_envvar(
c("HOME" = short_path(Sys.getenv("HOME"))),
withr::with_path(
c(
toolchain_PATH_env_var(),
tbb_path()
),
run_log <- wsl_compatible_run(
command = make_cmd(),
args = exe,
wd = cmdstan_path(),
echo_cmd = TRUE,
echo = TRUE,
error_on_status = TRUE
)
)
)
}
}
.run_sample <- function(mpi_cmd = NULL, mpi_args = NULL) {
procs <- self$procs
on.exit(procs$cleanup(), add = TRUE)
if (!is.null(mpi_cmd)) {
if (is.null(mpi_args)) {
mpi_args <- list()
}
mpi_args[["exe"]] <- wsl_safe_path(self$exe_file())
}
if (procs$num_procs() == 1) {
start_msg <- "Running MCMC with 1 chain"
} else if (procs$num_procs() == procs$parallel_procs()) {
start_msg <- paste0("Running MCMC with ", procs$num_procs(), " parallel chains")
} else {
if (procs$parallel_procs() == 1) {
if (!is.null(mpi_cmd)) {
if (!is.null(mpi_args[["n"]])) {
mpi_n_process <- mpi_args[["n"]]
} else if (!is.null(mpi_args[["np"]])) {
mpi_n_process <- mpi_args[["np"]]
}
if (is.null(mpi_n_process)) {
start_msg <- paste0("Running MCMC with ", procs$num_procs(), " chains using MPI")
} else {
start_msg <- paste0("Running MCMC with ", procs$num_procs(), " chains using MPI with ", mpi_n_process, " processes")
}
} else {
start_msg <- paste0("Running MCMC with ", procs$num_procs(), " sequential chains")
}
} else {
start_msg <- paste0("Running MCMC with ", procs$num_procs(), " chains, at most ", procs$parallel_procs(), " in parallel")
}
}
if (is.null(procs$threads_per_proc())) {
if (procs$show_stdout_messages()) {
cat(paste0(start_msg, "...\n\n"))
}
} else {
if (procs$show_stdout_messages()) {
cat(paste0(start_msg, ", with ", procs$threads_per_proc(), " thread(s) per chain...\n\n"))
}
Sys.setenv("STAN_NUM_THREADS" = as.integer(procs$threads_per_proc()))
# Windows environment variables have to be explicitly exported to WSL
if (os_is_wsl()) {
Sys.setenv("WSLENV"="STAN_NUM_THREADS/u")
}
}
start_time <- Sys.time()
chains <- procs$proc_ids()
chain_ind <- 1
while (!all(procs$is_finished() | procs$is_failed())) {
while (procs$active_procs() != procs$parallel_procs() && procs$any_queued()) {
chain_id <- chains[chain_ind]
procs$new_proc(
id = chain_id,
command = self$command(),
args = self$command_args()[[chain_id]],
wd = dirname(self$exe_file()),
mpi_cmd = mpi_cmd,
mpi_args = mpi_args
)
procs$mark_proc_start(chain_id)
procs$set_active_procs(procs$active_procs() + 1)
chain_ind <- chain_ind + 1
}
start_active_procs <- procs$active_procs()
while (procs$active_procs() == start_active_procs &&
procs$active_procs() > 0) {
procs$wait(0.1)
procs$poll(0)
for (chain_id in chains) {
if (!procs$is_queued(chain_id)) {
procs$process_output(chain_id)
procs$process_error_output(chain_id)
}
}
procs$set_active_procs(procs$num_alive())
}
procs$check_finished()
}
procs$set_total_time(as.double((Sys.time() - start_time), units = "secs"))
procs$report_time()
}
CmdStanRun$set("private", name = "run_sample_", value = .run_sample)
.run_generate_quantities <- function() {
procs <- self$procs
on.exit(procs$cleanup(), add = TRUE)
if (procs$num_procs() == 1) {
