Applies element-wise \(Sigmoid(x_i) = \frac{1}{1 + exp(-x_i)}\)
nn_module
Calls torch::nn_sigmoid() when trained.
Input and Output Channels
One input channel called "input" and one output channel called "output".
For an explanation see PipeOpTorch.
Super classes
mlr3pipelines::PipeOp -> PipeOpTorch -> PipeOpTorchSigmoid
Methods
PipeOpTorchSigmoid$new()
Creates a new instance of this R6 class.
Usage
PipeOpTorchSigmoid$new(id = "nn_sigmoid", param_vals = list())Arguments
id(
character(1))
Identifier of the resulting object.param_vals(
list())
List of hyperparameter settings, overwriting the hyperparameter settings that would otherwise be set during construction.
Examples
# Construct the PipeOp
pipeop = nn("sigmoid")
pipeop
#>
#> ── PipeOp <sigmoid>: not trained ───────────────────────────────────────────────
#> Values: list()
#>
#> ── Input channels:
#> name train predict
#> <char> <char> <char>
#> input ModelDescriptor Task
#>
#> ── Output channels:
#> name train predict
#> <char> <char> <char>
#> output ModelDescriptor Task
# The available parameters
pipeop$param_set
#> <ParamSet(0)>
#> Empty.