Ranger engine not outputting verbose messages

[jxu]

You need a large dataset for this (not sure which built-in datasets are large enough). The ranger fit should produce progress messages like

Growing trees.. Progress: 16%. Estimated remaining time: 2 minutes, 45 seconds.
Growing trees.. Progress: 42%. Estimated remaining time: 1 minute, 25 seconds.

However, parsnip fit doesn't show progress, even with verbosity=2 setting.

rf_mod <- rand_forest(mode="classification") %>%
  set_engine("ranger") 
rf_fit <- rf_mod %>% 
  fit(price ~ ., data=train,
      control=control_parsnip(verbosity=2, catch=F))

[jxu]

I got verbose output to show up with set_engine("ranger", verbose=T, num.threads=32).
Also parsnip seems to default to 1 thread even though ranger defaults to number of CPUs. Does it change the defaults?

[EmilHvitfeldt]

With regards to the progress bar. That is happening because the verbose argument has been defaulted to be FALSE:

parsnip/R/rand_forest_data.R

Lines 119 to 135 in 907d216

	set_fit(
	model = "rand_forest",
	eng = "ranger",
	mode = "classification",
	value = list(
	interface = "data.frame",
	data = c(x = "x", y = "y", weights = "case.weights"),
	protect = c("x", "y", "weights"),
	func = c(pkg = "ranger", fun = "ranger"),
	defaults =
	list(
	num.threads = 1,
	verbose = FALSE,
	seed = expr(sample.int(10 ^ 5, 1))
	)
	)
	)

You can overwrite it by setting verbose = TRUE in set_engine() as you have seen.

rf_mod <- rand_forest(mode = "classification") %>%
  set_engine("ranger", verbose = TRUE) 

With regards to the choice of num.threads = 1. We strongly believe that code should run single threaded by default, with an easy way to opt into multi threaded calculations. This stops a number of problems from happening:

• grabbing all 1000 cores of a supercomputer is properly not ideal, but will happen when code defaults to all available cores
• when fitting multiple models in parallel, which is often done in tidymodels when you do hyperparameter tuning, you generally want to fit one model in each thread. If each of those models tries to use all cores you run into issues as well. Hence the default of num.threads = 1.

[jxu]

Ok, thanks for the info.

[jxu]

I think verbose default should be set to true. Tidyverse functions (ex. read_csv) print a lot of progress output anyway.

[github-actions]

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