start_msg <- "Running standalone generated quantities after 1 MCMC chain"
} else if (procs$num_procs() == procs$parallel_procs()) {
start_msg <- paste0("Running standalone generated quantities after ", procs$num_procs(), " MCMC chains, all chains in parallel ")
} else {
if (procs$parallel_procs() == 1) {
start_msg <- paste0("Running standalone generated quantities after ", procs$num_procs(), " MCMC chains, 1 chain at a time ")
} else {
start_msg <- paste0("Running standalone generated quantities after ", procs$num_procs(), " MCMC chains, ", procs$parallel_procs(), " chains at a time ")
}
}
if (is.null(procs$threads_per_proc())) {
if (procs$show_stdout_messages()) {
cat(paste0(start_msg, "...\n\n"))
}
} else {
if (procs$show_stdout_messages()) {
cat(paste0(start_msg, ", with ", procs$threads_per_proc(), " thread(s) per chain...\n\n"))
}
Sys.setenv("STAN_NUM_THREADS" = as.integer(procs$threads_per_proc()))
# Windows environment variables have to be explicitly exported to WSL
if (os_is_wsl()) {
Sys.setenv("WSLENV"="STAN_NUM_THREADS/u")
}
}
start_time <- Sys.time()
chains <- procs$proc_ids()
chain_ind <- 1
while (!all(procs$is_finished() | procs$is_failed())) {
while (procs$active_procs() != procs$parallel_procs() && procs$any_queued()) {
chain_id <- chains[chain_ind]
procs$new_proc(
id = chain_id,
command = self$command(),
args = self$command_args()[[chain_id]],
wd = dirname(self$exe_file())
)
procs$mark_proc_start(chain_id)
procs$set_active_procs(procs$active_procs() + 1)
chain_ind <- chain_ind + 1
}
start_active_procs <- procs$active_procs()
while (procs$active_procs() == start_active_procs &&
procs$active_procs() > 0) {
procs$wait(0.1)
procs$poll(0)
for (chain_id in chains) {
if (!procs$is_queued(chain_id)) {
procs$process_output(chain_id)
procs$process_error_output(chain_id)
}
}
procs$set_active_procs(procs$num_alive())
}
procs$check_finished()
}
procs$set_total_time(as.double((Sys.time() - start_time), units = "secs"))
procs$report_time()
}
CmdStanRun$set("private", name = "run_generate_quantities_", value = .run_generate_quantities)
.run_other <- function() {
procs <- self$procs
if (!is.null(procs$threads_per_proc())) {
Sys.setenv("STAN_NUM_THREADS" = as.integer(procs$threads_per_proc()))
# Windows environment variables have to be explicitly exported to WSL
if (os_is_wsl()) {
Sys.setenv("WSLENV"="STAN_NUM_THREADS/u")
}
}
start_time <- Sys.time()
id <- 1
procs$new_proc(
id = id,
command = self$command(),
args = self$command_args()[[id]],
wd = dirname(self$exe_file())
)
procs$set_active_procs(1)
procs$mark_proc_start(id)
procs$set_proc_state(id = id, new_state = 2) # active process
while (procs$active_procs() == 1) {
procs$wait(0.1)
procs$poll(0)
if (!procs$is_queued(id)) {
procs$process_output(id)
procs$process_error_output(id)
}
procs$set_active_procs(procs$num_alive())
}
procs$process_output(id)
procs$process_error_output(id)
successful_fit <- FALSE
if (self$method() %in% "optimize") { # QUESTION: should this include laplace?
