FTTransformer Auto — AutoFTTransformer • mlr3automl

FTTransformer auto.

Value

Object of class R6::R6Class and AutoFTTransformer.

Super class

Auto -> AutoFTTransformer

Methods

Public methods

AutoFTTransformer$new()
AutoFTTransformer$graph()
AutoFTTransformer$estimate_memory()
AutoFTTransformer$clone()

Inherited methods

`AutoFTTransformer$new()`

Creates a new instance of this R6 class.

Usage

AutoFTTransformer$new(id = "ft_transformer")

Arguments

id: (character(1))
Identifier for the new instance.

`AutoFTTransformer$graph()`

Create the graph for the auto.

Usage

AutoFTTransformer$graph(task, measure, n_threads, timeout, devices)

Arguments

task: (mlr3::Task).
measure: (mlr3::Measure).
n_threads: (integer(1)).
timeout: (integer(1)).
devices: (character())
Devices to use. Allowed values are "cpu" and "cuda". Default is "cpu".

`AutoFTTransformer$estimate_memory()`

Estimate the memory for the auto.

Usage

AutoFTTransformer$estimate_memory(task)

Arguments

task: (mlr3::Task).

`AutoFTTransformer$clone()`

The objects of this class are cloneable with this method.

Usage

AutoFTTransformer$clone(deep = FALSE)

Arguments

deep: Whether to make a deep clone.

Examples

auto("ft_transformer")
#> <AutoFTTransformer>
#>   Inherits from: <Auto>
#>   Public:
#>     check: function (task, memory_limit = Inf, large_data_set = FALSE, devices) 
#>     clone: function (deep = FALSE) 
#>     design_default: function (task) 
#>     design_set: function (task, measure, size) 
#>     devices: cuda cpu
#>     early_stopping_rounds: function (task, budget = Inf) 
#>     estimate_memory: function (task) 
#>     finalize_model: function (graph_learner) 
#>     graph: function (task, measure, n_threads, timeout, devices) 
#>     id: ft_transformer
#>     initialize: function (id = "ft_transformer") 
#>     packages: mlr3 mlr3torch
#>     properties: internal_tuning
#>     search_space: function (task) 
#>     task_types: classif regr
#>   Private:
#>     .default_values: list
#>     .search_space: ParamSet, R6