mlr_learners_torch_image {mlr3torch}

Image Learner

Description

Base Class for Image Learners. The features are assumed to be a single lazy_tensor column in RGB format.

Parameters

Parameters include those inherited from LearnerTorch and the param_set construction argument.

Super classes

mlr3::Learner -> mlr3torch::LearnerTorch -> LearnerTorchImage

Methods

Public methods

• LearnerTorchImage$new()

• LearnerTorchImage$clone()

Inherited methods

• mlr3::Learner$base_learner()
• mlr3::Learner$help()
• mlr3::Learner$predict()
• mlr3::Learner$predict_newdata()
• mlr3::Learner$reset()
• mlr3::Learner$train()
• mlr3torch::LearnerTorch$dataset()
• mlr3torch::LearnerTorch$format()
• mlr3torch::LearnerTorch$marshal()
• mlr3torch::LearnerTorch$print()
• mlr3torch::LearnerTorch$unmarshal()

Method new()

Creates a new instance of this R6 class.

Usage

LearnerTorchImage$new(
  id,
  task_type,
  param_set = ps(),
  label,
  optimizer = NULL,
  loss = NULL,
  callbacks = list(),
  packages = c("torchvision", "magick"),
  man,
  properties = NULL,
  predict_types = NULL
)

Arguments

id

(character(1))
The id for of the new object.

task_type

(character(1))
The task type.

param_set

(ParamSet)
The parameter set.

label

(character(1))
Label for the new instance.

optimizer

(TorchOptimizer)
The torch optimizer.

loss

(TorchLoss)
The loss to use for training.

callbacks

(list() of TorchCallbacks)
The callbacks used during training. Must have unique ids. They are executed in the order in which they are provided

packages

(character())
The R packages this object depends on.

man

(character(1))
String in the format ⁠[pkg]::[topic]⁠ pointing to a manual page for this object. The referenced help package can be opened via method ⁠$help()⁠.

properties

(character())
The properties of the object. See mlr_reflections$learner_properties for available values.

predict_types

(character())
The predict types. See mlr_reflections$learner_predict_types for available values.

Method clone()

The objects of this class are cloneable with this method.

Usage

LearnerTorchImage$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

See Also

Other Learner: mlr_learners.mlp, mlr_learners.tab_resnet, mlr_learners.torch_featureless, mlr_learners_torch, mlr_learners_torch_model