if (procs$proc_state(id = id) > 3) {
successful_fit <- TRUE
}
} else if (self$method() == "pathfinder") {
if (procs$proc_state(id = id) > 3 | procs$get_proc(id)$get_exit_status() == 0) {
successful_fit <- TRUE
}
} else if (procs$get_proc(id)$get_exit_status() == 0) {
successful_fit <- TRUE
}
if (successful_fit) {
procs$set_proc_state(id = id, new_state = 5) # mark_proc_stop will mark this process successful
} else {
procs$set_proc_state(id = id, new_state = 4) # mark_proc_stop will mark this process unsuccessful
}
procs$mark_proc_stop(id)
procs$set_total_time(as.double((Sys.time() - start_time), units = "secs"))
procs$report_time()
}
CmdStanRun$set("private", name = "run_optimize_", value = .run_other)
CmdStanRun$set("private", name = "run_laplace_", value = .run_other)
CmdStanRun$set("private", name = "run_variational_", value = .run_other)
CmdStanRun$set("private", name = "run_pathfinder_", value = .run_other)
.run_diagnose <- function() {
procs <- self$procs
if (!is.null(procs$threads_per_proc())) {
Sys.setenv("STAN_NUM_THREADS" = as.integer(procs$threads_per_proc()))
# Windows environment variables have to be explicitly exported to WSL
if (os_is_wsl()) {
Sys.setenv("WSLENV"="STAN_NUM_THREADS/u")
}
}
stdout_file <- tempfile()
stderr_file <- tempfile()
withr::with_path(
c(
toolchain_PATH_env_var(),
tbb_path()
),
ret <- wsl_compatible_run(
command = self$command(),
args = self$command_args()[[1]],
wd = dirname(self$exe_file()),
stderr = stderr_file,
stdout = stdout_file,
error_on_status = FALSE
)
)
if (is.na(ret$status) || ret$status != 0) {
if (file.exists(stdout_file)) {
cat(readLines(stdout_file), sep = "\n")
}
if (file.exists(stderr_file)) {
cat(readLines(stderr_file), sep = "\n")
}
stop(
"Diagnose failed with the status code ", ret$status, "!\n",
"See the output above for more information.",
call. = FALSE
)
}
}
CmdStanRun$set("private", name = "run_diagnose_", value = .run_diagnose)
# CmdStanProcs ------------------------------------------------------------
#' System processes for running CmdStan using the `processx::process` R6 class
#'
#' The internal `CmdStanProcs` R6 class provides methods for setting up the
#' system processes for running CmdStan, monitoring the status of the processes,
#' and handling stdout and stderr.
#'
#' @noRd
#' @param num_procs The number of CmdStan processes to start for a run. For MCMC
#' this is the number of chains. Currently for other methods this must be set
#' to 1.
#' @param parallel_procs The maximum number of processes to run in parallel.
#' Currently for non-sampling this must be set to 1.
#' @param threads_per_proc The number of threads to use per process to run
#' parallel sections of model.
#'
CmdStanProcs <- R6::R6Class(
classname = "CmdStanProcs",
public = list(
initialize = function(num_procs,
parallel_procs = NULL,
threads_per_proc = NULL,
show_stderr_messages = TRUE,
show_stdout_messages = TRUE) {
checkmate::assert_integerish(num_procs, lower = 1, len = 1, any.missing = FALSE)
checkmate::assert_integerish(parallel_procs, lower = 1, len = 1, any.missing = FALSE, null.ok = TRUE)
checkmate::assert_integerish(threads_per_proc, lower = 1, len = 1, null.ok = TRUE)
private$num_procs_ <- as.integer(num_procs)
if (is.null(parallel_procs)) {
private$parallel_procs_ <- private$num_procs_
} else {
private$parallel_procs_ <- as.integer(parallel_procs)
}
private$threads_per_proc_ <- as.integer(threads_per_proc)
private$threads_per_proc_ <- threads_per_proc
private$active_procs_ <- 0
private$proc_ids_ <- seq_len(num_procs)
