parallel.md
In tune: Tidy Tuning Tools

no parallelism

Code
  tune:::choose_framework(verbose = TRUE)
Message
  mirai is not active.
  future is active with 1 worker.
  Too few workers for parallel processing.
Output
  [1] "sequential"

enable future parallelism

Code
  tune:::choose_framework(verbose = TRUE)
Message
  mirai is not active.
  future is active with 1 worker.
  Too few workers for parallel processing.
Output
  [1] "sequential"

Code
  tune:::choose_framework(verbose = TRUE)
Message
  mirai is not active.
  future is active with 2 workers.
  future will be used for parallel processing}.
Output
  [1] "future"

Code
  tune:::choose_framework(control = ctrl_no, verbose = TRUE)
Output
  [1] "sequential"

Code
  tune:::choose_framework(control = ctrl_java, verbose = TRUE)
Message
  These packages cannot be used with explicit parallel processing: rJava.
Output
  [1] "sequential"

Code
  tune:::choose_framework(verbose = TRUE)
Message
  mirai is not active.
  future is active with 1 worker.
  Too few workers for parallel processing.
Output
  [1] "sequential"

Code
  tune:::choose_framework(verbose = TRUE)
Message
  mirai is not active.
  future is active with 1 worker.
  Too few workers for parallel processing.
Output
  [1] "sequential"

enable mirai parallelism

Code
  tune:::choose_framework(verbose = TRUE)
Message
  mirai is not active.
  future is active with 1 worker.
  Too few workers for parallel processing.
Output
  [1] "sequential"

Code
  tune:::choose_framework(verbose = TRUE)
Message
  mirai is active with 2 workers.
  future is active with 1 worker.
  mirai will be used for parallel processing}.
Output
  [1] "mirai"

Code
  tune:::choose_framework(control = ctrl_no, verbose = TRUE)
Output
  [1] "sequential"

Code
  tune:::choose_framework(control = ctrl_java, verbose = TRUE)
Message
  These packages cannot be used with explicit parallel processing: rJava.
Output
  [1] "sequential"

Code
  tune:::choose_framework(verbose = TRUE)
Message
  mirai is active with 1 worker.
  future is active with 1 worker.
  Too few workers for parallel processing.
Output
  [1] "sequential"

Code
  tune:::choose_framework(verbose = TRUE)
Message
  mirai is not active.
  future is active with 1 worker.
  Too few workers for parallel processing.
Output
  [1] "sequential"

break parallelism tie

Code
  tune:::choose_framework(verbose = TRUE)
Message
  mirai is active with 2 workers.
  future is active with 2 workers.
  Multiple workers exist for both mirai and future; falling back to the default of mirai.
Output
  [1] "mirai"

loop execution code

Code
  tune:::loop_call("resamples", "sequential", list())
Output
  lapply(resamples, loop_over_all_stages, grid = grid, static = static)

Code
  tune:::loop_call("resamples", "sequential", list(a = quote(a)))
Output
  lapply(resamples, loop_over_all_stages, grid = grid, static = static, 
      a = a)

Code
  tune:::loop_call("everything", "sequential", list())
Output
  lapply(inds, loop_over_all_stages2, resamples = resamples, grid = candidates, 
      static = static)

Code
  tune:::loop_call("everything", "sequential", list(a = quote(a)))
Output
  lapply(inds, loop_over_all_stages2, resamples = resamples, grid = candidates, 
      static = static, a = a)

Code
  tune:::loop_call("resamples", "future", list())
Output
  future.apply::future_lapply(resamples, loop_over_all_stages, 
      grid = grid, static = static, future.label = "tune-grid-%d", 
      future.stdout = TRUE, future.seed = TRUE, future.globals = c("grid", 
      "static"))

Code
  tune:::loop_call("resamples", "future", list(a = quote(a)))
Output
  future.apply::future_lapply(resamples, loop_over_all_stages, 
      grid = grid, static = static, a = a, future.label = "tune-grid-%d", 
      future.stdout = TRUE, future.seed = TRUE, future.globals = c("grid", 
      "static", "a"))

Code
  tune:::loop_call("everything", "future", list())
Output
  future.apply::future_lapply(inds, loop_over_all_stages2, resamples = resamples, 
      grid = candidates, static = static, future.label = "tune-grid-%d", 
      future.stdout = TRUE, future.seed = TRUE, future.globals = c("resamples", 
      "grid", "static"))

Code
  tune:::loop_call("everything", "future", list(a = quote(a)))
Output
  future.apply::future_lapply(inds, loop_over_all_stages2, resamples = resamples, 
      grid = candidates, static = static, a = a, future.label = "tune-grid-%d", 
      future.stdout = TRUE, future.seed = TRUE, future.globals = c("resamples", 
      "grid", "static", "a"))

Code
  tune:::loop_call("resamples", "mirai", list())
Output
  eval_mirai(resamples, loop_over_all_stages, .args = list(grid = grid, 
      static = static))

Code
  tune:::loop_call("resamples", "mirai", list(a = quote(a)))
Output
  eval_mirai(resamples, loop_over_all_stages, .args = list(grid = grid, 
      static = static, a = a))

Code
  tune:::loop_call("everything", "mirai", list())
Output
  eval_mirai(inds, loop_over_all_stages2, .args = list(resamples = resamples, 
      grid = candidates, static = static))

Code
  tune:::loop_call("everything", "mirai", list(a = quote(a)))
Output
  eval_mirai(inds, loop_over_all_stages2, .args = list(resamples = resamples, 
      grid = candidates, static = static, a = a))