tab_icl2_control.RdControl TabICL2 inference execution
A character string or NULL for the torch device (e.g.,
"cpu", "cuda", "mps"). Applied to all three transformer stages.
A logical. Enable automatic mixed precision. Applied to all stages.
A logical. Enable Flash Attention 3 kernels. Applied to all stages.
A logical. Enable verbose logging. Applied to all stages.
A positive integer. Minimum batch size passed to the memory manager. Applied to all stages.
A number in [0, 1]. Memory safety margin for batch size estimation. Applied to all stages.
A logical or one of "auto", "gpu", "cpu", "disk".
Offload strategy for the column-embedding (COL) stage. Row-interaction
(ROW) and in-context-learning (ICL) stages default to FALSE unless
overridden via row_config/icl_config.
A logical. Bypass the default data size limits on training set rows (50,000) and predictors (2,000).
A named list of additional settings for the COL stage, overriding any of the defaults or parameters above.
A named list of additional settings for the ROW stage.
A named list of additional settings for the ICL stage.
Additional named arguments stored in the returned control object.
Use this for settings not covered above (e.g. auto_offload_threshold,
disk_offload_dir, use_async, etc.) that apply uniformly. Per-stage
values must go in col_config, row_config, or icl_config.
A list with class "tab_icl2_control" containing resolved
per-stage settings in $col, $row, and $icl, plus
$ignore_pretraining_limits.
tab_icl2_control()
#> inference control for `tab_icl2()`
tab_icl2_control(use_amp = FALSE, offload = "cpu")
#> inference control for `tab_icl2()`
#>
#> COL stage non-default arguments:
#> • `use_amp`: FALSE
#> • `offload`: "cpu"
#> ROW stage non-default arguments:
#> • `use_amp`: FALSE
#> ICL stage non-default arguments:
#> • `use_amp`: FALSE
tab_icl2_control(col_config = list(disk_offload_dir = tempdir()))
#> inference control for `tab_icl2()`
#>
#> COL stage non-default arguments:
#> • `disk_offload_dir`: "/tmp/RtmpWOrcdx"
tab_icl2_control(ignore_pretraining_limits = TRUE)
#> inference control for `tab_icl2()`
#>
#> non-default top-level arguments:
#> • `col`: TRUE, TRUE, FALSE, 1, 0.8, auto, 0.5, 0.85, 32768, NULL, 1024, 8192,
#> TRUE, , NULL, 0.95, TRUE, and 4
#> • `row`: TRUE, TRUE, FALSE, 1, 0.8, FALSE, 0.5, 0.85, 32768, NULL, 1024, 8192,
#> TRUE, , NULL, 0.95, TRUE, and 4
#> • `icl`: TRUE, TRUE, FALSE, 1, 0.8, FALSE, 0.5, 0.85, 32768, NULL, 1024, 8192,
#> TRUE, , NULL, 0.95, TRUE, and 4
#> • `ignore_pretraining_limits`: TRUE