zeros <- rep(0, num_procs)
names(zeros) <- private$proc_ids_
private$proc_state_ <- zeros
private$proc_start_time_ <- zeros
private$proc_total_time_ <- zeros
private$show_stderr_messages_ <- show_stderr_messages
private$show_stdout_messages_ <- show_stdout_messages
invisible(self)
},
show_stdout_messages = function () {
private$show_stdout_messages_
},
show_stderr_messages = function () {
private$show_stderr_messages_
},
num_procs = function() {
private$num_procs_
},
parallel_procs = function() {
private$parallel_procs_
},
threads_per_proc = function() {
private$threads_per_proc_
},
proc_ids = function() {
private$proc_ids_
},
cleanup = function() {
lapply(private$processes_, function(p) {
try(p$kill_tree(), silent = TRUE)
})
invisible(self)
},
poll = function(ms) { # time in milliseconds
processx::poll(private$processes_, ms)
},
wait = function(s) { # time in seconds
Sys.sleep(s)
},
get_proc = function(id) {
private$processes_[[id]]
},
new_proc = function(id, command, args, wd, mpi_cmd = NULL, mpi_args = NULL) {
if (!is.null(mpi_cmd)) {
exe_name <- mpi_args[["exe"]]
mpi_args[["exe"]] <- NULL
mpi_args_vector <- c()
for (i in names(mpi_args)) {
mpi_args_vector <- c(paste0("-", i), mpi_args[[i]], mpi_args_vector)
}
args <- c(mpi_args_vector, exe_name, args)
command <- mpi_cmd
}
withr::with_path(
c(
toolchain_PATH_env_var(),
tbb_path()
),
private$processes_[[id]] <- wsl_compatible_process_new(
command = command,
args = args,
wd = wd,
stdout = "|",
stderr = "|",
echo_cmd = is_verbose_mode()
)
)
invisible(self)
},
active_procs = function() {
private$active_procs_
},
set_active_procs = function(procs) {
private$active_procs_ <- procs
invisible(NULL)
},
proc_section_time = function(section, id = NULL) {
if (section %in% colnames(private$proc_section_time_)) {
if (is.null(id)) {
return(private$proc_section_time_[, section])
}
private$proc_section_time_[id, section]
}else {
NA_real_
}
},
proc_total_time = function(id = NULL) {
if (is.null(id)) {
return(private$proc_total_time_[self$is_finished()])
}
private$proc_total_time_[[id]]
},
total_time = function() {
# scalar overall time
private$total_time_
},
set_total_time = function(time) {
private$total_time_ <- as.numeric(time)
invisible(self)
},
check_finished = function() {
for (id in private$proc_ids_) {
if (self$is_still_working(id) && !self$is_queued(id) && !self$is_alive(id)) {
# if the process just finished make sure we process all
# input and mark the process finished
self$process_output(id)
self$process_error_output(id)
self$mark_proc_stop(id)
self$report_time(id)
}
}
invisible(self)
},
is_alive = function(id = NULL) {
if (!is.null(id)) {
return(private$processes_[[id]]$is_alive())
}
sapply(private$processes_, function(x) x$is_alive())
},
is_still_working = function(id = NULL) {
self$proc_state(id) < 6
},
is_finished = function(id = NULL) {
self$proc_state(id) == 6
},
is_failed = function(id = NULL) {
self$proc_state(id) == 7
},
is_queued = function(id = NULL) {
self$proc_state(id) == 0
},
num_alive = function() {
sum(self$is_alive())
},
num_failed = function() {
sum(self$proc_state() == 7)
},
any_queued = function() {
any(self$is_queued())
},
proc_output = function(id = NULL) {
out <- private$proc_output_
if (is.null(id)) {
return(out)
}
out[[id]]
},
proc_state = function(id = NULL) {
if (is.null(id)) {
return(private$proc_state_)
}
private$proc_state_[[id]]
},
set_proc_state = function(id, new_state) {
private$proc_state_[[id]] <- new_state
},
mark_proc_start = function(id) {
private$proc_state_[[id]] <- 1
private$proc_output_[[id]] <- c("")
invisible(self)
},
mark_proc_stop = function(id) {
if (private$proc_state_[[id]] == 5) {
private$proc_state_[[id]] <- 6
} else {
private$proc_state_[[id]] <- 7
}
invisible(self)
},
is_error_message = function(line) {
startsWith(line, "Exception:") ||
(grepl("either mistyped or misplaced.", line, perl = TRUE)) ||
(grepl("A method must be specified!", line, perl = TRUE)) ||
(grepl("is not a valid value for", line, perl = TRUE))
},
process_error_output = function(id) {
err_out <- self$get_proc(id)$read_error_lines()
if (length(err_out)) {
for (err_line in err_out) {
private$proc_output_[[id]] <- c(private$proc_output_[[id]], err_line)
if (private$show_stderr_messages_) {
message("Chain ", id, " ", err_line)
}
}
}
},
process_output = function(id) {
out <- self$get_proc(id)$read_output_lines()
if (length(out) == 0) {
return(NULL)
}
for (line in out) {
private$proc_output_[[id]] <- c(private$proc_output_[[id]], line)
if (nzchar(line)) {
if (grepl("Optimization terminated with error", line, perl = TRUE)) {
self$set_proc_state(id, new_state = 3.5)
}
if (grepl("Optimization terminated normally", line, perl = TRUE)) {
self$set_proc_state(id, new_state = 4)
}
if (self$proc_state(id) == 2 && grepl("refresh = ", line, perl = TRUE)) {
self$set_proc_state(id, new_state = 2.5)
}
if (self$proc_state(id) == 2.5 && grepl("Exception:", line, fixed = TRUE)) {
self$set_proc_state(id, new_state = 3)
}
if (private$proc_state_[[id]] == 3.5) {
message(line)
} else if ((private$show_stdout_messages_ && private$proc_state_[[id]] >= 3) || is_verbose_mode()) {
cat(line, collapse = "\n")
}
} else {
# after the metadata is printed and we found a blank line
# this represents the start of fitting
if (self$proc_state(id) == 2.5) {
self$set_proc_state(id, new_state = 3)
}
}
}
invisible(self)
},
report_time = function(id = NULL) {
if (self$proc_state(id) == 7) {
warning("Fitting finished unexpectedly! Use the $output() method for more information.\n", immediate. = TRUE, call. = FALSE)
}
if (private$show_stdout_messages_) {
cat("Finished in ",
base::format(round(self$total_time(), 1), nsmall = 1),
"seconds.\n")
}
},
return_codes = function() {
ret <- c()
for (id in private$proc_ids_) {
ret <- c(ret, self$get_proc(id)$get_exit_status())
}
ret
}
),
private = list(
processes_ = NULL, # will be list of processx::process objects
proc_ids_ = integer(),
num_procs_ = integer(),
parallel_procs_ = integer(),
active_procs_ = integer(),
threads_per_proc_ = integer(),
proc_state_ = NULL,
proc_start_time_ = NULL,
proc_total_time_ = NULL,
proc_section_time_ = data.frame(),
proc_output_ = list(),
proc_error_ouput_ = list(),
total_time_ = numeric(),
show_stderr_messages_ = TRUE,
show_stdout_messages_ = TRUE
)
)
# Process R6 class that overrides the default
# function for processing the output
CmdStanMCMCProcs <- R6::R6Class(
classname = "CmdStanMCMCProcs",
inherit = CmdStanProcs,
public = list(
process_output = function(id) {
out <- self$get_proc(id)$read_output_lines()
if (length(out) == 0) {
return(invisible(NULL))
}
for (line in out) {
private$proc_output_[[id]] <- c(private$proc_output_[[id]], line)
if (nzchar(line)) {
ignore_line <- FALSE
last_section_start_time <- private$proc_section_time_[id, "last_section_start"]
state <- private$proc_state_[[id]]
# State machine for reading stdout.
# 0 - chain has not started yet
# 1 - chain is initializing (before iterations) and no output is printed
# 2 - chain is initializing and inital values were rejected (output is printed)